From 2814b80db21c55f574cabf1d1e34958c3c290482 Mon Sep 17 00:00:00 2001 From: aws-sdk-python-automation Date: Fri, 20 Dec 2024 19:04:16 +0000 Subject: [PATCH] Update to latest models --- .../api-change-bedrockagent-36826.json | 5 + .../api-change-bedrockagentruntime-35124.json | 5 + ...pi-change-bedrockdataautomation-64708.json | 5 + ...ge-bedrockdataautomationruntime-88987.json | 5 + .../api-change-billing-97262.json | 5 + .changes/next-release/api-change-ce-7851.json | 5 + .../api-change-connect-82198.json | 5 + .../next-release/api-change-docdb-94266.json | 5 + .../next-release/api-change-eks-49199.json | 5 + .../next-release/api-change-macie2-74869.json | 5 + .../api-change-outposts-24239.json | 5 + .../api-change-sagemaker-78861.json | 5 + .../2023-07-26/service-2.json | 102 ++- .../bedrock-agent/2023-06-05/service-2.json | 48 +- .../2024-06-13/service-2.json | 2 +- .../2023-07-26/service-2.json | 24 +- .../data/billing/2023-09-07/paginators-1.json | 6 + .../data/billing/2023-09-07/service-2.json | 698 +++++++++++++++++- botocore/data/ce/2017-10-25/service-2.json | 55 +- .../data/connect/2017-08-08/service-2.json | 23 +- botocore/data/docdb/2014-10-31/service-2.json | 42 ++ botocore/data/eks/2017-11-01/service-2.json | 22 + .../data/macie2/2020-01-01/service-2.json | 71 +- .../data/outposts/2019-12-03/service-2.json | 7 +- .../data/sagemaker/2017-07-24/service-2.json | 346 +++++---- 25 files changed, 1278 insertions(+), 228 deletions(-) create mode 100644 .changes/next-release/api-change-bedrockagent-36826.json create mode 100644 .changes/next-release/api-change-bedrockagentruntime-35124.json create mode 100644 .changes/next-release/api-change-bedrockdataautomation-64708.json create mode 100644 .changes/next-release/api-change-bedrockdataautomationruntime-88987.json create mode 100644 .changes/next-release/api-change-billing-97262.json create mode 100644 .changes/next-release/api-change-ce-7851.json create mode 100644 .changes/next-release/api-change-connect-82198.json create mode 100644 .changes/next-release/api-change-docdb-94266.json create mode 100644 .changes/next-release/api-change-eks-49199.json create mode 100644 .changes/next-release/api-change-macie2-74869.json create mode 100644 .changes/next-release/api-change-outposts-24239.json create mode 100644 .changes/next-release/api-change-sagemaker-78861.json diff --git a/.changes/next-release/api-change-bedrockagent-36826.json b/.changes/next-release/api-change-bedrockagent-36826.json new file mode 100644 index 0000000000..e1f02c1db8 --- /dev/null +++ b/.changes/next-release/api-change-bedrockagent-36826.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-agent``", + "description": "Support for custom user agent and max web pages crawled for web connector. Support app only credentials for SharePoint connector. Increase agents memory duration limit to 365 days. Support to specify max number of session summaries to include in agent invocation context." +} diff --git a/.changes/next-release/api-change-bedrockagentruntime-35124.json b/.changes/next-release/api-change-bedrockagentruntime-35124.json new file mode 100644 index 0000000000..f4cde6938e --- /dev/null +++ b/.changes/next-release/api-change-bedrockagentruntime-35124.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-agent-runtime``", + "description": "bedrock agents now supports long term memory and performance configs. Invokeflow supports performance configs. RetrieveAndGenerate performance configs" +} diff --git a/.changes/next-release/api-change-bedrockdataautomation-64708.json b/.changes/next-release/api-change-bedrockdataautomation-64708.json new file mode 100644 index 0000000000..e0c7d41518 --- /dev/null +++ b/.changes/next-release/api-change-bedrockdataautomation-64708.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-data-automation``", + "description": "Documentation update for Amazon Bedrock Data Automation" +} diff --git a/.changes/next-release/api-change-bedrockdataautomationruntime-88987.json b/.changes/next-release/api-change-bedrockdataautomationruntime-88987.json new file mode 100644 index 0000000000..3541f8edc4 --- /dev/null +++ b/.changes/next-release/api-change-bedrockdataautomationruntime-88987.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-data-automation-runtime``", + "description": "Documentation update for Amazon Bedrock Data Automation Runtime" +} diff --git a/.changes/next-release/api-change-billing-97262.json b/.changes/next-release/api-change-billing-97262.json new file mode 100644 index 0000000000..98d99566ff --- /dev/null +++ b/.changes/next-release/api-change-billing-97262.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``billing``", + "description": "Added new API's for defining and fetching Billing Views." +} diff --git a/.changes/next-release/api-change-ce-7851.json b/.changes/next-release/api-change-ce-7851.json new file mode 100644 index 0000000000..d93885ed08 --- /dev/null +++ b/.changes/next-release/api-change-ce-7851.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``ce``", + "description": "Support for retrieving cost, usage, and forecast for billing view." +} diff --git a/.changes/next-release/api-change-connect-82198.json b/.changes/next-release/api-change-connect-82198.json new file mode 100644 index 0000000000..53c8e8f6b8 --- /dev/null +++ b/.changes/next-release/api-change-connect-82198.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``connect``", + "description": "This release supports adding NotAttributeCondition and Range to the RoutingCriteria object." +} diff --git a/.changes/next-release/api-change-docdb-94266.json b/.changes/next-release/api-change-docdb-94266.json new file mode 100644 index 0000000000..418afc90d8 --- /dev/null +++ b/.changes/next-release/api-change-docdb-94266.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``docdb``", + "description": "Support AWS Secret Manager managed password for AWS DocumentDB instance-based cluster." +} diff --git a/.changes/next-release/api-change-eks-49199.json b/.changes/next-release/api-change-eks-49199.json new file mode 100644 index 0000000000..1d0062d152 --- /dev/null +++ b/.changes/next-release/api-change-eks-49199.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``eks``", + "description": "This release expands the catalog of upgrade insight checks" +} diff --git a/.changes/next-release/api-change-macie2-74869.json b/.changes/next-release/api-change-macie2-74869.json new file mode 100644 index 0000000000..5b5d5207ca --- /dev/null +++ b/.changes/next-release/api-change-macie2-74869.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``macie2``", + "description": "This release adds support for identifying S3 general purpose buckets that exceed the Amazon Macie quota for preventative control monitoring." +} diff --git a/.changes/next-release/api-change-outposts-24239.json b/.changes/next-release/api-change-outposts-24239.json new file mode 100644 index 0000000000..43ea1e2814 --- /dev/null +++ b/.changes/next-release/api-change-outposts-24239.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``outposts``", + "description": "Add CS8365C as a supported power connector for Outpost sites." +} diff --git a/.changes/next-release/api-change-sagemaker-78861.json b/.changes/next-release/api-change-sagemaker-78861.json new file mode 100644 index 0000000000..a93886df54 --- /dev/null +++ b/.changes/next-release/api-change-sagemaker-78861.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``sagemaker``", + "description": "This release adds support for c6i, m6i and r6i instance on SageMaker Hyperpod and trn1 instances in batch" +} diff --git a/botocore/data/bedrock-agent-runtime/2023-07-26/service-2.json b/botocore/data/bedrock-agent-runtime/2023-07-26/service-2.json index ae45ead207..36c06b21b6 100644 --- a/botocore/data/bedrock-agent-runtime/2023-07-26/service-2.json +++ b/botocore/data/bedrock-agent-runtime/2023-07-26/service-2.json @@ -91,6 +91,7 @@ "input":{"shape":"InvokeAgentRequest"}, "output":{"shape":"InvokeAgentResponse"}, "errors":[ + {"shape":"ModelNotReadyException"}, {"shape":"ConflictException"}, {"shape":"ResourceNotFoundException"}, {"shape":"ValidationException"}, @@ -101,7 +102,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ServiceQuotaExceededException"} ], - "documentation":"

The CLI doesn't support streaming operations in Amazon Bedrock, including InvokeAgent.

Sends a prompt for the agent to process and respond to. Note the following fields for the request:

The response is returned in the bytes field of the chunk object.

" + "documentation":"

The CLI doesn't support streaming operations in Amazon Bedrock, including InvokeAgent.

Sends a prompt for the agent to process and respond to. Note the following fields for the request:

The response is returned in the bytes field of the chunk object.

" }, "InvokeFlow":{ "name":"InvokeFlow", @@ -417,7 +418,7 @@ }, "parentActionGroupSignature":{ "shape":"ActionGroupSignature", - "documentation":"

To allow your agent to request the user for additional information when trying to complete a task, set this field to AMAZON.UserInput. You must leave the description, apiSchema, and actionGroupExecutor fields blank for this action group.

To allow your agent to generate, run, and troubleshoot code when trying to complete a task, set this field to AMAZON.CodeInterpreter. You must leave the description, apiSchema, and actionGroupExecutor fields blank for this action group.

During orchestration, if your agent determines that it needs to invoke an API in an action group, but doesn't have enough information to complete the API request, it will invoke this action group instead and return an Observation reprompting the user for more information.

" + "documentation":"

To allow your agent to request the user for additional information when trying to complete a task, set this field to AMAZON.UserInput. You must leave the description, apiSchema, and actionGroupExecutor fields blank for this action group.

To allow your agent to generate, run, and troubleshoot code when trying to complete a task, set this field to AMAZON.CodeInterpreter. You must leave the description, apiSchema, and actionGroupExecutor fields blank for this action group.

During orchestration, if your agent determines that it needs to invoke an API in an action group, but doesn't have enough information to complete the API request, it will invoke this action group instead and return an Observation reprompting the user for more information.

" } }, "documentation":"

Contains details of the inline agent's action group.

" @@ -702,6 +703,16 @@ "min":1, "pattern":"^(arn:aws(-[^:]+)?:(bedrock|sagemaker):[a-z0-9-]{1,20}:([0-9]{12})?:([a-z-]+/)?)?([a-z0-9.-]{1,63}){0,2}(([:][a-z0-9-]{1,63}){0,2})?(/[a-z0-9]{1,12})?$" }, + "BedrockModelConfigurations":{ + "type":"structure", + "members":{ + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The performance configuration for the model.

" + } + }, + "documentation":"

Settings for a model called with InvokeAgent.

" + }, "BedrockRerankingConfiguration":{ "type":"structure", "required":["modelConfiguration"], @@ -1012,6 +1023,12 @@ "documentation":"

The unique identifier of the memory.

", "location":"querystring", "locationName":"memoryId" + }, + "sessionId":{ + "shape":"SessionId", + "documentation":"

The unique session identifier of the memory.

", + "location":"querystring", + "locationName":"sessionId" } } }, @@ -1100,6 +1117,10 @@ "shape":"InferenceConfig", "documentation":"

Configuration settings for inference when using RetrieveAndGenerate to generate responses while using an external source.

" }, + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The latency configuration for the model.

" + }, "promptTemplate":{ "shape":"PromptTemplate", "documentation":"

Contain the textPromptTemplate string for the external source wrapper object.

" @@ -1834,6 +1855,10 @@ "shape":"InferenceConfig", "documentation":"

Configuration settings for inference when using RetrieveAndGenerate to generate responses while using a knowledge base as a source.

" }, + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The latency configuration for the model.

" + }, "promptTemplate":{ "shape":"PromptTemplate", "documentation":"

Contains the template for the prompt that's sent to the model for response generation. Generation prompts must include the $search_results$ variable. For more information, see Use placeholder variables in the user guide.

" @@ -2493,6 +2518,16 @@ "event":true, "sensitive":true }, + "InlineBedrockModelConfigurations":{ + "type":"structure", + "members":{ + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The latency configuration for the model.

" + } + }, + "documentation":"

Settings for a model called with InvokeInlineAgent.

" + }, "InlineSessionState":{ "type":"structure", "members":{ @@ -2683,6 +2718,10 @@ "location":"uri", "locationName":"agentId" }, + "bedrockModelConfigurations":{ + "shape":"BedrockModelConfigurations", + "documentation":"

Model performance settings for the request.

" + }, "enableTrace":{ "shape":"Boolean", "documentation":"

Specifies whether to turn on the trace or not to track the agent's reasoning process. For more information, see Trace enablement.

" @@ -2717,7 +2756,7 @@ }, "streamingConfigurations":{ "shape":"StreamingConfigurations", - "documentation":"

Specifies the configurations for streaming.

" + "documentation":"

Specifies the configurations for streaming.

To use agent streaming, you need permissions to perform the bedrock:InvokeModelWithResponseStream action.

" } } }, @@ -2781,6 +2820,10 @@ "inputs":{ "shape":"FlowInputs", "documentation":"

A list of objects, each containing information about an input into the flow.

" + }, + "modelPerformanceConfiguration":{ + "shape":"ModelPerformanceConfiguration", + "documentation":"

Model performance settings for the request.

" } } }, @@ -2807,6 +2850,10 @@ "shape":"AgentActionGroups", "documentation":"

A list of action groups with each action group defining the action the inline agent needs to carry out.

" }, + "bedrockModelConfigurations":{ + "shape":"InlineBedrockModelConfigurations", + "documentation":"

Model settings for the request.

" + }, "customerEncryptionKeyArn":{ "shape":"KmsKeyArn", "documentation":"

The Amazon Resource Name (ARN) of the Amazon Web Services KMS key to use to encrypt your inline agent.

" @@ -3313,6 +3360,28 @@ "documentation":"

The input for the pre-processing step.

", "sensitive":true }, + "ModelNotReadyException":{ + "type":"structure", + "members":{ + "message":{"shape":"NonBlankString"} + }, + "documentation":"

The model specified in the request is not ready to serve inference requests. The AWS SDK will automatically retry the operation up to 5 times. For information about configuring automatic retries, see Retry behavior in the AWS SDKs and Tools reference guide.

", + "error":{ + "httpStatusCode":424, + "senderFault":true + }, + "exception":true + }, + "ModelPerformanceConfiguration":{ + "type":"structure", + "members":{ + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The latency configuration for the model.

" + } + }, + "documentation":"

The performance configuration for a model called with InvokeFlow.

" + }, "Name":{ "type":"string", "pattern":"^([0-9a-zA-Z][_-]?){1,100}$", @@ -3498,6 +3567,10 @@ "shape":"InferenceConfig", "documentation":"

Configuration settings for inference when using RetrieveAndGenerate to generate responses while using a knowledge base as a source.

" }, + "performanceConfig":{ + "shape":"PerformanceConfiguration", + "documentation":"

The latency configuration for the model.

" + }, "promptTemplate":{ "shape":"PromptTemplate", "documentation":"

Contains the template for the prompt that's sent to the model. Orchestration prompts must include the $conversation_history$ and $output_format_instructions$ variables. For more information, see Use placeholder variables in the user guide.

" @@ -3687,6 +3760,23 @@ "RETURN_CONTROL" ] }, + "PerformanceConfigLatency":{ + "type":"string", + "enum":[ + "standard", + "optimized" + ] + }, + "PerformanceConfiguration":{ + "type":"structure", + "members":{ + "latency":{ + "shape":"PerformanceConfigLatency", + "documentation":"

To use a latency-optimized version of the model, set to optimized.

" + } + }, + "documentation":"

Performance settings for a model.

" + }, "PostProcessingModelInvocationOutput":{ "type":"structure", "members":{ @@ -4291,6 +4381,10 @@ "shape":"InternalServerException", "documentation":"

An internal server error occurred. Retry your request.

" }, + "modelNotReadyException":{ + "shape":"ModelNotReadyException", + "documentation":"

The model specified in the request is not ready to serve Inference requests. The AWS SDK will automatically retry the operation up to 5 times. For information about configuring automatic retries, see Retry behavior in the AWS SDKs and Tools reference guide.

" + }, "resourceNotFoundException":{ "shape":"ResourceNotFoundException", "documentation":"

The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.

" @@ -5153,7 +5247,7 @@ "documentation":"

Specifies whether to enable streaming for the final response. This is set to false by default.

" } }, - "documentation":"

Configurations for streaming.

" + "documentation":"

Configurations for streaming.

