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Merge branch 'main' into aws-audit
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KarolTegha authored Oct 14, 2024
2 parents c5a1460 + 3b31682 commit fa6a67f
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1 change: 1 addition & 0 deletions .lycheeignore
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Expand Up @@ -5,3 +5,4 @@ https://entra.microsoft.com*
https://knowledge.hitachivantara.com*
http://sso.hitachivantara.com*
https://www.kubecost.com/pricing/*
https://www.gnu.org/*
2 changes: 1 addition & 1 deletion install-and-configure/advanced-configuration/add-key.md
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Expand Up @@ -32,7 +32,7 @@ Update your [_values.yaml_](https://github.com/kubecost/cost-analyzer-helm-chart
kubecostProductConfigs:
productKey:
enabled: true
secretName: <SECRET_NAME>
secretname: <SECRET_NAME>
```
## Option 2: Apply your product key to _values.yaml_ and upgrade Kubecost
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2 changes: 1 addition & 1 deletion install-and-configure/advanced-configuration/gpu.md
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Expand Up @@ -2,7 +2,7 @@

## Monitoring GPU utilization

In order for Kubecost to understand GPU utilization, Kubecost depends on metrics being available from NVIDIA [DCGM Exporter](https://github.com/NVIDIA/dcgm-exporter). Kubecost will search for GPU metrics by default, but since DCGM Exporter is the provider of those metrics it is a required component when GPU monitoring is used with Kubecost and must be installed if it is not already. In many cases, DCGM Exporter may already be installed in your cluster, for example if you currently monitor NVIDIA GPUs with other software. But if not, follow the below instructions to install and configure DCGM Exporter on each of your GPU-enabled clusters.
Kubecost supports monitoring of NVIDIA GPU utilization starting with the Volta architecture (2017). In order for Kubecost to understand GPU utilization, Kubecost depends on metrics being available from NVIDIA [DCGM Exporter](https://github.com/NVIDIA/dcgm-exporter). Kubecost will search for GPU metrics by default, but since DCGM Exporter is the provider of those metrics it is a required component when GPU monitoring is used with Kubecost and must be installed if it is not already. In many cases, DCGM Exporter may already be installed in your cluster, for example if you currently monitor NVIDIA GPUs with other software. But if not, follow the below instructions to install and configure DCGM Exporter on each of your GPU-enabled clusters.

## Install DCGM Exporter

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Expand Up @@ -128,7 +128,7 @@ This step can take some time depending on how much data the Aggregator must proc
* The ETL Utils image is building the directory structure in the object store needed by Aggregator to pull the ETL data.
* SQL tables are building.

Ensure all data loads into the Kubecost UI before moving onto Step 7.
Ensure all data loads into the Kubecost UI before moving onto Step 8.

### Step 8: Upgrade your secondary clusters to build and push ETL data

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28 changes: 14 additions & 14 deletions using-kubecost/navigating-the-kubecost-ui/external-costs.md
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Expand Up @@ -34,13 +34,13 @@ kubecostModel:
enabled: true
enabledPlugins:
- datadog
configs:
datadog: |
{
"datadog_site": "us5.datadoghq.com",
"datadog_api_key": "847081f247542151fc63b4dXXXX",
"datadog_app_key": "6515819e6a3fb23c0dc3d6032ffc84XXXXX"
}
configs:
datadog: |
{
"datadog_site": "us5.datadoghq.com",
"datadog_api_key": "847081f247542151fc63b4dXXXX",
"datadog_app_key": "6515819e6a3fb23c0dc3d6032ffc84XXXXX"
}
```
Now update your Kubecost install via `helm`:
Expand Down Expand Up @@ -93,13 +93,13 @@ kubecostModel:
enabled: true
enabledPlugins:
- datadog
configs:
datadog: |
{
"datadog_site": "us5.datadoghq.com",
"datadog_api_key": "847081f247542151fc63b4dXXXX",
"datadog_app_key": "6515819e6a3fb23c0dc3d6032ffc84XXXXX"
}
configs:
datadog: |
{
"datadog_site": "us5.datadoghq.com",
"datadog_api_key": "847081f247542151fc63b4dXXXX",
"datadog_app_key": "6515819e6a3fb23c0dc3d6032ffc84XXXXX"
}
install:
enabled: true
fullImageName: curlimages/curl:latest
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