" }, "StreamingConfigurationsApplyGuardrailIntervalInteger":{ "type":"integer", diff --git a/botocore/data/bedrock-agent/2023-06-05/service-2.json b/botocore/data/bedrock-agent/2023-06-05/service-2.json index a163630509..fa10799769 100644 --- a/botocore/data/bedrock-agent/2023-06-05/service-2.json +++ b/botocore/data/bedrock-agent/2023-06-05/service-2.json @@ -7213,6 +7213,11 @@ }, "documentation":"

Details about a malformed input expression in a node.

" }, + "MaxRecentSessions":{ + "type":"integer", + "box":true, + "min":1 + }, "MaxResults":{ "type":"integer", "box":true, @@ -7233,6 +7238,10 @@ "shape":"EnabledMemoryTypes", "documentation":"

The type of memory that is stored.

" }, + "sessionSummaryConfiguration":{ + "shape":"SessionSummaryConfiguration", + "documentation":"

Contains the configuration for SESSION_SUMMARY memory type enabled for the agent.

" + }, "storageDays":{ "shape":"StorageDays", "documentation":"

The number of days the agent is configured to retain the conversational context.

" @@ -8297,7 +8306,8 @@ "PRE_PROCESSING", "ORCHESTRATION", "POST_PROCESSING", - "KNOWLEDGE_BASE_RESPONSE_GENERATION" + "KNOWLEDGE_BASE_RESPONSE_GENERATION", + "MEMORY_SUMMARIZATION" ] }, "PromptVariant":{ @@ -9099,6 +9109,16 @@ }, "exception":true }, + "SessionSummaryConfiguration":{ + "type":"structure", + "members":{ + "maxRecentSessions":{ + "shape":"MaxRecentSessions", + "documentation":"

Maximum number of recent session summaries to include in the agent's prompt context.

" + } + }, + "documentation":"

Configuration for SESSION_SUMMARY memory type enabled for the agent.

" + }, "SessionTTL":{ "type":"integer", "box":true, @@ -9107,7 +9127,10 @@ }, "SharePointAuthType":{ "type":"string", - "enum":["OAUTH2_CLIENT_CREDENTIALS"] + "enum":[ + "OAUTH2_CLIENT_CREDENTIALS", + "OAUTH2_SHAREPOINT_APP_ONLY_CLIENT_CREDENTIALS" + ] }, "SharePointCrawlerConfiguration":{ "type":"structure", @@ -9346,7 +9369,7 @@ "StorageDays":{ "type":"integer", "box":true, - "max":30, + "max":365, "min":0 }, "StorageFlowNodeConfiguration":{ @@ -10506,6 +10529,12 @@ }, "documentation":"

The configuration of web URLs that you want to crawl. You should be authorized to crawl the URLs.

" }, + "UserAgent":{ + "type":"string", + "max":40, + "min":15, + "sensitive":true + }, "ValidateFlowDefinitionRequest":{ "type":"structure", "required":["definition"], @@ -10625,6 +10654,10 @@ "scope":{ "shape":"WebScopeType", "documentation":"

The scope of what is crawled for your URLs.

You can choose to crawl only web pages that belong to the same host or primary domain. For example, only web pages that contain the seed URL \"https://docs.aws.amazon.com/bedrock/latest/userguide/\" and no other domains. You can choose to include sub domains in addition to the host or primary domain. For example, web pages that contain \"aws.amazon.com\" can also include sub domain \"docs.aws.amazon.com\".

" + }, + "userAgent":{ + "shape":"UserAgent", + "documentation":"

A string used for identifying the crawler or a bot when it accesses a web server. By default, this is set to bedrockbot_UUID for your crawler. You can optionally append a custom string to bedrockbot_UUID to allowlist a specific user agent permitted to access your source URLs.

" } }, "documentation":"

The configuration of web URLs that you want to crawl. You should be authorized to crawl the URLs.

" @@ -10632,6 +10665,10 @@ "WebCrawlerLimits":{ "type":"structure", "members":{ + "maxPages":{ + "shape":"WebCrawlerLimitsMaxPagesInteger", + "documentation":"

The max number of web pages crawled from your source URLs, up to 25,000 pages. If the web pages exceed this limit, the data source sync will fail and no web pages will be ingested.

" + }, "rateLimit":{ "shape":"WebCrawlerLimitsRateLimitInteger", "documentation":"

The max rate at which pages are crawled, up to 300 per minute per host.

" @@ -10639,6 +10676,11 @@ }, "documentation":"

The rate limits for the URLs that you want to crawl. You should be authorized to crawl the URLs.

" }, + "WebCrawlerLimitsMaxPagesInteger":{ + "type":"integer", + "box":true, + "min":1 + }, "WebCrawlerLimitsRateLimitInteger":{ "type":"integer", "box":true, diff --git a/botocore/data/bedrock-data-automation-runtime/2024-06-13/service-2.json b/botocore/data/bedrock-data-automation-runtime/2024-06-13/service-2.json index 859ea45c7f..eae6630dfb 100644 --- a/botocore/data/bedrock-data-automation-runtime/2024-06-13/service-2.json +++ b/botocore/data/bedrock-data-automation-runtime/2024-06-13/service-2.json @@ -390,5 +390,5 @@ "exception":true } }, - "documentation":"

Amazon Bedrock Keystone Runtime

" + "documentation":"

Amazon Bedrock Data Automation Runtime

" } diff --git a/botocore/data/bedrock-data-automation/2023-07-26/service-2.json b/botocore/data/bedrock-data-automation/2023-07-26/service-2.json index d1f082192f..b99a0efc9a 100644 --- a/botocore/data/bedrock-data-automation/2023-07-26/service-2.json +++ b/botocore/data/bedrock-data-automation/2023-07-26/service-2.json @@ -30,7 +30,7 @@ {"shape":"ThrottlingException"}, {"shape":"AccessDeniedException"} ], - "documentation":"

Creates an Amazon Bedrock Keystone Blueprint

", + "documentation":"

Creates an Amazon Bedrock Data Automation Blueprint

", "idempotent":true }, "CreateBlueprintVersion":{ @@ -50,7 +50,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Creates a new version of an existing Amazon Bedrock Keystone Blueprint

", + "documentation":"

Creates a new version of an existing Amazon Bedrock Data Automation Blueprint

", "idempotent":true }, "CreateDataAutomationProject":{ @@ -70,7 +70,7 @@ {"shape":"ThrottlingException"}, {"shape":"AccessDeniedException"} ], - "documentation":"

Creates an Amazon Bedrock Keystone DataAutomationProject

", + "documentation":"

Creates an Amazon Bedrock Data Automation Project

", "idempotent":true }, "DeleteBlueprint":{ @@ -89,7 +89,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Deletes an existing Amazon Bedrock Keystone Blueprint

", + "documentation":"

Deletes an existing Amazon Bedrock Data Automation Blueprint

", "idempotent":true }, "DeleteDataAutomationProject":{ @@ -108,7 +108,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Deletes an existing Amazon Bedrock Keystone DataAutomationProject

", + "documentation":"

Deletes an existing Amazon Bedrock Data Automation Project

", "idempotent":true }, "GetBlueprint":{ @@ -127,7 +127,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Gets an existing Amazon Bedrock Keystone Blueprint

" + "documentation":"

Gets an existing Amazon Bedrock Data Automation Blueprint

" }, "GetDataAutomationProject":{ "name":"GetDataAutomationProject", @@ -145,7 +145,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Gets an existing Amazon Bedrock Keystone DataAutomationProject

" + "documentation":"

Gets an existing Amazon Bedrock Data Automation Project

" }, "ListBlueprints":{ "name":"ListBlueprints", @@ -163,7 +163,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Lists all existing Amazon Bedrock Keystone Blueprints

" + "documentation":"

Lists all existing Amazon Bedrock Data Automation Blueprints

" }, "ListDataAutomationProjects":{ "name":"ListDataAutomationProjects", @@ -181,7 +181,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Lists all existing Amazon Bedrock Keystone DataAutomationProjects

" + "documentation":"

Lists all existing Amazon Bedrock Data Automation Projects

" }, "UpdateBlueprint":{ "name":"UpdateBlueprint", @@ -200,7 +200,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Updates an existing Amazon Bedrock Blueprint

", + "documentation":"

Updates an existing Amazon Bedrock Data Automation Blueprint

", "idempotent":true }, "UpdateDataAutomationProject":{ @@ -220,7 +220,7 @@ {"shape":"AccessDeniedException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"

Updates an existing Amazon Bedrock DataAutomationProject

", + "documentation":"

Updates an existing Amazon Bedrock Data Automation Project

", "idempotent":true } }, @@ -1243,5 +1243,5 @@ "documentation":"

Standard Output Configuration of Video

" } }, - "documentation":"

Amazon Bedrock Keystone Build

" + "documentation":"

Amazon Bedrock Data Automation BuildTime

" } diff --git a/botocore/data/billing/2023-09-07/paginators-1.json b/botocore/data/billing/2023-09-07/paginators-1.json index 73eb95fc8d..bc7789184d 100644 --- a/botocore/data/billing/2023-09-07/paginators-1.json +++ b/botocore/data/billing/2023-09-07/paginators-1.json @@ -5,6 +5,12 @@ "output_token": "nextToken", "limit_key": "maxResults", "result_key": "billingViews" + }, + "ListSourceViewsForBillingView": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "sourceViews" } } } diff --git a/botocore/data/billing/2023-09-07/service-2.json b/botocore/data/billing/2023-09-07/service-2.json index bb55ce95e4..dae674f992 100644 --- a/botocore/data/billing/2023-09-07/service-2.json +++ b/botocore/data/billing/2023-09-07/service-2.json @@ -15,6 +15,77 @@ "uid":"billing-2023-09-07" }, "operations":{ + "CreateBillingView":{ + "name":"CreateBillingView", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"CreateBillingViewRequest"}, + "output":{"shape":"CreateBillingViewResponse"}, + "errors":[ + {"shape":"ServiceQuotaExceededException"}, + {"shape":"ThrottlingException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Creates a billing view with the specified billing view attributes.

", + "idempotent":true + }, + "DeleteBillingView":{ + "name":"DeleteBillingView", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"DeleteBillingViewRequest"}, + "output":{"shape":"DeleteBillingViewResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Deletes the specified billing view.

", + "idempotent":true + }, + "GetBillingView":{ + "name":"GetBillingView", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"GetBillingViewRequest"}, + "output":{"shape":"GetBillingViewResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Returns the metadata associated to the specified billing view ARN.

" + }, + "GetResourcePolicy":{ + "name":"GetResourcePolicy", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"GetResourcePolicyRequest"}, + "output":{"shape":"GetResourcePolicyResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Returns the resource-based policy document attached to the resource in JSON format.

" + }, "ListBillingViews":{ "name":"ListBillingViews", "http":{ @@ -30,6 +101,94 @@ {"shape":"InternalServerException"} ], "documentation":"

Lists the billing views available for a given time period.

Every Amazon Web Services account has a unique PRIMARY billing view that represents the billing data available by default. Accounts that use Billing Conductor also have BILLING_GROUP billing views representing pro forma costs associated with each created billing group.

" + }, + "ListSourceViewsForBillingView":{ + "name":"ListSourceViewsForBillingView", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"ListSourceViewsForBillingViewRequest"}, + "output":{"shape":"ListSourceViewsForBillingViewResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Lists the source views (managed Amazon Web Services billing views) associated with the billing view.

" + }, + "ListTagsForResource":{ + "name":"ListTagsForResource", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"ListTagsForResourceRequest"}, + "output":{"shape":"ListTagsForResourceResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Lists tags associated with the billing view resource.

" + }, + "TagResource":{ + "name":"TagResource", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"TagResourceRequest"}, + "output":{"shape":"TagResourceResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

An API operation for adding one or more tags (key-value pairs) to a resource.

" + }, + "UntagResource":{ + "name":"UntagResource", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"UntagResourceRequest"}, + "output":{"shape":"UntagResourceResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Removes one or more tags from a resource. Specify only tag keys in your request. Don't specify the value.

" + }, + "UpdateBillingView":{ + "name":"UpdateBillingView", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"UpdateBillingViewRequest"}, + "output":{"shape":"UpdateBillingViewResponse"}, + "errors":[ + {"shape":"ServiceQuotaExceededException"}, + {"shape":"ThrottlingException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

An API to update the attributes of the billing view.

", + "idempotent":true } }, "shapes":{ @@ -66,7 +225,58 @@ }, "BillingViewArn":{ "type":"string", - "pattern":"arn:aws[a-z-]*:(billing)::[0-9]{12}:billingview/[a-zA-Z0-9_\\+=\\.\\-@]{1,43}" + "pattern":"arn:aws[a-z-]*:(billing)::[0-9]{12}:billingview/[a-zA-Z0-9/:_\\+=\\.\\-@]{0,59}[a-zA-Z0-9]" + }, + "BillingViewArnList":{ + "type":"list", + "member":{"shape":"BillingViewArn"}, + "max":10, + "min":0 + }, + "BillingViewDescription":{ + "type":"string", + "max":1024, + "min":0, + "pattern":"([ a-zA-Z0-9_\\+=\\.\\-@]+)?", + "sensitive":true + }, + "BillingViewElement":{ + "type":"structure", + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "name":{ + "shape":"BillingViewName", + "documentation":"

A list of names of the billing view.

" + }, + "description":{ + "shape":"BillingViewDescription", + "documentation":"

The description of the billing view.

" + }, + "billingViewType":{ + "shape":"BillingViewType", + "documentation":"

The type of billing group.

" + }, + "ownerAccountId":{ + "shape":"AccountId", + "documentation":"

The list of owners of the billing view.

" + }, + "dataFilterExpression":{ + "shape":"Expression", + "documentation":"

See Expression. Billing view only supports LINKED_ACCOUNT and Tags.

" + }, + "createdAt":{ + "shape":"Timestamp", + "documentation":"

The time when the billing view was created.

" + }, + "updatedAt":{ + "shape":"Timestamp", + "documentation":"

The time when the billing view was last updated.

" + } + }, + "documentation":"

The metadata associated to the billing view.

" }, "BillingViewList":{ "type":"list", @@ -83,6 +293,10 @@ "shape":"BillingViewName", "documentation":"

A list of names of the Billing view.

" }, + "description":{ + "shape":"BillingViewDescription", + "documentation":"

The description of the billing view.

" + }, "ownerAccountId":{ "shape":"AccountId", "documentation":"

The list of owners of the Billing view.

" @@ -96,32 +310,218 @@ }, "BillingViewName":{ "type":"string", + "max":128, + "min":1, "pattern":"[ a-zA-Z0-9_\\+=\\.\\-@]+", "sensitive":true }, + "BillingViewSourceViewsList":{ + "type":"list", + "member":{"shape":"BillingViewArn"}, + "max":1, + "min":1 + }, "BillingViewType":{ "type":"string", "enum":[ "PRIMARY", - "BILLING_GROUP" + "BILLING_GROUP", + "CUSTOM" ] }, + "BillingViewTypeList":{ + "type":"list", + "member":{"shape":"BillingViewType"} + }, "BillingViewsMaxResults":{ "type":"integer", "box":true, "max":100, "min":1 }, + "ClientToken":{ + "type":"string", + "pattern":"[a-zA-Z0-9-]+" + }, + "ConflictException":{ + "type":"structure", + "required":[ + "message", + "resourceId", + "resourceType" + ], + "members":{ + "message":{"shape":"ErrorMessage"}, + "resourceId":{ + "shape":"ResourceId", + "documentation":"

The identifier for the service resource associated with the request.

" + }, + "resourceType":{ + "shape":"ResourceType", + "documentation":"

The type of resource associated with the request.

" + } + }, + "documentation":"

The requested operation would cause a conflict with the current state of a service resource associated with the request. Resolve the conflict before retrying this request.

", + "exception":true + }, + "CreateBillingViewRequest":{ + "type":"structure", + "required":[ + "name", + "sourceViews" + ], + "members":{ + "name":{ + "shape":"BillingViewName", + "documentation":"

The name of the billing view.

" + }, + "description":{ + "shape":"BillingViewDescription", + "documentation":"

The description of the billing view.

" + }, + "sourceViews":{ + "shape":"BillingViewSourceViewsList", + "documentation":"

A list of billing views used as the data source for the custom billing view.

" + }, + "dataFilterExpression":{ + "shape":"Expression", + "documentation":"

See Expression. Billing view only supports LINKED_ACCOUNT and Tags.

" + }, + "clientToken":{ + "shape":"ClientToken", + "documentation":"

A unique, case-sensitive identifier you specify to ensure idempotency of the request. Idempotency ensures that an API request completes no more than one time. If the original request completes successfully, any subsequent retries complete successfully without performing any further actions with an idempotent request.

", + "idempotencyToken":true + }, + "resourceTags":{ + "shape":"ResourceTagList", + "documentation":"

A list of key value map specifying tags associated to the billing view being created.

" + } + } + }, + "CreateBillingViewResponse":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "createdAt":{ + "shape":"Timestamp", + "documentation":"

The time when the billing view was created.

" + } + } + }, + "DeleteBillingViewRequest":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + } + } + }, + "DeleteBillingViewResponse":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + } + } + }, + "Dimension":{ + "type":"string", + "enum":["LINKED_ACCOUNT"] + }, + "DimensionValues":{ + "type":"structure", + "required":[ + "key", + "values" + ], + "members":{ + "key":{ + "shape":"Dimension", + "documentation":"

The names of the metadata types that you can use to filter and group your results.

" + }, + "values":{ + "shape":"Values", + "documentation":"

The metadata values that you can use to filter and group your results.

" + } + }, + "documentation":"

The metadata that you can use to filter and group your results.

" + }, "ErrorMessage":{ "type":"string", "max":1024, "min":0 }, + "Expression":{ + "type":"structure", + "members":{ + "dimensions":{ + "shape":"DimensionValues", + "documentation":"

The specific Dimension to use for Expression.

" + }, + "tags":{ + "shape":"TagValues", + "documentation":"

The specific Tag to use for Expression.

" + } + }, + "documentation":"

See Expression. Billing view only supports LINKED_ACCOUNT and Tags.

" + }, "FieldName":{ "type":"string", "max":100, "min":0 }, + "GetBillingViewRequest":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + } + } + }, + "GetBillingViewResponse":{ + "type":"structure", + "required":["billingView"], + "members":{ + "billingView":{ + "shape":"BillingViewElement", + "documentation":"

The billing view element associated with the specified ARN.

" + } + } + }, + "GetResourcePolicyRequest":{ + "type":"structure", + "required":["resourceArn"], + "members":{ + "resourceArn":{ + "shape":"ResourceArn", + "documentation":"

The Amazon Resource Name (ARN) of the billing view resource to which the policy is attached to.

" + } + } + }, + "GetResourcePolicyResponse":{ + "type":"structure", + "required":["resourceArn"], + "members":{ + "resourceArn":{ + "shape":"ResourceArn", + "documentation":"

The Amazon Resource Name (ARN) of the billing view resource to which the policy is attached to.

" + }, + "policy":{ + "shape":"PolicyDocument", + "documentation":"

The resource-based policy document attached to the resource in JSON format.

" + } + } + }, "InternalServerException":{ "type":"structure", "required":["message"], @@ -134,12 +534,23 @@ }, "ListBillingViewsRequest":{ "type":"structure", - "required":["activeTimeRange"], "members":{ "activeTimeRange":{ "shape":"ActiveTimeRange", "documentation":"

The time range for the billing views listed. PRIMARY billing view is always listed. BILLING_GROUP billing views are listed for time ranges when the associated billing group resource in Billing Conductor is active. The time range must be within one calendar month.

" }, + "arns":{ + "shape":"BillingViewArnList", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "billingViewTypes":{ + "shape":"BillingViewTypeList", + "documentation":"

The type of billing view.

" + }, + "ownerAccountId":{ + "shape":"AccountId", + "documentation":"

The list of owners of the billing view.

" + }, "maxResults":{ "shape":"BillingViewsMaxResults", "documentation":"

The maximum number of billing views to retrieve. Default is 100.

" @@ -164,11 +575,222 @@ } } }, + "ListSourceViewsForBillingViewRequest":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "maxResults":{ + "shape":"BillingViewsMaxResults", + "documentation":"

The number of entries a paginated response contains.

" + }, + "nextToken":{ + "shape":"PageToken", + "documentation":"

The pagination token that is used on subsequent calls to list billing views.

" + } + } + }, + "ListSourceViewsForBillingViewResponse":{ + "type":"structure", + "required":["sourceViews"], + "members":{ + "sourceViews":{ + "shape":"BillingViewSourceViewsList", + "documentation":"

A list of billing views used as the data source for the custom billing view.

" + }, + "nextToken":{ + "shape":"PageToken", + "documentation":"

The pagination token that is used on subsequent calls to list billing views.

" + } + } + }, + "ListTagsForResourceRequest":{ + "type":"structure", + "required":["resourceArn"], + "members":{ + "resourceArn":{ + "shape":"ResourceArn", + "documentation":"

The Amazon Resource Name (ARN) of the resource.

" + } + } + }, + "ListTagsForResourceResponse":{ + "type":"structure", + "members":{ + "resourceTags":{ + "shape":"ResourceTagList", + "documentation":"

A list of tag key value pairs that are associated with the resource.

" + } + } + }, "PageToken":{ "type":"string", "max":2047, "min":1 }, + "PolicyDocument":{"type":"string"}, + "QuotaCode":{ + "type":"string", + "max":1024, + "min":1 + }, + "ResourceArn":{ + "type":"string", + "pattern":"arn:aws[a-z-]*:(billing)::[0-9]{12}:[a-zA-Z0-9/:_\\+=\\.\\@-]{0,70}[a-zA-Z0-9]" + }, + "ResourceId":{ + "type":"string", + "max":1024, + "min":1 + }, + "ResourceNotFoundException":{ + "type":"structure", + "required":[ + "message", + "resourceId", + "resourceType" + ], + "members":{ + "message":{"shape":"ErrorMessage"}, + "resourceId":{ + "shape":"ResourceId", + "documentation":"

Value is a list of resource IDs that were not found.

" + }, + "resourceType":{ + "shape":"ResourceType", + "documentation":"

Value is the type of resource that was not found.

" + } + }, + "documentation":"

The specified ARN in the request doesn't exist.

", + "exception":true + }, + "ResourceTag":{ + "type":"structure", + "required":["key"], + "members":{ + "key":{ + "shape":"ResourceTagKey", + "documentation":"

The key that's associated with the tag.

" + }, + "value":{ + "shape":"ResourceTagValue", + "documentation":"

The value that's associated with the tag.

" + } + }, + "documentation":"

The tag structure that contains a tag key and value.

" + }, + "ResourceTagKey":{ + "type":"string", + "max":128, + "min":1 + }, + "ResourceTagKeyList":{ + "type":"list", + "member":{"shape":"ResourceTagKey"}, + "max":200, + "min":0 + }, + "ResourceTagList":{ + "type":"list", + "member":{"shape":"ResourceTag"}, + "max":200, + "min":0 + }, + "ResourceTagValue":{ + "type":"string", + "max":256, + "min":0 + }, + "ResourceType":{ + "type":"string", + "max":1024, + "min":1 + }, + "ServiceCode":{ + "type":"string", + "max":1024, + "min":1 + }, + "ServiceQuotaExceededException":{ + "type":"structure", + "required":[ + "message", + "resourceId", + "resourceType", + "serviceCode", + "quotaCode" + ], + "members":{ + "message":{"shape":"ErrorMessage"}, + "resourceId":{ + "shape":"ResourceId", + "documentation":"

The ID of the resource.

" + }, + "resourceType":{ + "shape":"ResourceType", + "documentation":"

The type of Amazon Web Services resource.

" + }, + "serviceCode":{ + "shape":"ServiceCode", + "documentation":"

The container for the serviceCode.

" + }, + "quotaCode":{ + "shape":"QuotaCode", + "documentation":"

The container for the quotaCode.

" + } + }, + "documentation":"

You've reached the limit of resources you can create, or exceeded the size of an individual resource.

", + "exception":true + }, + "TagKey":{ + "type":"string", + "max":1024, + "min":0, + "pattern":"[\\S\\s]*" + }, + "TagResourceRequest":{ + "type":"structure", + "required":[ + "resourceArn", + "resourceTags" + ], + "members":{ + "resourceArn":{ + "shape":"ResourceArn", + "documentation":"

The Amazon Resource Name (ARN) of the resource.

" + }, + "resourceTags":{ + "shape":"ResourceTagList", + "documentation":"

A list of tag key value pairs that are associated with the resource.

" + } + } + }, + "TagResourceResponse":{ + "type":"structure", + "members":{ + } + }, + "TagValues":{ + "type":"structure", + "required":[ + "key", + "values" + ], + "members":{ + "key":{ + "shape":"TagKey", + "documentation":"

The key for the tag.

" + }, + "values":{ + "shape":"Values", + "documentation":"

The specific value of the tag.

" + } + }, + "documentation":"

The values that are available for a tag.

" + }, "ThrottlingException":{ "type":"structure", "required":["message"], @@ -179,6 +801,64 @@ "exception":true }, "Timestamp":{"type":"timestamp"}, + "UntagResourceRequest":{ + "type":"structure", + "required":[ + "resourceArn", + "resourceTagKeys" + ], + "members":{ + "resourceArn":{ + "shape":"ResourceArn", + "documentation":"

The Amazon Resource Name (ARN) of the resource.

" + }, + "resourceTagKeys":{ + "shape":"ResourceTagKeyList", + "documentation":"

A list of tag key value pairs that are associated with the resource.

" + } + } + }, + "UntagResourceResponse":{ + "type":"structure", + "members":{ + } + }, + "UpdateBillingViewRequest":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "name":{ + "shape":"BillingViewName", + "documentation":"

The name of the billing view.

" + }, + "description":{ + "shape":"BillingViewDescription", + "documentation":"

The description of the billing view.

" + }, + "dataFilterExpression":{ + "shape":"Expression", + "documentation":"

See Expression. Billing view only supports LINKED_ACCOUNT and Tags.

" + } + } + }, + "UpdateBillingViewResponse":{ + "type":"structure", + "required":["arn"], + "members":{ + "arn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that can be used to uniquely identify the billing view.

" + }, + "updatedAt":{ + "shape":"Timestamp", + "documentation":"

The time when the billing view was last updated.

" + } + } + }, "ValidationException":{ "type":"structure", "required":[ @@ -229,6 +909,18 @@ "fieldValidationFailed", "other" ] + }, + "Value":{ + "type":"string", + "max":1024, + "min":0, + "pattern":"[\\S\\s]*" + }, + "Values":{ + "type":"list", + "member":{"shape":"Value"}, + "max":200, + "min":1 } }, "documentation":"

You can use the Billing API to programatically list the billing views available to you for a given time period. A billing view represents a set of billing data.

The Billing API provides the following endpoint:

https://billing.us-east-1.api.aws

" diff --git a/botocore/data/ce/2017-10-25/service-2.json b/botocore/data/ce/2017-10-25/service-2.json index f958c92655..77de36cd1e 100644 --- a/botocore/data/ce/2017-10-25/service-2.json +++ b/botocore/data/ce/2017-10-25/service-2.json @@ -199,7 +199,8 @@ {"shape":"BillExpirationException"}, {"shape":"DataUnavailableException"}, {"shape":"InvalidNextTokenException"}, - {"shape":"RequestChangedException"} + {"shape":"RequestChangedException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves cost and usage metrics for your account. You can specify which cost and usage-related metric that you want the request to return. For example, you can specify BlendedCosts or UsageQuantity. You can also filter and group your data by various dimensions, such as SERVICE or AZ, in a specific time range. For a complete list of valid dimensions, see the GetDimensionValues operation. Management account in an organization in Organizations have access to all member accounts.

For information about filter limitations, see Quotas and restrictions in the Billing and Cost Management User Guide.

" }, @@ -216,7 +217,8 @@ {"shape":"LimitExceededException"}, {"shape":"BillExpirationException"}, {"shape":"InvalidNextTokenException"}, - {"shape":"RequestChangedException"} + {"shape":"RequestChangedException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves cost and usage metrics with resources for your account. You can specify which cost and usage-related metric, such as BlendedCosts or UsageQuantity, that you want the request to return. You can also filter and group your data by various dimensions, such as SERVICE or AZ, in a specific time range. For a complete list of valid dimensions, see the GetDimensionValues operation. Management account in an organization in Organizations have access to all member accounts.

Hourly granularity is only available for EC2-Instances (Elastic Compute Cloud) resource-level data. All other resource-level data is available at daily granularity.

This is an opt-in only feature. You can enable this feature from the Cost Explorer Settings page. For information about how to access the Settings page, see Controlling Access for Cost Explorer in the Billing and Cost Management User Guide.

" }, @@ -233,7 +235,8 @@ {"shape":"BillExpirationException"}, {"shape":"DataUnavailableException"}, {"shape":"InvalidNextTokenException"}, - {"shape":"RequestChangedException"} + {"shape":"RequestChangedException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves an array of Cost Category names and values incurred cost.

If some Cost Category names and values are not associated with any cost, they will not be returned by this API.

" }, @@ -247,7 +250,8 @@ "output":{"shape":"GetCostForecastResponse"}, "errors":[ {"shape":"LimitExceededException"}, - {"shape":"DataUnavailableException"} + {"shape":"DataUnavailableException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves a forecast for how much Amazon Web Services predicts that you will spend over the forecast time period that you select, based on your past costs.

" }, @@ -264,7 +268,8 @@ {"shape":"BillExpirationException"}, {"shape":"DataUnavailableException"}, {"shape":"InvalidNextTokenException"}, - {"shape":"RequestChangedException"} + {"shape":"RequestChangedException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves all available filter values for a specified filter over a period of time. You can search the dimension values for an arbitrary string.

" }, @@ -412,7 +417,8 @@ {"shape":"BillExpirationException"}, {"shape":"DataUnavailableException"}, {"shape":"InvalidNextTokenException"}, - {"shape":"RequestChangedException"} + {"shape":"RequestChangedException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Queries for available tag keys and tag values for a specified period. You can search the tag values for an arbitrary string.

" }, @@ -427,7 +433,8 @@ "errors":[ {"shape":"LimitExceededException"}, {"shape":"DataUnavailableException"}, - {"shape":"UnresolvableUsageUnitException"} + {"shape":"UnresolvableUsageUnitException"}, + {"shape":"ResourceNotFoundException"} ], "documentation":"

Retrieves a forecast for how much Amazon Web Services predicts that you will use over the forecast time period that you select, based on your past usage.

" }, @@ -1000,6 +1007,12 @@ "documentation":"

The requested report expired. Update the date interval and try again.

", "exception":true }, + "BillingViewArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"^arn:aws[a-z-]*:(billing)::[0-9]{12}:billingview/[-a-zA-Z0-9/:_+=.-@]{1,43}$" + }, "CommitmentPurchaseAnalysisConfiguration":{ "type":"structure", "members":{ @@ -2456,6 +2469,10 @@ "shape":"GroupDefinitions", "documentation":"

You can group Amazon Web Services costs using up to two different groups, either dimensions, tag keys, cost categories, or any two group by types.

Valid values for the DIMENSION type are AZ, INSTANCE_TYPE, LEGAL_ENTITY_NAME, INVOICING_ENTITY, LINKED_ACCOUNT, OPERATION, PLATFORM, PURCHASE_TYPE, SERVICE, TENANCY, RECORD_TYPE, and USAGE_TYPE.

When you group by the TAG type and include a valid tag key, you get all tag values, including empty strings.

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "NextPageToken":{ "shape":"NextPageToken", "documentation":"

The token to retrieve the next set of results. Amazon Web Services provides the token when the response from a previous call has more results than the maximum page size.

" @@ -2511,6 +2528,10 @@ "shape":"GroupDefinitions", "documentation":"

You can group Amazon Web Services costs using up to two different groups: DIMENSION, TAG, COST_CATEGORY.

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "NextPageToken":{ "shape":"NextPageToken", "documentation":"

The token to retrieve the next set of results. Amazon Web Services provides the token when the response from a previous call has more results than the maximum page size.

" @@ -2553,6 +2574,10 @@ "shape":"SortDefinitions", "documentation":"

The value that you sort the data by.

The key represents the cost and usage metrics. The following values are supported:

The supported key values for the SortOrder value are ASCENDING and DESCENDING.

When you use the SortBy value, the NextPageToken and SearchString key values aren't supported.

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "MaxResults":{ "shape":"MaxResults", "documentation":"

This field is only used when the SortBy value is provided in the request.

The maximum number of objects that are returned for this request. If MaxResults isn't specified with the SortBy value, the request returns 1000 results as the default value for this parameter.

For GetCostCategories, MaxResults has an upper quota of 1000.

" @@ -2616,6 +2641,10 @@ "shape":"Expression", "documentation":"

The filters that you want to use to filter your forecast. The GetCostForecast API supports filtering by the following dimensions:

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "PredictionIntervalLevel":{ "shape":"PredictionIntervalLevel", "documentation":"

Cost Explorer always returns the mean forecast as a single point. You can request a prediction interval around the mean by specifying a confidence level. The higher the confidence level, the more confident Cost Explorer is about the actual value falling in the prediction interval. Higher confidence levels result in wider prediction intervals.

" @@ -2663,6 +2692,10 @@ "shape":"SortDefinitions", "documentation":"

The value that you want to sort the data by.

The key represents cost and usage metrics. The following values are supported:

The supported values for the SortOrder key are ASCENDING or DESCENDING.

When you specify a SortBy paramater, the context must be COST_AND_USAGE. Further, when using SortBy, NextPageToken and SearchString aren't supported.

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "MaxResults":{ "shape":"MaxResults", "documentation":"

This field is only used when SortBy is provided in the request. The maximum number of objects that are returned for this request. If MaxResults isn't specified with SortBy, the request returns 1000 results as the default value for this parameter.

For GetDimensionValues, MaxResults has an upper limit of 1000.

" @@ -3164,6 +3197,10 @@ "shape":"SortDefinitions", "documentation":"

The value that you want to sort the data by.

The key represents cost and usage metrics. The following values are supported:

The supported values for SortOrder are ASCENDING and DESCENDING.

When you use SortBy, NextPageToken and SearchString aren't supported.

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "MaxResults":{ "shape":"MaxResults", "documentation":"

This field is only used when SortBy is provided in the request. The maximum number of objects that are returned for this request. If MaxResults isn't specified with SortBy, the request returns 1000 results as the default value for this parameter.

For GetTags, MaxResults has an upper quota of 1000.

" @@ -3224,6 +3261,10 @@ "shape":"Expression", "documentation":"

The filters that you want to use to filter your forecast. The GetUsageForecast API supports filtering by the following dimensions:

" }, + "BillingViewArn":{ + "shape":"BillingViewArn", + "documentation":"

The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.

" + }, "PredictionIntervalLevel":{ "shape":"PredictionIntervalLevel", "documentation":"

Amazon Web Services Cost Explorer always returns the mean forecast as a single point. You can request a prediction interval around the mean by specifying a confidence level. The higher the confidence level, the more confident Cost Explorer is about the actual value falling in the prediction interval. Higher confidence levels result in wider prediction intervals.

" diff --git a/botocore/data/connect/2017-08-08/service-2.json b/botocore/data/connect/2017-08-08/service-2.json index 81d1e2e048..1befa2930d 100644 --- a/botocore/data/connect/2017-08-08/service-2.json +++ b/botocore/data/connect/2017-08-08/service-2.json @@ -6067,6 +6067,10 @@ "shape":"NullableProficiencyLevel", "documentation":"

The proficiency level of the condition.

" }, + "Range":{ + "shape":"Range", + "documentation":"

An Object to define the minimum and maximum proficiency levels.

" + }, "MatchCriteria":{ "shape":"MatchCriteria", "documentation":"

An object to define AgentsCriteria.

" @@ -12755,7 +12759,8 @@ "OrExpression":{ "shape":"Expressions", "documentation":"

List of routing expressions which will be OR-ed together.

" - } + }, + "NotAttributeCondition":{"shape":"AttributeCondition"} }, "documentation":"

A tagged union to specify expression for a routing step.

" }, @@ -19164,6 +19169,20 @@ "max":50, "min":1 }, + "Range":{ + "type":"structure", + "members":{ + "MinProficiencyLevel":{ + "shape":"NullableProficiencyLevel", + "documentation":"

The minimum proficiency level of the range.

" + }, + "MaxProficiencyLevel":{ + "shape":"NullableProficiencyLevel", + "documentation":"

The maximum proficiency level of the range.

" + } + }, + "documentation":"

An Object to define the minimum and maximum proficiency levels.

" + }, "ReadOnlyFieldInfo":{ "type":"structure", "members":{ @@ -22203,7 +22222,7 @@ }, "UploadUrlMetadata":{ "shape":"UploadUrlMetadata", - "documentation":"

Information to be used while uploading the attached file.

" + "documentation":"

The headers to be provided while uploading the file to the URL.

" } }, "documentation":"Response from StartAttachedFileUpload API." diff --git a/botocore/data/docdb/2014-10-31/service-2.json b/botocore/data/docdb/2014-10-31/service-2.json index 462207e810..af2f3f7f4c 100644 --- a/botocore/data/docdb/2014-10-31/service-2.json +++ b/botocore/data/docdb/2014-10-31/service-2.json @@ -1244,6 +1244,24 @@ }, "documentation":"

The configuration setting for the log types to be enabled for export to Amazon CloudWatch Logs for a specific instance or cluster.

The EnableLogTypes and DisableLogTypes arrays determine which logs are exported (or not exported) to CloudWatch Logs. The values within these arrays depend on the engine that is being used.

" }, + "ClusterMasterUserSecret":{ + "type":"structure", + "members":{ + "SecretArn":{ + "shape":"String", + "documentation":"

The Amazon Resource Name (ARN) of the secret.

" + }, + "SecretStatus":{ + "shape":"String", + "documentation":"

The status of the secret.

The possible status values include the following:

" + }, + "KmsKeyId":{ + "shape":"String", + "documentation":"

The Amazon Web Services KMS key identifier that is used to encrypt the secret.

" + } + }, + "documentation":"

Contains the secret managed by Amazon DocumentDB in Amazon Web Services Secrets Manager for the master user password.

" + }, "CopyDBClusterParameterGroupMessage":{ "type":"structure", "required":[ @@ -1407,6 +1425,14 @@ "StorageType":{ "shape":"String", "documentation":"

The storage type to associate with the DB cluster.

For information on storage types for Amazon DocumentDB clusters, see Cluster storage configurations in the Amazon DocumentDB Developer Guide.

Valid values for storage type - standard | iopt1

Default value is standard

When you create a DocumentDB DB cluster with the storage type set to iopt1, the storage type is returned in the response. The storage type isn't returned when you set it to standard.

" + }, + "ManageMasterUserPassword":{ + "shape":"BooleanOptional", + "documentation":"

Specifies whether to manage the master user password with Amazon Web Services Secrets Manager.

Constraint: You can't manage the master user password with Amazon Web Services Secrets Manager if MasterUserPassword is specified.

" + }, + "MasterUserSecretKmsKeyId":{ + "shape":"String", + "documentation":"

The Amazon Web Services KMS key identifier to encrypt a secret that is automatically generated and managed in Amazon Web Services Secrets Manager. This setting is valid only if the master user password is managed by Amazon DocumentDB in Amazon Web Services Secrets Manager for the DB cluster.

The Amazon Web Services KMS key identifier is the key ARN, key ID, alias ARN, or alias name for the KMS key. To use a KMS key in a different Amazon Web Services account, specify the key ARN or alias ARN.

If you don't specify MasterUserSecretKmsKeyId, then the aws/secretsmanager KMS key is used to encrypt the secret. If the secret is in a different Amazon Web Services account, then you can't use the aws/secretsmanager KMS key to encrypt the secret, and you must use a customer managed KMS key.

There is a default KMS key for your Amazon Web Services account. Your Amazon Web Services account has a different default KMS key for each Amazon Web Services Region.

" } }, "documentation":"

Represents the input to CreateDBCluster.

" @@ -1800,6 +1826,10 @@ "StorageType":{ "shape":"String", "documentation":"

Storage type associated with your cluster

Storage type associated with your cluster

For information on storage types for Amazon DocumentDB clusters, see Cluster storage configurations in the Amazon DocumentDB Developer Guide.

Valid values for storage type - standard | iopt1

Default value is standard

" + }, + "MasterUserSecret":{ + "shape":"ClusterMasterUserSecret", + "documentation":"

The secret managed by Amazon DocumentDB in Amazon Web Services Secrets Manager for the master user password.

" } }, "documentation":"

Detailed information about a cluster.

", @@ -3889,6 +3919,18 @@ "StorageType":{ "shape":"String", "documentation":"

The storage type to associate with the DB cluster.

For information on storage types for Amazon DocumentDB clusters, see Cluster storage configurations in the Amazon DocumentDB Developer Guide.

Valid values for storage type - standard | iopt1

Default value is standard

" + }, + "ManageMasterUserPassword":{ + "shape":"BooleanOptional", + "documentation":"

Specifies whether to manage the master user password with Amazon Web Services Secrets Manager. If the cluster doesn't manage the master user password with Amazon Web Services Secrets Manager, you can turn on this management. In this case, you can't specify MasterUserPassword. If the cluster already manages the master user password with Amazon Web Services Secrets Manager, and you specify that the master user password is not managed with Amazon Web Services Secrets Manager, then you must specify MasterUserPassword. In this case, Amazon DocumentDB deletes the secret and uses the new password for the master user specified by MasterUserPassword.

" + }, + "MasterUserSecretKmsKeyId":{ + "shape":"String", + "documentation":"

The Amazon Web Services KMS key identifier to encrypt a secret that is automatically generated and managed in Amazon Web Services Secrets Manager.

This setting is valid only if both of the following conditions are met:

The Amazon Web Services KMS key identifier is the key ARN, key ID, alias ARN, or alias name for the KMS key. To use a KMS key in a different Amazon Web Services account, specify the key ARN or alias ARN.

There is a default KMS key for your Amazon Web Services account. Your Amazon Web Services account has a different default KMS key for each Amazon Web Services Region.

" + }, + "RotateMasterUserPassword":{ + "shape":"BooleanOptional", + "documentation":"

Specifies whether to rotate the secret managed by Amazon Web Services Secrets Manager for the master user password.

This setting is valid only if the master user password is managed by Amazon DocumentDB in Amazon Web Services Secrets Manager for the cluster. The secret value contains the updated password.

Constraint: You must apply the change immediately when rotating the master user password.

" } }, "documentation":"

Represents the input to ModifyDBCluster.

" diff --git a/botocore/data/eks/2017-11-01/service-2.json b/botocore/data/eks/2017-11-01/service-2.json index c389546bce..afc845c26b 100644 --- a/botocore/data/eks/2017-11-01/service-2.json +++ b/botocore/data/eks/2017-11-01/service-2.json @@ -1145,6 +1145,24 @@ }, "documentation":"

An Amazon EKS add-on. For more information, see Amazon EKS add-ons in the Amazon EKS User Guide.

" }, + "AddonCompatibilityDetail":{ + "type":"structure", + "members":{ + "name":{ + "shape":"String", + "documentation":"

The name of the Amazon EKS add-on.

" + }, + "compatibleVersions":{ + "shape":"StringList", + "documentation":"

The list of compatible Amazon EKS add-on versions for the next Kubernetes version.

" + } + }, + "documentation":"

The summary information about the Amazon EKS add-on compatibility for the next Kubernetes version for an insight check in the UPGRADE_READINESS category.

" + }, + "AddonCompatibilityDetails":{ + "type":"list", + "member":{"shape":"AddonCompatibilityDetail"} + }, "AddonHealth":{ "type":"structure", "members":{ @@ -3459,6 +3477,10 @@ "deprecationDetails":{ "shape":"DeprecationDetails", "documentation":"

The summary information about deprecated resource usage for an insight check in the UPGRADE_READINESS category.

" + }, + "addonCompatibilityDetails":{ + "shape":"AddonCompatibilityDetails", + "documentation":"

A list of AddonCompatibilityDetail objects for Amazon EKS add-ons.

" } }, "documentation":"

Summary information that relates to the category of the insight. Currently only returned with certain insights having category UPGRADE_READINESS.

" diff --git a/botocore/data/macie2/2020-01-01/service-2.json b/botocore/data/macie2/2020-01-01/service-2.json index 6678e53a65..5428c0e0aa 100644 --- a/botocore/data/macie2/2020-01-01/service-2.json +++ b/botocore/data/macie2/2020-01-01/service-2.json @@ -2331,7 +2331,7 @@ "documentation": "

The request failed because it conflicts with the current state of the specified resource.

" } ], - "documentation": "

Retrieves a subset of information about all the custom data identifiers for an account.

" + "documentation": "

Retrieves a subset of information about the custom data identifiers for an account.

" }, "ListFindings": { "name": "ListFindings", @@ -2855,7 +2855,7 @@ "documentation": "

The request failed because it conflicts with the current state of the specified resource.

" } ], - "documentation": "

Retrieves (queries) statistical data and other information about Amazon Web Services resources that Amazon Macie monitors and analyzes.

" + "documentation": "

Retrieves (queries) statistical data and other information about Amazon Web Services resources that Amazon Macie monitors and analyzes for an account.

" }, "TagResource": { "name": "TagResource", @@ -3657,7 +3657,7 @@ "apiServiceName": { "shape": "__string", "locationName": "apiServiceName", - "documentation": "

The URL of the Amazon Web Service that provides the operation, for example: s3.amazonaws.com.

" + "documentation": "

The URL of the Amazon Web Services service that provides the operation, for example: s3.amazonaws.com.

" }, "firstSeen": { "shape": "__timestampIso8601", @@ -3955,7 +3955,7 @@ "unknown": { "shape": "__long", "locationName": "unknown", - "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate permissions settings for. Macie can't determine whether these buckets are publicly accessible.

" + "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate permissions settings for. For example, the buckets' policies or a quota prevented Macie from retrieving the requisite data. Macie can't determine whether the buckets are publicly accessible.

" } }, "documentation": "

Provides information about the number of S3 buckets that are publicly accessible due to a combination of permissions settings for each bucket.

" @@ -3981,7 +3981,7 @@ "unknown": { "shape": "__long", "locationName": "unknown", - "documentation": "

The total number of buckets that Amazon Macie doesn't have current encryption metadata for. Macie can't provide current data about the default encryption settings for these buckets.

" + "documentation": "

The total number of buckets that Amazon Macie doesn't have current encryption metadata for. For example, the buckets' permissions settings or a quota prevented Macie from retrieving the default encryption settings for the buckets.

" } }, "documentation": "

Provides information about the number of S3 buckets whose settings do or don't specify default server-side encryption behavior for objects that are added to the buckets. For detailed information about these settings, see Setting default server-side encryption behavior for Amazon S3 buckets in the Amazon Simple Storage Service User Guide.

" @@ -4007,7 +4007,7 @@ "unknown": { "shape": "__long", "locationName": "unknown", - "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate shared access settings for. Macie can't determine whether these buckets are shared with other Amazon Web Services accounts, Amazon CloudFront OAIs, or CloudFront OACs.

" + "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate shared access settings for. For example, the buckets' permissions settings or a quota prevented Macie from retrieving the requisite data. Macie can't determine whether the buckets are shared with other Amazon Web Services accounts, Amazon CloudFront OAIs, or CloudFront OACs.

" } }, "documentation": "

Provides information about the number of S3 buckets that are or aren't shared with other Amazon Web Services accounts, Amazon CloudFront origin access identities (OAIs), or CloudFront origin access controls (OACs). In this data, an Amazon Macie organization is defined as a set of Macie accounts that are centrally managed as a group of related accounts through Organizations or by Macie invitation.

" @@ -4028,7 +4028,7 @@ "unknown": { "shape": "__long", "locationName": "unknown", - "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate server-side encryption requirements for. Macie can't determine whether the bucket policies for these buckets require server-side encryption of new objects.

" + "documentation": "

The total number of buckets that Amazon Macie wasn't able to evaluate server-side encryption requirements for. For example, the buckets' permissions settings or a quota prevented Macie from retrieving the requisite data. Macie can't determine whether bucket policies for the buckets require server-side encryption of new objects.

" } }, "documentation": "

Provides information about the number of S3 buckets whose bucket policies do or don't require server-side encryption of objects when objects are added to the buckets.

" @@ -4151,12 +4151,12 @@ "errorCode": { "shape": "BucketMetadataErrorCode", "locationName": "errorCode", - "documentation": "

The error code for an error that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. If this value is ACCESS_DENIED, Macie doesn't have permission to retrieve the information. For example, the bucket has a restrictive bucket policy and Amazon S3 denied the request. If this value is null, Macie was able to retrieve and process the information.

" + "documentation": "

The code for an error or issue that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. Possible values are:

If this value is null, Macie was able to retrieve and process the information.

" }, "errorMessage": { "shape": "__string", "locationName": "errorMessage", - "documentation": "

A brief description of the error (errorCode) that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. This value is null if Macie was able to retrieve and process the information.

" + "documentation": "

A brief description of the error or issue (errorCode) that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. This value is null if Macie was able to retrieve and process the information.

" }, "jobDetails": { "shape": "JobDetails", @@ -4166,7 +4166,7 @@ "lastAutomatedDiscoveryTime": { "shape": "__timestampIso8601", "locationName": "lastAutomatedDiscoveryTime", - "documentation": "

The date and time, in UTC and extended ISO 8601 format, when Amazon Macie most recently analyzed objects in the bucket while performing automated sensitive data discovery. This value is null if automated sensitive data discovery is disabled for your account.

" + "documentation": "

The date and time, in UTC and extended ISO 8601 format, when Amazon Macie most recently analyzed objects in the bucket while performing automated sensitive data discovery. This value is null if this analysis hasn't occurred.

" }, "lastUpdated": { "shape": "__timestampIso8601", @@ -4201,7 +4201,7 @@ "sensitivityScore": { "shape": "__integer", "locationName": "sensitivityScore", - "documentation": "

The sensitivity score for the bucket, ranging from -1 (classification error) to 100 (sensitive).

If automated sensitive data discovery has never been enabled for your account or it’s been disabled for your organization or your standalone account for more than 30 days, possible values are: 1, the bucket is empty; or, 50, the bucket stores objects but it’s been excluded from recent analyses.

" + "documentation": "

The sensitivity score for the bucket, ranging from -1 (classification error) to 100 (sensitive).

If automated sensitive data discovery has never been enabled for your account or it's been disabled for your organization or standalone account for more than 30 days, possible values are: 1, the bucket is empty; or, 50, the bucket stores objects but it's been excluded from recent analyses.

" }, "serverSideEncryption": { "shape": "BucketServerSideEncryption", @@ -4244,13 +4244,14 @@ "documentation": "

Specifies whether versioning is enabled for the bucket.

" } }, - "documentation": "

Provides statistical data and other information about an S3 bucket that Amazon Macie monitors and analyzes for your account. By default, object count and storage size values include data for object parts that are the result of incomplete multipart uploads. For more information, see How Macie monitors Amazon S3 data security in the Amazon Macie User Guide.

If an error occurs when Macie attempts to retrieve and process metadata from Amazon S3 for the bucket or the bucket's objects, the value for the versioning property is false and the value for most other properties is null. Key exceptions are accountId, bucketArn, bucketCreatedAt, bucketName, lastUpdated, and region. To identify the cause of the error, refer to the errorCode and errorMessage values.

" + "documentation": "

Provides statistical data and other information about an S3 bucket that Amazon Macie monitors and analyzes for your account. By default, object count and storage size values include data for object parts that are the result of incomplete multipart uploads. For more information, see How Macie monitors Amazon S3 data security in the Amazon Macie User Guide.

If an error or issue prevents Macie from retrieving and processing metadata from Amazon S3 for the bucket or the bucket's objects, the value for the versioning property is false and the value for most other properties is null or UNKNOWN. Key exceptions are accountId, bucketArn, bucketCreatedAt, bucketName, lastUpdated, and region. To identify the cause, refer to the errorCode and errorMessage values.

" }, "BucketMetadataErrorCode": { "type": "string", - "documentation": "

The error code for an error that prevented Amazon Macie from retrieving and processing information about an S3 bucket and the bucket's objects.

", + "documentation": "

The code for an error or issue that prevented Amazon Macie from retrieving and processing information about an S3 bucket and the bucket's objects.

", "enum": [ - "ACCESS_DENIED" + "ACCESS_DENIED", + "BUCKET_COUNT_EXCEEDS_QUOTA" ] }, "BucketPermissionConfiguration": { @@ -4357,7 +4358,7 @@ "documentation": "

The aggregated statistical data for all buckets that have a sensitivity score of 51-100.

" } }, - "documentation": "

Provides aggregated statistical data for sensitive data discovery metrics that apply to S3 buckets, grouped by bucket sensitivity score (sensitivityScore). If automated sensitive data discovery is currently disabled for your account, the value for each metric is 0.

" + "documentation": "

Provides aggregated statistical data for sensitive data discovery metrics that apply to S3 buckets, grouped by bucket sensitivity score (sensitivityScore). If automated sensitive data discovery is currently disabled for your account, the value for most of these metrics is 0.

" }, "Cell": { "type": "structure", @@ -5462,7 +5463,7 @@ "suppressed": { "shape": "__boolean", "locationName": "suppressed", - "documentation": "

Specifies whether occurrences of this type of sensitive data are excluded (true) or included (false) in the bucket's sensitivity score.

" + "documentation": "

Specifies whether occurrences of this type of sensitive data are excluded (true) or included (false) in the bucket's sensitivity score, if the score is calculated by Amazon Macie.

" }, "type": { "shape": "DataIdentifierType", @@ -5859,7 +5860,7 @@ }, "FindingType": { "type": "string", - "documentation": "

The type of finding. For details about each type, see Types of Amazon Macie findings in the Amazon Macie User Guide. Possible values are:

", + "documentation": "

The type of finding. For details about each type, see Types of findings in the Amazon Macie User Guide. Possible values are:

", "enum": [ "SensitiveData:S3Object/Multiple", "SensitiveData:S3Object/Financial", @@ -6078,7 +6079,7 @@ "bucketStatisticsBySensitivity": { "shape": "BucketStatisticsBySensitivity", "locationName": "bucketStatisticsBySensitivity", - "documentation": "

The aggregated sensitive data discovery statistics for the buckets. If automated sensitive data discovery is currently disabled for your account, the value for each statistic is 0.

" + "documentation": "

The aggregated sensitive data discovery statistics for the buckets. If automated sensitive data discovery is currently disabled for your account, the value for most statistics is 0.

" }, "classifiableObjectCount": { "shape": "__long", @@ -6603,7 +6604,7 @@ "reasons": { "shape": "__listOfUnavailabilityReasonCode", "locationName": "reasons", - "documentation": "

Specifies why occurrences of sensitive data can't be retrieved for the finding. Possible values are:

This value is null if sensitive data can be retrieved for the finding.

" + "documentation": "

Specifies why occurrences of sensitive data can't be retrieved for the finding. Possible values are:

This value is null if sensitive data can be retrieved for the finding.

" } } }, @@ -7812,12 +7813,12 @@ "errorCode": { "shape": "BucketMetadataErrorCode", "locationName": "errorCode", - "documentation": "

The error code for an error that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. If this value is ACCESS_DENIED, Macie doesn't have permission to retrieve the information. For example, the bucket has a restrictive bucket policy and Amazon S3 denied the request. If this value is null, Macie was able to retrieve and process the information.

" + "documentation": "

The code for an error or issue that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. Possible values are:

If this value is null, Macie was able to retrieve and process the information.

" }, "errorMessage": { "shape": "__string", "locationName": "errorMessage", - "documentation": "

A brief description of the error (errorCode) that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. This value is null if Macie was able to retrieve and process the information.

" + "documentation": "

A brief description of the error or issue (errorCode) that prevented Amazon Macie from retrieving and processing information about the bucket and the bucket's objects. This value is null if Macie was able to retrieve and process the information.

" }, "jobDetails": { "shape": "JobDetails", @@ -7827,7 +7828,7 @@ "lastAutomatedDiscoveryTime": { "shape": "__timestampIso8601", "locationName": "lastAutomatedDiscoveryTime", - "documentation": "

The date and time, in UTC and extended ISO 8601 format, when Amazon Macie most recently analyzed objects in the bucket while performing automated sensitive data discovery. This value is null if automated sensitive data discovery is disabled for your account.

" + "documentation": "

The date and time, in UTC and extended ISO 8601 format, when Amazon Macie most recently analyzed objects in the bucket while performing automated sensitive data discovery. This value is null if this analysis hasn't occurred.

" }, "objectCount": { "shape": "__long", @@ -7842,7 +7843,7 @@ "sensitivityScore": { "shape": "__integer", "locationName": "sensitivityScore", - "documentation": "

The sensitivity score for the bucket, ranging from -1 (classification error) to 100 (sensitive).

If automated sensitive data discovery has never been enabled for your account or it’s been disabled for your organization or your standalone account for more than 30 days, possible values are: 1, the bucket is empty; or, 50, the bucket stores objects but it’s been excluded from recent analyses.

" + "documentation": "

The sensitivity score for the bucket, ranging from -1 (classification error) to 100 (sensitive).

If automated sensitive data discovery has never been enabled for your account or it's been disabled for your organization or standalone account for more than 30 days, possible values are: 1, the bucket is empty; or, 50, the bucket stores objects but it's been excluded from recent analyses.

" }, "sizeInBytes": { "shape": "__long", @@ -7865,7 +7866,7 @@ "documentation": "

The total storage size, in bytes, of the objects that Amazon Macie can't analyze in the bucket. These objects don't use a supported storage class or don't have a file name extension for a supported file or storage format.

" } }, - "documentation": "

Provides statistical data and other information about an S3 bucket that Amazon Macie monitors and analyzes for your account. By default, object count and storage size values include data for object parts that are the result of incomplete multipart uploads. For more information, see How Macie monitors Amazon S3 data security in the Amazon Macie User Guide.

If an error occurs when Macie attempts to retrieve and process information about the bucket or the bucket's objects, the value for most of these properties is null. Key exceptions are accountId and bucketName. To identify the cause of the error, refer to the errorCode and errorMessage values.

" + "documentation": "

Provides statistical data and other information about an S3 bucket that Amazon Macie monitors and analyzes for your account. By default, object count and storage size values include data for object parts that are the result of incomplete multipart uploads. For more information, see How Macie monitors Amazon S3 data security in the Amazon Macie User Guide.

If an error or issue prevents Macie from retrieving and processing information about the bucket or the bucket's objects, the value for many of these properties is null. Key exceptions are accountId and bucketName. To identify the cause, refer to the errorCode and errorMessage values.

" }, "MatchingResource": { "type": "structure", @@ -7873,7 +7874,7 @@ "matchingBucket": { "shape": "MatchingBucket", "locationName": "matchingBucket", - "documentation": "

The details of an S3 bucket that Amazon Macie monitors and analyzes.

" + "documentation": "

The details of an S3 bucket that Amazon Macie monitors and analyzes for your account.

" } }, "documentation": "

Provides statistical data and other information about an Amazon Web Services resource that Amazon Macie monitors and analyzes for your account.

" @@ -8443,7 +8444,7 @@ "documentation": "

The tags that are associated with the bucket.

" } }, - "documentation": "

Provides information about the S3 bucket that a finding applies to.

" + "documentation": "

Provides information about the S3 bucket that a finding applies to. If a quota prevented Amazon Macie from retrieving and processing all the bucket's information prior to generating the finding, the following values are UNKNOWN or null: allowsUnencryptedObjectUploads, defaultServerSideEncryption, publicAccess, and tags.

" }, "S3BucketCriteriaForJob": { "type": "structure", @@ -8536,7 +8537,7 @@ "bucketNames": { "shape": "__listOfS3BucketName", "locationName": "bucketNames", - "documentation": "

Depending on the value specified for the update operation (ClassificationScopeUpdateOperation), an array of strings that: lists the names of buckets to add or remove from the list, or specifies a new set of bucket names that overwrites all existing names in the list. Each string must be the full name of an S3 bucket. Values are case sensitive.

" + "documentation": "

Depending on the value specified for the update operation (ClassificationScopeUpdateOperation), an array of strings that: lists the names of buckets to add or remove from the list, or specifies a new set of bucket names that overwrites all existing names in the list. Each string must be the full name of an existing S3 bucket. Values are case sensitive.

" }, "operation": { "shape": "ClassificationScopeUpdateOperation", @@ -8917,7 +8918,7 @@ "documentation": "

Specifies whether to publish policy findings to Security Hub. If you set this value to true, Amazon Macie automatically publishes all new and updated policy findings that weren't suppressed by a findings filter. The default value is true.

" } }, - "documentation": "

Specifies configuration settings that determine which findings are published to Security Hub automatically. For information about how Macie publishes findings to Security Hub, see Amazon Macie integration with Security Hub in the Amazon Macie User Guide.

", + "documentation": "

Specifies configuration settings that determine which findings are published to Security Hub automatically. For information about how Macie publishes findings to Security Hub, see Evaluating findings with Security Hub in the Amazon Macie User Guide.

", "required": [ "publishPolicyFindings", "publishClassificationFindings" @@ -8995,7 +8996,7 @@ "documentation": "

The total storage size, in bytes, of the buckets.

If versioning is enabled for any of the buckets, this value is based on the size of the latest version of each object in the buckets. This value doesn't reflect the storage size of all versions of the objects in the buckets.

" } }, - "documentation": "

Provides aggregated statistical data for sensitive data discovery metrics that apply to S3 buckets. Each field contains aggregated data for all the buckets that have a sensitivity score (sensitivityScore) of a specified value or within a specified range (BucketStatisticsBySensitivity). If automated sensitive data discovery is currently disabled for your account, the value for each field is 0.

" + "documentation": "

Provides aggregated statistical data for sensitive data discovery metrics that apply to S3 buckets. Each field contains aggregated data for all the buckets that have a sensitivity score (sensitivityScore) of a specified value or within a specified range (BucketStatisticsBySensitivity). If automated sensitive data discovery is currently disabled for your account, the value for most fields is 0.

" }, "SensitivityInspectionTemplateExcludes": { "type": "structure", @@ -9330,7 +9331,7 @@ "id": { "shape": "__string", "locationName": "id", - "documentation": "

The unique identifier for the custom data identifier or managed data identifier that detected the type of sensitive data to exclude or include in the score.

" + "documentation": "

The unique identifier for the custom data identifier or managed data identifier that detected the type of sensitive data to exclude from the score.

" }, "type": { "shape": "DataIdentifierType", @@ -9338,7 +9339,7 @@ "documentation": "

The type of data identifier that detected the sensitive data. Possible values are: CUSTOM, for a custom data identifier; and, MANAGED, for a managed data identifier.

" } }, - "documentation": "

Specifies a custom data identifier or managed data identifier that detected a type of sensitive data to start excluding or including in an S3 bucket's sensitivity score.

" + "documentation": "

Specifies a custom data identifier or managed data identifier that detected a type of sensitive data to exclude from an S3 bucket's sensitivity score.

" }, "TagCriterionForJob": { "type": "structure", @@ -9566,7 +9567,7 @@ "message": { "shape": "__string", "locationName": "message", - "documentation": "

The type of error that occurred and prevented Amazon Macie from retrieving occurrences of sensitive data reported by the finding. Possible values are:

" + "documentation": "

The type of error that occurred and prevented Amazon Macie from retrieving occurrences of sensitive data reported by the finding. Possible values are:

" } }, "documentation": "

Provides information about an error that occurred due to an unprocessable entity.

", @@ -9878,7 +9879,7 @@ "suppressDataIdentifiers": { "shape": "__listOfSuppressDataIdentifier", "locationName": "suppressDataIdentifiers", - "documentation": "

An array of objects, one for each custom data identifier or managed data identifier that detected the type of sensitive data to start excluding or including in the bucket's score. To start including all sensitive data types in the score, don't specify any values for this array.

" + "documentation": "

An array of objects, one for each custom data identifier or managed data identifier that detected a type of sensitive data to exclude from the bucket's score. To include all sensitive data types in the score, don't specify any values for this array.

" } }, "required": [ @@ -9928,7 +9929,7 @@ "documentation": "

The name of the IAM role that is in the affected Amazon Web Services account and Amazon Macie is allowed to assume when retrieving sensitive data from affected S3 objects for the account. The trust and permissions policies for the role must meet all requirements for Macie to assume the role.

" } }, - "documentation": "

Specifies the access method and settings to use when retrieving occurrences of sensitive data reported by findings. If your request specifies an Identity and Access Management (IAM) role to assume, Amazon Macie verifies that the role exists and the attached policies are configured correctly. If there's an issue, Macie returns an error. For information about addressing the issue, see Configuration options and requirements for retrieving sensitive data samples in the Amazon Macie User Guide.

", + "documentation": "

Specifies the access method and settings to use when retrieving occurrences of sensitive data reported by findings. If your request specifies an Identity and Access Management (IAM) role to assume, Amazon Macie verifies that the role exists and the attached policies are configured correctly. If there's an issue, Macie returns an error. For information about addressing the issue, see Configuration options for retrieving sensitive data samples in the Amazon Macie User Guide.

", "required": [ "retrievalMode" ] @@ -10169,7 +10170,7 @@ "awsService": { "shape": "AwsService", "locationName": "awsService", - "documentation": "

If the action was performed by an Amazon Web Services account that belongs to an Amazon Web Service, the name of the service.

" + "documentation": "

If the action was performed by an Amazon Web Services account that belongs to an Amazon Web Services service, the name of the service.

" }, "federatedUser": { "shape": "FederatedUser", diff --git a/botocore/data/outposts/2019-12-03/service-2.json b/botocore/data/outposts/2019-12-03/service-2.json index 644e31e038..d26293ce50 100644 --- a/botocore/data/outposts/2019-12-03/service-2.json +++ b/botocore/data/outposts/2019-12-03/service-2.json @@ -433,7 +433,7 @@ {"shape":"InternalServerException"}, {"shape":"ConflictException"} ], - "documentation":"

Starts the specified capacity task. You can have one active capacity task per order or Outpost.

" + "documentation":"

Starts the specified capacity task. You can have one active capacity task for each order and each Outpost.

" }, "StartConnection":{ "name":"StartConnection", @@ -2490,7 +2490,8 @@ "L6_30P", "IEC309", "AH530P7W", - "AH532P6W" + "AH532P6W", + "CS8365C" ] }, "PowerDrawKva":{ @@ -3073,7 +3074,7 @@ }, "PowerConnector":{ "shape":"PowerConnector", - "documentation":"

The power connector that Amazon Web Services should plan to provide for connections to the hardware. Note the correlation between PowerPhase and PowerConnector.

" + "documentation":"

The power connector that Amazon Web Services should plan to provide for connections to the hardware. Note the correlation between PowerPhase and PowerConnector.

" }, "PowerFeedDrop":{ "shape":"PowerFeedDrop", diff --git a/botocore/data/sagemaker/2017-07-24/service-2.json b/botocore/data/sagemaker/2017-07-24/service-2.json index 516e09250c..bd50b452d7 100644 --- a/botocore/data/sagemaker/2017-07-24/service-2.json +++ b/botocore/data/sagemaker/2017-07-24/service-2.json @@ -112,7 +112,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceInUse"} ], - "documentation":"

Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

" + "documentation":"

Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker AI upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

" }, "CreateAppImageConfig":{ "name":"CreateAppImageConfig", @@ -125,7 +125,7 @@ "errors":[ {"shape":"ResourceInUse"} ], - "documentation":"

Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.

" + "documentation":"

Creates a configuration for running a SageMaker AI image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.

" }, "CreateArtifact":{ "name":"CreateArtifact", @@ -152,7 +152,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.

An AutoML job in SageMaker is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.

For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker developer guide.

We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.

" + "documentation":"

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.

An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.

For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.

We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.

" }, "CreateAutoMLJobV2":{ "name":"CreateAutoMLJobV2", @@ -166,7 +166,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.

An AutoML job in SageMaker is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.

For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker developer guide.

AutoML jobs V2 support various problem types such as regression, binary, and multiclass classification with tabular data, text and image classification, time-series forecasting, and fine-tuning of large language models (LLMs) for text generation.

CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.

You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.

" + "documentation":"

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.

An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.

For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.

AutoML jobs V2 support various problem types such as regression, binary, and multiclass classification with tabular data, text and image classification, time-series forecasting, and fine-tuning of large language models (LLMs) for text generation.

CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.

You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.

" }, "CreateCluster":{ "name":"CreateCluster", @@ -204,7 +204,7 @@ }, "input":{"shape":"CreateCodeRepositoryInput"}, "output":{"shape":"CreateCodeRepositoryOutput"}, - "documentation":"

Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.

The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.

" + "documentation":"

Creates a Git repository as a resource in your SageMaker AI account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker AI account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.

The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.

" }, "CreateCompilationJob":{ "name":"CreateCompilationJob", @@ -218,7 +218,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.

If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.

In the request body, you provide the following:

You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.

To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.

" + "documentation":"

Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.

If you choose to host your model using Amazon SageMaker AI hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.

In the request body, you provide the following:

You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.

To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.

" }, "CreateComputeQuota":{ "name":"CreateComputeQuota", @@ -259,7 +259,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceInUse"} ], - "documentation":"

Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.

" + "documentation":"

Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.

" }, "CreateDeviceFleet":{ "name":"CreateDeviceFleet", @@ -286,7 +286,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceInUse"} ], - "documentation":"

Creates a Domain. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.

EFS storage

When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.

SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.

VPC configuration

All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to the domain. The following options are available:

NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.

For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.

" + "documentation":"

Creates a Domain. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.

EFS storage

When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.

SageMaker AI uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.

VPC configuration

All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to the domain. The following options are available:

NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker AI Studio app successfully.

For more information, see Connect Amazon SageMaker AI Studio Notebooks to Resources in a VPC.

" }, "CreateEdgeDeploymentPlan":{ "name":"CreateEdgeDeploymentPlan", @@ -461,7 +461,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker image.

" + "documentation":"

Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker AI image.

" }, "CreateImageVersion":{ "name":"CreateImageVersion", @@ -476,7 +476,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon ECR container image specified by BaseImage.

" + "documentation":"

Creates a version of the SageMaker AI image specified by ImageName. The version represents the Amazon ECR container image specified by BaseImage.

" }, "CreateInferenceComponent":{ "name":"CreateInferenceComponent", @@ -489,7 +489,7 @@ "errors":[ {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Creates an inference component, which is a SageMaker hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.

" + "documentation":"

Creates an inference component, which is a SageMaker AI hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.

" }, "CreateInferenceExperiment":{ "name":"CreateInferenceExperiment", @@ -655,7 +655,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceInUse"} ], - "documentation":"

Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.

" + "documentation":"

Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.

" }, "CreateMonitoringSchedule":{ "name":"CreateMonitoringSchedule", @@ -669,7 +669,7 @@ {"shape":"ResourceLimitExceeded"}, {"shape":"ResourceInUse"} ], - "documentation":"

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.

" + "documentation":"

Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint.

" }, "CreateNotebookInstance":{ "name":"CreateNotebookInstance", @@ -682,7 +682,7 @@ "errors":[ {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.

In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.

SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.

After receiving the request, SageMaker does the following:

  1. Creates a network interface in the SageMaker VPC.

  2. (Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.

  3. Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.

After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.

After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.

For more information, see How It Works.

" + "documentation":"

Creates an SageMaker AI notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.

In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker AI launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.

SageMaker AI also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker AI with a specific algorithm or with a machine learning framework.

After receiving the request, SageMaker AI does the following:

  1. Creates a network interface in the SageMaker AI VPC.

  2. (Option) If you specified SubnetId, SageMaker AI creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker AI attaches the security group that you specified in the request to the network interface that it creates in your VPC.

  3. Launches an EC2 instance of the type specified in the request in the SageMaker AI VPC. If you specified SubnetId of your VPC, SageMaker AI specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.

After creating the notebook instance, SageMaker AI returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.

After SageMaker AI creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker AI endpoints, and validate hosted models.

For more information, see How It Works.

" }, "CreateNotebookInstanceLifecycleConfig":{ "name":"CreateNotebookInstanceLifecycleConfig", @@ -764,7 +764,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System volume. This operation can only be called when the authentication mode equals IAM.

The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.

You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker Studio Through an Interface VPC Endpoint .

" + "documentation":"

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System volume. This operation can only be called when the authentication mode equals IAM.

The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.

You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker AI Studio Through an Interface VPC Endpoint .

" }, "CreatePresignedMlflowTrackingServerUrl":{ "name":"CreatePresignedMlflowTrackingServerUrl", @@ -787,7 +787,7 @@ }, "input":{"shape":"CreatePresignedNotebookInstanceUrlInput"}, "output":{"shape":"CreatePresignedNotebookInstanceUrlOutput"}, - "documentation":"

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.

The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.

You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.

The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.

" + "documentation":"

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker AI console, when you choose Open next to a notebook instance, SageMaker AI opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.

The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.

You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.

The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.

" }, "CreateProcessingJob":{ "name":"CreateProcessingJob", @@ -842,7 +842,7 @@ "errors":[ {"shape":"ResourceInUse"} ], - "documentation":"

Creates a new Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

Creates a new Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "CreateTrainingJob":{ "name":"CreateTrainingJob", @@ -1075,7 +1075,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker. It doesn't delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.

You can delete a compilation job only if its current status is COMPLETED, FAILED, or STOPPED. If the job status is STARTING or INPROGRESS, stop the job, and then delete it after its status becomes STOPPED.

" + "documentation":"

Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker AI. It doesn't delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.

You can delete a compilation job only if its current status is COMPLETED, FAILED, or STOPPED. If the job status is STARTING or INPROGRESS, stop the job, and then delete it after its status becomes STOPPED.

" }, "DeleteComputeQuota":{ "name":"DeleteComputeQuota", @@ -1292,7 +1292,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Deletes a SageMaker image and all versions of the image. The container images aren't deleted.

" + "documentation":"

Deletes a SageMaker AI image and all versions of the image. The container images aren't deleted.

" }, "DeleteImageVersion":{ "name":"DeleteImageVersion", @@ -1306,7 +1306,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Deletes a version of a SageMaker image. The container image the version represents isn't deleted.

" + "documentation":"

Deletes a version of a SageMaker AI image. The container image the version represents isn't deleted.

" }, "DeleteInferenceComponent":{ "name":"DeleteInferenceComponent", @@ -1363,7 +1363,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Deletes an Amazon SageMaker model bias job definition.

" + "documentation":"

Deletes an Amazon SageMaker AI model bias job definition.

" }, "DeleteModelCard":{ "name":"DeleteModelCard", @@ -1388,7 +1388,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Deletes an Amazon SageMaker model explainability job definition.

" + "documentation":"

Deletes an Amazon SageMaker AI model explainability job definition.

" }, "DeleteModelPackage":{ "name":"DeleteModelPackage", @@ -1454,7 +1454,7 @@ "requestUri":"/" }, "input":{"shape":"DeleteNotebookInstanceInput"}, - "documentation":"

Deletes an SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.

When you delete a notebook instance, you lose all of your data. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.

" + "documentation":"

Deletes an SageMaker AI notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.

When you delete a notebook instance, you lose all of your data. SageMaker AI removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.

" }, "DeleteNotebookInstanceLifecycleConfig":{ "name":"DeleteNotebookInstanceLifecycleConfig", @@ -1541,7 +1541,7 @@ {"shape":"ResourceNotFound"}, {"shape":"ResourceInUse"} ], - "documentation":"

Deletes the Amazon SageMaker Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.

" + "documentation":"

Deletes the Amazon SageMaker AI Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.

" }, "DeleteTags":{ "name":"DeleteTags", @@ -2013,7 +2013,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Describes a SageMaker image.

" + "documentation":"

Describes a SageMaker AI image.

" }, "DescribeImageVersion":{ "name":"DescribeImageVersion", @@ -2026,7 +2026,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Describes a version of a SageMaker image.

" + "documentation":"

Describes a version of a SageMaker AI image.

" }, "DescribeInferenceComponent":{ "name":"DescribeInferenceComponent", @@ -2343,7 +2343,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Describes the Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

Describes the Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "DescribeSubscribedWorkteam":{ "name":"DescribeSubscribedWorkteam", @@ -3191,7 +3191,7 @@ }, "input":{"shape":"ListNotebookInstancesInput"}, "output":{"shape":"ListNotebookInstancesOutput"}, - "documentation":"

Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services Region.

" + "documentation":"

Returns a list of the SageMaker AI notebook instances in the requester's account in an Amazon Web Services Region.

" }, "ListOptimizationJobs":{ "name":"ListOptimizationJobs", @@ -3323,7 +3323,7 @@ "errors":[ {"shape":"ResourceInUse"} ], - "documentation":"

Lists the Amazon SageMaker Studio Lifecycle Configurations in your Amazon Web Services Account.

" + "documentation":"

Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services Account.

" }, "ListSubscribedWorkteams":{ "name":"ListSubscribedWorkteams", @@ -3622,7 +3622,7 @@ "errors":[ {"shape":"ResourceLimitExceeded"} ], - "documentation":"

Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.

" + "documentation":"

Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker AI sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.

" }, "StartPipelineExecution":{ "name":"StartPipelineExecution", @@ -3661,7 +3661,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"

Stops a model compilation job.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.

When it receives a StopCompilationJob request, Amazon SageMaker changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.

" + "documentation":"

Stops a model compilation job.

To stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.

When it receives a StopCompilationJob request, Amazon SageMaker AI changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.

" }, "StopEdgeDeploymentStage":{ "name":"StopEdgeDeploymentStage", @@ -3764,7 +3764,7 @@ "requestUri":"/" }, "input":{"shape":"StopNotebookInstanceInput"}, - "documentation":"

Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance.

To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.

" + "documentation":"

Terminates the ML compute instance. Before terminating the instance, SageMaker AI disconnects the ML storage volume from it. SageMaker AI preserves the ML storage volume. SageMaker AI stops charging you for the ML compute instance when you call StopNotebookInstance.

To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.

" }, "StopOptimizationJob":{ "name":"StopOptimizationJob", @@ -4082,7 +4082,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Updates the properties of a SageMaker image. To change the image's tags, use the AddTags and DeleteTags APIs.

" + "documentation":"

Updates the properties of a SageMaker AI image. To change the image's tags, use the AddTags and DeleteTags APIs.

" }, "UpdateImageVersion":{ "name":"UpdateImageVersion", @@ -4096,7 +4096,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Updates the properties of a SageMaker image version.

" + "documentation":"

Updates the properties of a SageMaker AI image version.

" }, "UpdateInferenceComponent":{ "name":"UpdateInferenceComponent", @@ -4303,7 +4303,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceNotFound"} ], - "documentation":"

Updates the settings of a space.

" + "documentation":"

Updates the settings of a space.

You can't edit the app type of a space in the SpaceSettings.

" }, "UpdateTrainingJob":{ "name":"UpdateTrainingJob", @@ -4760,7 +4760,7 @@ "documentation":"

The configuration to use an image from a private Docker registry for a training job.

" } }, - "documentation":"

Specifies the training algorithm to use in a CreateTrainingJob request.

For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.

" + "documentation":"

Specifies the training algorithm to use in a CreateTrainingJob request.

SageMaker uses its own SageMaker account credentials to pull and access built-in algorithms so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard, unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use custom algorithms if you require specific access controls.

For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.

" }, "AlgorithmStatus":{ "type":"string", @@ -4957,7 +4957,7 @@ }, "ResourceSpec":{"shape":"ResourceSpec"} }, - "documentation":"

Details about an Amazon SageMaker app.

" + "documentation":"

Details about an Amazon SageMaker AI app.

" }, "AppImageConfigArn":{ "type":"string", @@ -4985,7 +4985,7 @@ }, "KernelGatewayImageConfig":{ "shape":"KernelGatewayImageConfig", - "documentation":"

The configuration for the file system and kernels in the SageMaker image.

" + "documentation":"

The configuration for the file system and kernels in the SageMaker AI image.

" }, "JupyterLabAppImageConfig":{ "shape":"JupyterLabAppImageConfig", @@ -4996,7 +4996,7 @@ "documentation":"

The configuration for the file system and the runtime, such as the environment variables and entry point.

" } }, - "documentation":"

The configuration for running a SageMaker image as a KernelGateway app.

" + "documentation":"

The configuration for running a SageMaker AI image as a KernelGateway app.

" }, "AppImageConfigList":{ "type":"list", @@ -6322,7 +6322,7 @@ "members":{ "S3DataType":{ "shape":"AutoMLS3DataType", - "documentation":"

The data type.

" + "documentation":"

The data type.

" }, "S3Uri":{ "shape":"S3Uri", @@ -6980,14 +6980,14 @@ "members":{ "CsvContentTypes":{ "shape":"CsvContentTypes", - "documentation":"

The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.

" + "documentation":"

The list of all content type headers that Amazon SageMaker AI will treat as CSV and capture accordingly.

" }, "JsonContentTypes":{ "shape":"JsonContentTypes", - "documentation":"

The list of all content type headers that SageMaker will treat as JSON and capture accordingly.

" + "documentation":"

The list of all content type headers that SageMaker AI will treat as JSON and capture accordingly.

" } }, - "documentation":"

Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.

" + "documentation":"

Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker AI will by default base64 encode when capturing the data.

" }, "CaptureMode":{ "type":"string", @@ -7597,6 +7597,7 @@ }, "ClusterInstanceCount":{ "type":"integer", + "max":6758, "min":0 }, "ClusterInstanceGroupDetails":{ @@ -7837,7 +7838,34 @@ "ml.g6e.48xlarge", "ml.p5e.48xlarge", "ml.p5en.48xlarge", - "ml.trn2.48xlarge" + "ml.trn2.48xlarge", + "ml.c6i.large", + "ml.c6i.xlarge", + "ml.c6i.2xlarge", + "ml.c6i.4xlarge", + "ml.c6i.8xlarge", + "ml.c6i.12xlarge", + "ml.c6i.16xlarge", + "ml.c6i.24xlarge", + "ml.c6i.32xlarge", + "ml.m6i.large", + "ml.m6i.xlarge", + "ml.m6i.2xlarge", + "ml.m6i.4xlarge", + "ml.m6i.8xlarge", + "ml.m6i.12xlarge", + "ml.m6i.16xlarge", + "ml.m6i.24xlarge", + "ml.m6i.32xlarge", + "ml.r6i.large", + "ml.r6i.xlarge", + "ml.r6i.2xlarge", + "ml.r6i.4xlarge", + "ml.r6i.8xlarge", + "ml.r6i.12xlarge", + "ml.r6i.16xlarge", + "ml.r6i.24xlarge", + "ml.r6i.32xlarge" ] }, "ClusterLifeCycleConfig":{ @@ -8186,7 +8214,7 @@ "documentation":"

The URL of the Git repository.

" } }, - "documentation":"

A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.

" + "documentation":"

A Git repository that SageMaker AI automatically displays to users for cloning in the JupyterServer application.

" }, "CodeRepositoryArn":{ "type":"string", @@ -9080,7 +9108,7 @@ }, "ResourceSpec":{ "shape":"ResourceSpec", - "documentation":"

The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.

The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.

" + "documentation":"

The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.

The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.

" } } }, @@ -9392,7 +9420,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.

During model compilation, Amazon SageMaker needs your permission to:

You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker Roles.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.

During model compilation, Amazon SageMaker AI needs your permission to:

You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.

" }, "ModelPackageVersionArn":{ "shape":"ModelPackageArn", @@ -9412,7 +9440,7 @@ }, "StoppingCondition":{ "shape":"StoppingCondition", - "documentation":"

Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.

" + "documentation":"

Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.

" }, "Tags":{ "shape":"TagList", @@ -9426,7 +9454,7 @@ "members":{ "CompilationJobArn":{ "shape":"CompilationJobArn", - "documentation":"

If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:

" + "documentation":"

If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns the following data in JSON format:

" } } }, @@ -9564,7 +9592,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"}, "Tags":{ @@ -9656,7 +9684,7 @@ }, "AppNetworkAccessType":{ "shape":"AppNetworkAccessType", - "documentation":"

Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.

" + "documentation":"

Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.

" }, "HomeEfsFileSystemKmsKeyId":{ "shape":"KmsKeyId", @@ -9666,7 +9694,7 @@ }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

SageMaker uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.

" + "documentation":"

SageMaker AI uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.

" }, "AppSecurityGroupManagement":{ "shape":"AppSecurityGroupManagement", @@ -9835,7 +9863,7 @@ }, "ExecutionRoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform actions on your behalf. For more information, see SageMaker Roles.

To be able to pass this role to Amazon SageMaker, the caller of this action must have the iam:PassRole permission.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.

To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.

" }, "VpcConfig":{"shape":"VpcConfig"}, "EnableNetworkIsolation":{ @@ -10208,7 +10236,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.

" + "documentation":"

The ARN of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.

" }, "Tags":{ "shape":"TagList", @@ -10256,7 +10284,7 @@ }, "JobType":{ "shape":"JobType", - "documentation":"

Indicates SageMaker job type compatibility.

" + "documentation":"

Indicates SageMaker AI job type compatibility.

" }, "MLFramework":{ "shape":"MLFramework", @@ -10602,7 +10630,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"}, "Tags":{ @@ -10732,7 +10760,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"}, "Tags":{ @@ -10967,7 +10995,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"}, "Tags":{ @@ -11043,11 +11071,11 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.

To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.

" + "documentation":"

When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker AI assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker AI can perform these tasks. The policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker AI Roles.

To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.

" }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.

" + "documentation":"

The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker AI uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.

" }, "Tags":{ "shape":"TagList", @@ -11059,7 +11087,7 @@ }, "DirectInternetAccess":{ "shape":"DirectInternetAccess", - "documentation":"

Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.

For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.

" + "documentation":"

Sets whether SageMaker AI provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker AI training and endpoint services unless you configure a NAT Gateway in your VPC.

For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.

" }, "VolumeSizeInGB":{ "shape":"NotebookInstanceVolumeSizeInGB", @@ -11071,11 +11099,11 @@ }, "DefaultCodeRepository":{ "shape":"CodeRepositoryNameOrUrl", - "documentation":"

A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "AdditionalCodeRepositories":{ "shape":"AdditionalCodeRepositoryNamesOrUrls", - "documentation":"

An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "RootAccess":{ "shape":"RootAccess", @@ -11145,7 +11173,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.

During model optimization, Amazon SageMaker needs your permission to:

You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker Roles.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.

During model optimization, Amazon SageMaker AI needs your permission to:

You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.

" }, "ModelSource":{ "shape":"OptimizationJobModelSource", @@ -11585,11 +11613,11 @@ "members":{ "StudioLifecycleConfigName":{ "shape":"StudioLifecycleConfigName", - "documentation":"

The name of the Amazon SageMaker Studio Lifecycle Configuration to create.

" + "documentation":"

The name of the Amazon SageMaker AI Studio Lifecycle Configuration to create.

" }, "StudioLifecycleConfigContent":{ "shape":"StudioLifecycleConfigContent", - "documentation":"

The content of your Amazon SageMaker Studio Lifecycle Configuration script. This content must be base64 encoded.

" + "documentation":"

The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This content must be base64 encoded.

" }, "StudioLifecycleConfigAppType":{ "shape":"StudioLifecycleConfigAppType", @@ -12073,7 +12101,7 @@ "documentation":"

A custom file system in Amazon FSx for Lustre.

" } }, - "documentation":"

A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.

", + "documentation":"

A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

", "union":true }, "CustomFileSystemConfig":{ @@ -12088,7 +12116,7 @@ "documentation":"

The settings for a custom Amazon FSx for Lustre file system.

" } }, - "documentation":"

The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.

", + "documentation":"

The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

", "union":true }, "CustomFileSystemConfigs":{ @@ -12122,7 +12150,7 @@ "documentation":"

The name of the AppImageConfig.

" } }, - "documentation":"

A custom SageMaker image. For more information, see Bring your own SageMaker image.

" + "documentation":"

A custom SageMaker AI image. For more information, see Bring your own SageMaker AI image.

" }, "CustomImageContainerArguments":{ "type":"list", @@ -12218,7 +12246,7 @@ }, "InitialSamplingPercentage":{ "shape":"SamplingPercentage", - "documentation":"

The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.

" + "documentation":"

The percentage of requests SageMaker AI will capture. A lower value is recommended for Endpoints with high traffic.

" }, "DestinationS3Uri":{ "shape":"DestinationS3Uri", @@ -12226,7 +12254,7 @@ }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.

The KmsKeyId can be any of the following formats:

" + "documentation":"

The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI uses to encrypt the captured data at rest using Amazon S3 server-side encryption.

The KmsKeyId can be any of the following formats:

" }, "CaptureOptions":{ "shape":"CaptureOptionList", @@ -12234,10 +12262,10 @@ }, "CaptureContentTypeHeader":{ "shape":"CaptureContentTypeHeader", - "documentation":"

Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.

" + "documentation":"

Configuration specifying how to treat different headers. If no headers are specified SageMaker AI will by default base64 encode when capturing the data.

" } }, - "documentation":"

Configuration to control how SageMaker captures inference data.

" + "documentation":"

Configuration to control how SageMaker AI captures inference data.

" }, "DataCaptureConfigSummary":{ "type":"structure", @@ -12578,7 +12606,7 @@ "CustomPosixUserConfig":{"shape":"CustomPosixUserConfig"}, "CustomFileSystemConfigs":{ "shape":"CustomFileSystemConfigs", - "documentation":"

The settings for assigning a custom file system to a domain. Permitted users can access this file system in Amazon SageMaker Studio.

" + "documentation":"

The settings for assigning a custom file system to a domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

" } }, "documentation":"

The default settings for shared spaces that users create in the domain.

SageMaker applies these settings only to shared spaces. It doesn't apply them to private spaces.

" @@ -13190,7 +13218,7 @@ "members":{ "NotebookInstanceName":{ "shape":"NotebookInstanceName", - "documentation":"

The name of the SageMaker notebook instance to delete.

" + "documentation":"

The name of the SageMaker AI notebook instance to delete.

" } } }, @@ -13298,7 +13326,7 @@ "members":{ "StudioLifecycleConfigName":{ "shape":"StudioLifecycleConfigName", - "documentation":"

The name of the Amazon SageMaker Studio Lifecycle Configuration to delete.

" + "documentation":"

The name of the Amazon SageMaker AI Studio Lifecycle Configuration to delete.

" } } }, @@ -13803,11 +13831,11 @@ }, "LastUserActivityTimestamp":{ "shape":"Timestamp", - "documentation":"

The timestamp of the last user's activity. LastUserActivityTimestamp is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.

" + "documentation":"

The timestamp of the last user's activity. LastUserActivityTimestamp is also updated when SageMaker AI performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.

" }, "CreationTime":{ "shape":"Timestamp", - "documentation":"

The creation time of the application.

After an application has been shut down for 24 hours, SageMaker deletes all metadata for the application. To be considered an update and retain application metadata, applications must be restarted within 24 hours after the previous application has been shut down. After this time window, creation of an application is considered a new application rather than an update of the previous application.

" + "documentation":"

The creation time of the application.

After an application has been shut down for 24 hours, SageMaker AI deletes all metadata for the application. To be considered an update and retain application metadata, applications must be restarted within 24 hours after the previous application has been shut down. After this time window, creation of an application is considered a new application rather than an update of the previous application.

" }, "FailureReason":{ "shape":"FailureReason", @@ -13815,7 +13843,7 @@ }, "ResourceSpec":{ "shape":"ResourceSpec", - "documentation":"

The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.

" + "documentation":"

The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.

" }, "BuiltInLifecycleConfigArn":{ "shape":"StudioLifecycleConfigArn", @@ -13951,7 +13979,7 @@ }, "BestCandidate":{ "shape":"AutoMLCandidate", - "documentation":"

The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.

" + "documentation":"

The best model candidate selected by SageMaker AI Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.

" }, "AutoMLJobStatus":{ "shape":"AutoMLJobStatus", @@ -14336,11 +14364,11 @@ }, "CompilationEndTime":{ "shape":"Timestamp", - "documentation":"

The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.

" + "documentation":"

The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker AI detected that the job failed.

" }, "StoppingCondition":{ "shape":"StoppingCondition", - "documentation":"

Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.

" + "documentation":"

Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.

" }, "InferenceImage":{ "shape":"InferenceImage", @@ -14372,7 +14400,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model compilation job.

" }, "InputConfig":{ "shape":"InputConfig", @@ -14582,7 +14610,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"} } @@ -14751,7 +14779,7 @@ }, "SingleSignOnApplicationArn":{ "shape":"SingleSignOnApplicationArn", - "documentation":"

The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after October 1, 2023.

" + "documentation":"

The ARN of the application managed by SageMaker AI in IAM Identity Center. This value is only returned for domains created after October 1, 2023.

" }, "Status":{ "shape":"DomainStatus", @@ -14787,7 +14815,7 @@ }, "AppNetworkAccessType":{ "shape":"AppNetworkAccessType", - "documentation":"

Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.

" + "documentation":"

Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.

" }, "HomeEfsFileSystemKmsKeyId":{ "shape":"KmsKeyId", @@ -15749,7 +15777,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.

" + "documentation":"

The ARN of the IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.

" } } }, @@ -15816,7 +15844,7 @@ }, "JobType":{ "shape":"JobType", - "documentation":"

Indicates SageMaker job type compatibility.

" + "documentation":"

Indicates SageMaker AI job type compatibility.

" }, "MLFramework":{ "shape":"MLFramework", @@ -16827,7 +16855,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" }, "StoppingCondition":{"shape":"MonitoringStoppingCondition"} } @@ -16953,7 +16981,7 @@ }, "NotebookInstanceName":{ "shape":"NotebookInstanceName", - "documentation":"

The name of the SageMaker notebook instance.

" + "documentation":"

The name of the SageMaker AI notebook instance.

" }, "NotebookInstanceStatus":{ "shape":"NotebookInstanceStatus", @@ -16985,11 +17013,11 @@ }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.

" + "documentation":"

The Amazon Web Services KMS key ID SageMaker AI uses to encrypt data when storing it on the ML storage volume attached to the instance.

" }, "NetworkInterfaceId":{ "shape":"NetworkInterfaceId", - "documentation":"

The network interface IDs that SageMaker created at the time of creating the instance.

" + "documentation":"

The network interface IDs that SageMaker AI created at the time of creating the instance.

" }, "LastModifiedTime":{ "shape":"LastModifiedTime", @@ -17005,7 +17033,7 @@ }, "DirectInternetAccess":{ "shape":"DirectInternetAccess", - "documentation":"

Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.

For more information, see Notebook Instances Are Internet-Enabled by Default.

" + "documentation":"

Describes whether SageMaker AI provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker AI training and endpoint services.

For more information, see Notebook Instances Are Internet-Enabled by Default.

" }, "VolumeSizeInGB":{ "shape":"NotebookInstanceVolumeSizeInGB", @@ -17017,11 +17045,11 @@ }, "DefaultCodeRepository":{ "shape":"CodeRepositoryNameOrUrl", - "documentation":"

The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "AdditionalCodeRepositories":{ "shape":"AdditionalCodeRepositoryNamesOrUrls", - "documentation":"

An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "RootAccess":{ "shape":"RootAccess", @@ -17591,7 +17619,7 @@ "members":{ "StudioLifecycleConfigName":{ "shape":"StudioLifecycleConfigName", - "documentation":"

The name of the Amazon SageMaker Studio Lifecycle Configuration to describe.

" + "documentation":"

The name of the Amazon SageMaker AI Studio Lifecycle Configuration to describe.

" } } }, @@ -17604,19 +17632,19 @@ }, "StudioLifecycleConfigName":{ "shape":"StudioLifecycleConfigName", - "documentation":"

The name of the Amazon SageMaker Studio Lifecycle Configuration that is described.

" + "documentation":"

The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is described.

" }, "CreationTime":{ "shape":"Timestamp", - "documentation":"

The creation time of the Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

The creation time of the Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "LastModifiedTime":{ "shape":"Timestamp", - "documentation":"

This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.

" + "documentation":"

This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.

" }, "StudioLifecycleConfigContent":{ "shape":"StudioLifecycleConfigContent", - "documentation":"

The content of your Amazon SageMaker Studio Lifecycle Configuration script.

" + "documentation":"

The content of your Amazon SageMaker AI Studio Lifecycle Configuration script.

" }, "StudioLifecycleConfigAppType":{ "shape":"StudioLifecycleConfigAppType", @@ -18738,7 +18766,7 @@ }, "ExecutionRoleIdentityConfig":{ "shape":"ExecutionRoleIdentityConfig", - "documentation":"

The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.

" + "documentation":"

The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key.

" }, "DockerSettings":{ "shape":"DockerSettings", @@ -18760,7 +18788,7 @@ }, "ExecutionRoleIdentityConfig":{ "shape":"ExecutionRoleIdentityConfig", - "documentation":"

The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.

" + "documentation":"

The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.

" }, "SecurityGroupIds":{ "shape":"DomainSecurityGroupIds", @@ -18908,7 +18936,7 @@ "documentation":"

The ID of your Amazon EFS file system.

" } }, - "documentation":"

A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.

" + "documentation":"

A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

" }, "EFSFileSystemConfig":{ "type":"structure", @@ -18920,10 +18948,10 @@ }, "FileSystemPath":{ "shape":"FileSystemPath", - "documentation":"

The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.

" + "documentation":"

The path to the file system directory that is accessible in Amazon SageMaker AI Studio. Permitted users can access only this directory and below.

" } }, - "documentation":"

The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker Domain.

" + "documentation":"

The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker AI Domain.

" }, "EMRStepMetadata":{ "type":"structure", @@ -20445,7 +20473,7 @@ "box":true } }, - "documentation":"

The Amazon Elastic File System storage configuration for a SageMaker image.

" + "documentation":"

The Amazon Elastic File System storage configuration for a SageMaker AI image.

" }, "FileSystemDataSource":{ "type":"structure", @@ -22322,7 +22350,7 @@ "documentation":"

When the image was last modified.

" } }, - "documentation":"

A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion.

" + "documentation":"

A SageMaker AI image. A SageMaker AI image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker AI ImageVersion.

" }, "ImageArn":{ "type":"string", @@ -22476,7 +22504,7 @@ "documentation":"

The version number.

" } }, - "documentation":"

A version of a SageMaker Image. A version represents an existing container image.

" + "documentation":"

A version of a SageMaker AI Image. A version represents an existing container image.

" }, "ImageVersionAlias":{ "type":"string", @@ -22722,7 +22750,7 @@ "members":{ "ModelName":{ "shape":"ModelName", - "documentation":"

The name of an existing SageMaker model object in your account that you want to deploy with the inference component.

" + "documentation":"

The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.

" }, "Container":{ "shape":"InferenceComponentContainerSpecification", @@ -22748,7 +22776,7 @@ "members":{ "ModelName":{ "shape":"ModelName", - "documentation":"

The name of the SageMaker model object that is deployed with the inference component.

" + "documentation":"

The name of the SageMaker AI model object that is deployed with the inference component.

" }, "Container":{ "shape":"InferenceComponentContainerSpecificationSummary", @@ -23650,7 +23678,7 @@ "FileSystemConfig":{"shape":"FileSystemConfig"}, "ContainerConfig":{"shape":"ContainerConfig"} }, - "documentation":"

The configuration for the file system and kernels in a SageMaker image running as a JupyterLab app. The FileSystemConfig object is not supported.

" + "documentation":"

The configuration for the file system and kernels in a SageMaker AI image running as a JupyterLab app. The FileSystemConfig object is not supported.

" }, "JupyterLabAppSettings":{ "type":"structure", @@ -23688,7 +23716,7 @@ "members":{ "DefaultResourceSpec":{ "shape":"ResourceSpec", - "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.

" + "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.

" }, "LifecycleConfigArns":{ "shape":"LifecycleConfigArns", @@ -23696,7 +23724,7 @@ }, "CodeRepositories":{ "shape":"CodeRepositories", - "documentation":"

A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.

" + "documentation":"

A list of Git repositories that SageMaker AI automatically displays to users for cloning in the JupyterServer application.

" } }, "documentation":"

The JupyterServer app settings.

" @@ -23726,11 +23754,11 @@ "members":{ "DefaultResourceSpec":{ "shape":"ResourceSpec", - "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.

The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not passed.

" + "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the KernelGateway app.

The Amazon SageMaker AI Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not passed.

" }, "CustomImages":{ "shape":"CustomImages", - "documentation":"

A list of custom SageMaker images that are configured to run as a KernelGateway app.

" + "documentation":"

A list of custom SageMaker AI images that are configured to run as a KernelGateway app.

" }, "LifecycleConfigArns":{ "shape":"LifecycleConfigArns", @@ -23749,10 +23777,10 @@ }, "FileSystemConfig":{ "shape":"FileSystemConfig", - "documentation":"

The Amazon Elastic File System storage configuration for a SageMaker image.

" + "documentation":"

The Amazon Elastic File System storage configuration for a SageMaker AI image.

" } }, - "documentation":"

The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.

" + "documentation":"

The configuration for the file system and kernels in a SageMaker AI image running as a KernelGateway app.

" }, "KernelName":{ "type":"string", @@ -24358,7 +24386,7 @@ "members":{ "SageMakerImageVersionAliases":{ "shape":"SageMakerImageVersionAliases", - "documentation":"

A list of SageMaker image version aliases.

" + "documentation":"

A list of SageMaker AI image version aliases.

" }, "NextToken":{ "shape":"NextToken", @@ -24961,7 +24989,7 @@ }, "NextToken":{ "shape":"NextToken", - "documentation":"

If the response is truncated, Amazon SageMaker returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.

" + "documentation":"

If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.

" } } }, @@ -26949,7 +26977,7 @@ }, "NextToken":{ "shape":"NextToken", - "documentation":"

If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.

" + "documentation":"

If the response is truncated, Amazon SageMaker AI returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.

" } } }, @@ -27281,7 +27309,7 @@ "members":{ "NextToken":{ "shape":"NextToken", - "documentation":"

If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.

" + "documentation":"

If the response is truncated, SageMaker AI returns this token. To get the next set of lifecycle configurations, use it in the next request.

" }, "NotebookInstanceLifecycleConfigs":{ "shape":"NotebookInstanceLifecycleConfigSummaryList", @@ -27351,7 +27379,7 @@ "members":{ "NextToken":{ "shape":"NextToken", - "documentation":"

If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.

" + "documentation":"

If the response to the previous ListNotebookInstances request was truncated, SageMaker AI returns this token. To retrieve the next set of notebook instances, use the token in the next request.

" }, "NotebookInstances":{ "shape":"NotebookInstanceSummaryList", @@ -28765,11 +28793,11 @@ "Projects", "InferenceOptimization", "PerformanceEvaluation", - "HyperPodClusters", "LakeraGuard", "Comet", "DeepchecksLLMEvaluation", - "Fiddler" + "Fiddler", + "HyperPodClusters" ] }, "MlflowVersion":{ @@ -30644,7 +30672,7 @@ }, "VolumeKmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.

" + "documentation":"

The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.

" } }, "documentation":"

Configuration for the cluster used to run model monitoring jobs.

" @@ -30820,7 +30848,7 @@ }, "MonitoringInputs":{ "shape":"MonitoringInputs", - "documentation":"

The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.

" + "documentation":"

The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker AI Endpoint.

" }, "MonitoringOutputConfig":{ "shape":"MonitoringOutputConfig", @@ -30848,7 +30876,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

" + "documentation":"

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

" } }, "documentation":"

Defines the monitoring job.

" @@ -30954,7 +30982,7 @@ }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.

" + "documentation":"

The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.

" } }, "documentation":"

The output configuration for monitoring jobs.

" @@ -30999,11 +31027,11 @@ "members":{ "S3Uri":{ "shape":"MonitoringS3Uri", - "documentation":"

A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.

" + "documentation":"

A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job.

" }, "LocalPath":{ "shape":"ProcessingLocalPath", - "documentation":"

The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.

" + "documentation":"

The local path to the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job. LocalPath is an absolute path for the output data.

" }, "S3UploadMode":{ "shape":"ProcessingS3UploadMode", @@ -31227,7 +31255,7 @@ "documentation":"

The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.

" } }, - "documentation":"

The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.

" + "documentation":"

The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker AI Compilation Jobs Access to Resources in Your Amazon VPC.

" }, "NeoVpcSecurityGroupId":{ "type":"string", @@ -31483,14 +31511,14 @@ }, "DefaultCodeRepository":{ "shape":"CodeRepositoryNameOrUrl", - "documentation":"

The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "AdditionalCodeRepositories":{ "shape":"AdditionalCodeRepositoryNamesOrUrls", - "documentation":"

An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" } }, - "documentation":"

Provides summary information for an SageMaker notebook instance.

" + "documentation":"

Provides summary information for an SageMaker AI notebook instance.

" }, "NotebookInstanceSummaryList":{ "type":"list", @@ -32061,7 +32089,7 @@ "members":{ "S3OutputLocation":{ "shape":"S3Uri", - "documentation":"

Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.

" + "documentation":"

Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For example, s3://bucket-name/key-name-prefix.

" }, "TargetDevice":{ "shape":"TargetDevice", @@ -32077,7 +32105,7 @@ }, "KmsKeyId":{ "shape":"KmsKeyId", - "documentation":"

The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.

The KmsKeyId can be any of the following formats:

" + "documentation":"

The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker AI uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.

The KmsKeyId can be any of the following formats:

" } }, "documentation":"

Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.

" @@ -34520,7 +34548,7 @@ "DefaultResourceSpec":{"shape":"ResourceSpec"}, "CustomImages":{ "shape":"CustomImages", - "documentation":"

A list of custom SageMaker images that are configured to run as a RSession app.

" + "documentation":"

A list of custom SageMaker AI images that are configured to run as a RSession app.

" } }, "documentation":"

A collection of settings that apply to an RSessionGateway app.

" @@ -35606,7 +35634,7 @@ "members":{ "SageMakerImageArn":{ "shape":"ImageArn", - "documentation":"

The ARN of the SageMaker image that the image version belongs to.

" + "documentation":"

The ARN of the SageMaker AI image that the image version belongs to.

" }, "SageMakerImageVersionArn":{ "shape":"ImageVersionArn", @@ -35625,7 +35653,7 @@ "documentation":"

The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.

" } }, - "documentation":"

Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.

" + "documentation":"

Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.

" }, "ResourceType":{ "type":"string", @@ -36016,7 +36044,7 @@ "members":{ "ScheduleExpression":{ "shape":"ScheduleExpression", - "documentation":"

A cron expression that describes details about the monitoring schedule.

The supported cron expressions are:

For example, the following are valid cron expressions:

To support running every 6, 12 hours, the following are also supported:

cron(0 [00-23]/[01-24] ? * * *)

For example, the following are valid cron expressions:

You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.

" + "documentation":"

A cron expression that describes details about the monitoring schedule.

The supported cron expressions are:

For example, the following are valid cron expressions:

To support running every 6, 12 hours, the following are also supported:

cron(0 [00-23]/[01-24] ? * * *)

For example, the following are valid cron expressions:

You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.

" }, "DataAnalysisStartTime":{ "shape":"String", @@ -36571,7 +36599,7 @@ "documentation":"

When NotebookOutputOption is Allowed, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.

" } }, - "documentation":"

Specifies options for sharing Amazon SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn't allowed.

" + "documentation":"

Specifies options for sharing Amazon SageMaker AI Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn't allowed.

" }, "SharingType":{ "type":"string", @@ -36908,7 +36936,7 @@ }, "AppType":{ "shape":"AppType", - "documentation":"

The type of app created within the space.

" + "documentation":"

The type of app created within the space.

If using the UpdateSpace API, you can't change the app type of your space by specifying a different value for this field.

" }, "SpaceStorageSettings":{ "shape":"SpaceStorageSettings", @@ -36916,7 +36944,7 @@ }, "CustomFileSystems":{ "shape":"CustomFileSystems", - "documentation":"

A file system, created by you, that you assign to a space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.

" + "documentation":"

A file system, created by you, that you assign to a space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

" } }, "documentation":"

A collection of space settings.

" @@ -37522,22 +37550,22 @@ }, "StudioLifecycleConfigName":{ "shape":"StudioLifecycleConfigName", - "documentation":"

The name of the Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

The name of the Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "CreationTime":{ "shape":"Timestamp", - "documentation":"

The creation time of the Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

The creation time of the Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "LastModifiedTime":{ "shape":"Timestamp", - "documentation":"

This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.

" + "documentation":"

This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.

" }, "StudioLifecycleConfigAppType":{ "shape":"StudioLifecycleConfigAppType", "documentation":"

The App type to which the Lifecycle Configuration is attached.

" } }, - "documentation":"

Details of the Amazon SageMaker Studio Lifecycle Configuration.

" + "documentation":"

Details of the Amazon SageMaker AI Studio Lifecycle Configuration.

" }, "StudioLifecycleConfigName":{ "type":"string", @@ -37924,7 +37952,7 @@ "members":{ "DefaultResourceSpec":{ "shape":"ResourceSpec", - "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.

" + "documentation":"

The default instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.

" } }, "documentation":"

The TensorBoard app settings.

" @@ -39280,6 +39308,8 @@ "ml.g5.16xlarge", "ml.g5.24xlarge", "ml.g5.48xlarge", + "ml.trn1.2xlarge", + "ml.trn1.32xlarge", "ml.inf2.xlarge", "ml.inf2.8xlarge", "ml.inf2.24xlarge", @@ -40479,7 +40509,7 @@ }, "AppNetworkAccessType":{ "shape":"AppNetworkAccessType", - "documentation":"

Specifies the VPC used for non-EFS traffic.

This configuration can only be modified if there are no apps in the InService, Pending, or Deleting state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided as part of the same request.

" + "documentation":"

Specifies the VPC used for non-EFS traffic.

This configuration can only be modified if there are no apps in the InService, Pending, or Deleting state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided as part of the same request.

" }, "TagPropagation":{ "shape":"TagPropagation", @@ -40705,7 +40735,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.

" + "documentation":"

The new ARN for the IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.

" } } }, @@ -40748,7 +40778,7 @@ }, "JobType":{ "shape":"JobType", - "documentation":"

Indicates SageMaker job type compatibility.

" + "documentation":"

Indicates SageMaker AI job type compatibility.

" }, "MLFramework":{ "shape":"MLFramework", @@ -41081,7 +41111,7 @@ }, "RoleArn":{ "shape":"RoleArn", - "documentation":"

The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.

To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.

" + "documentation":"

The Amazon Resource Name (ARN) of the IAM role that SageMaker AI can assume to access the notebook instance. For more information, see SageMaker AI Roles.

To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.

" }, "LifecycleConfigName":{ "shape":"NotebookInstanceLifecycleConfigName", @@ -41093,15 +41123,15 @@ }, "VolumeSizeInGB":{ "shape":"NotebookInstanceVolumeSizeInGB", - "documentation":"

The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.

" + "documentation":"

The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker AI can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.

" }, "DefaultCodeRepository":{ "shape":"CodeRepositoryNameOrUrl", - "documentation":"

The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "AdditionalCodeRepositories":{ "shape":"AdditionalCodeRepositoryNamesOrUrls", - "documentation":"

An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.

" + "documentation":"

An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.

" }, "AcceleratorTypes":{ "shape":"NotebookInstanceAcceleratorTypes", @@ -41653,11 +41683,11 @@ }, "SecurityGroups":{ "shape":"SecurityGroupIds", - "documentation":"

The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.

Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.

Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.

Amazon SageMaker adds a security group to allow NFS traffic from Amazon SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.

SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.

" + "documentation":"

The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.

Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.

Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.

Amazon SageMaker AI adds a security group to allow NFS traffic from Amazon SageMaker AI Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.

SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.

" }, "SharingSettings":{ "shape":"SharingSettings", - "documentation":"

Specifies options for sharing Amazon SageMaker Studio notebooks.

" + "documentation":"

Specifies options for sharing Amazon SageMaker AI Studio notebooks.

" }, "JupyterServerAppSettings":{ "shape":"JupyterServerAppSettings", @@ -41709,7 +41739,7 @@ }, "CustomFileSystemConfigs":{ "shape":"CustomFileSystemConfigs", - "documentation":"

The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker Studio.

SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.

" + "documentation":"

The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker AI Studio.

SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.

" }, "StudioWebPortalSettings":{ "shape":"StudioWebPortalSettings",