Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

chore(deps): bump tonic-build from 0.8.4 to 0.9.1 #17102

Closed
wants to merge 1 commit into from

Conversation

dependabot[bot]
Copy link
Contributor

@dependabot dependabot bot commented on behalf of github Apr 11, 2023

Bumps tonic-build from 0.8.4 to 0.9.1.

Changelog

Sourced from tonic-build's changelog.

v0.9.1 (2023-04-03)

Features

  • transport: Update rustls to 0.21 (#1340)

v0.9.0 (2023-03-31)

All tonic-* crates owned by this repository will now be versioned together to make it easier to understand which crate matches the core tonic crate version.

Breaking Changes

  • All crates bumped to 2021 edition
  • tonic-health and tonic-reflection internal protobuf module renamed.
  • Default decoding message limit set to 4MiB by default.

Bug Fixes

Features

  • add GrpcMethod extension into request for client (#1275) (7a6b20d)
  • build: Builder: add {enum,message}_attributes (#1234) (ff642f9)
  • codec: Configure max request message size (#1274) (9f716d8), closes #1097
  • core: Default encoding/decoding limits (#1335) (ff33119)
  • reflection: Add dummy implementation for extension (#1209) (fdff111)
  • Rename api related to protobuf (#1224) (d2542dc)
  • tls: add an option for optional TLS client authentication (#1163) (773e4e1), closes #687
  • tonic: Use NamedService without transport feature (#1273) (5acde56)
  • transport: Add local_addr to Request o (#1327) (b54ce23)
  • transport: added support for EC keys (#1145) (17d6a4b), closes #1143
  • types: Add gRPC Richer Error Model support (Docs) (#1317) (69ce71e)
  • types: Add gRPC Richer Error Model support (Examples) (#1300) (d471212)
  • types: Add gRPC Richer Error Model support (Help) (#1293) (d6041a9)
  • types: Add gRPC Richer Error Model support (LocalizedMessage) (#1295) (d54d02d)
  • types: Add gRPC Richer Error Model support (PreconditionFailure) (#1276) (2378581)
  • types: Add gRPC Richer Error Model support (QuotaFailure) (#1204) (03b4735)
  • types: Add gRPC Richer Error Model support (ResourceInfo) (#1282) (7eeda24)
  • types: Add gRPC Richer Error Model support (RetryInfo) (#1095) (6cdb3d4)
  • types: add support for DebugInfo error message type (#1179) (3076e82)
  • types: Expose FILE_DESCRIPTOR_SET (#1210) (cc42d1f)
  • core: Make some functionality of Status public (#1256)
  • core: Expose Response#into_parts and Response#from_parts (#1263)

... (truncated)

Commits

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

@dependabot dependabot bot requested a review from spencergilbert as a code owner April 11, 2023 04:59
@dependabot dependabot bot requested a review from a team April 11, 2023 04:59
@dependabot dependabot bot added the domain: deps Anything related to Vector's dependencies label Apr 11, 2023
@bits-bot
Copy link

CLA assistant check
Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.
You have signed the CLA already but the status is still pending? Let us recheck it.

@netlify
Copy link

netlify bot commented Apr 11, 2023

Deploy Preview for vector-project canceled.

Name Link
🔨 Latest commit 93703e1
🔍 Latest deploy log https://app.netlify.com/sites/vector-project/deploys/64493a57ba5ff70008f0ed6c

@netlify
Copy link

netlify bot commented Apr 11, 2023

Deploy Preview for vrl-playground ready!

Name Link
🔨 Latest commit 93703e1
🔍 Latest deploy log https://app.netlify.com/sites/vrl-playground/deploys/64493a5740541c0007f35dcb
😎 Deploy Preview https://deploy-preview-17102--vrl-playground.netlify.app
📱 Preview on mobile
Toggle QR Code...

QR Code

Use your smartphone camera to open QR code link.

To edit notification comments on pull requests, go to your Netlify site settings.

@github-actions
Copy link

Regression Detector Results

Run ID: 817d382-823d-41f4-9ac6-0adf7abc9863
Baseline: 887d6d7
Comparison: 91c1042
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values mean that baseline is faster, positive comparison. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean Δ mean % confidence baseline mean baseline stdev baseline stderr baseline outlier % baseline CoV comparison mean comparison stdev comparison stderr comparison outlier % comparison CoV erratic declared erratic
file_to_blackhole egress throughput 1.31MiB/CPU-s 21.11 100.00% 6.19MiB/CPU-s 4.54MiB/CPU-s 131.18KiB/CPU-s 0.0 0.733131 7.5MiB/CPU-s 4.02MiB/CPU-s 141.52KiB/CPU-s 0.35503 0.53533 True True
socket_to_socket_blackhole ingress throughput 507.16KiB/CPU-s 3.69 100.00% 13.44MiB/CPU-s 376.93KiB/CPU-s 4.86KiB/CPU-s 0.0 0.027389 13.93MiB/CPU-s 229.63KiB/CPU-s 2.96KiB/CPU-s 0.0 0.016092 False False
otlp_http_to_blackhole ingress throughput 40.39KiB/CPU-s 2.54 100.00% 1.55MiB/CPU-s 118.82KiB/CPU-s 1.53KiB/CPU-s 0.0 0.074835 1.59MiB/CPU-s 89.46KiB/CPU-s 1.15KiB/CPU-s 0.0 0.054946 False False
datadog_agent_remap_blackhole_acks ingress throughput 472.33KiB/CPU-s 1.51 100.00% 30.49MiB/CPU-s 1.69MiB/CPU-s 22.36KiB/CPU-s 0.0 0.055504 30.95MiB/CPU-s 1.18MiB/CPU-s 15.64KiB/CPU-s 0.0 0.038225 False False
otlp_grpc_to_blackhole ingress throughput 15.06KiB/CPU-s 1.41 100.00% 1.04MiB/CPU-s 50.03KiB/CPU-s 661.02B/CPU-s 0.0 0.046922 1.06MiB/CPU-s 37.91KiB/CPU-s 501.17B/CPU-s 0.0 0.035065 False False
datadog_agent_remap_datadog_logs ingress throughput 449.94KiB/CPU-s 1.34 100.00% 32.82MiB/CPU-s 1.56MiB/CPU-s 20.56KiB/CPU-s 0.0 0.04741 33.26MiB/CPU-s 1.21MiB/CPU-s 15.96KiB/CPU-s 0.0 0.036306 False False
syslog_humio_logs ingress throughput 74.15KiB/CPU-s 0.80 100.00% 9.1MiB/CPU-s 217.19KiB/CPU-s 2.8KiB/CPU-s 0.0 0.023303 9.17MiB/CPU-s 258.09KiB/CPU-s 3.33KiB/CPU-s 0.0 0.027474 False False
datadog_agent_remap_blackhole ingress throughput 251.98KiB/CPU-s 0.80 100.00% 30.76MiB/CPU-s 1.15MiB/CPU-s 15.13KiB/CPU-s 0.0 0.037237 31.0MiB/CPU-s 1013.28KiB/CPU-s 13.08KiB/CPU-s 0.0 0.031914 False False
http_text_to_http_json ingress throughput 187.76KiB/CPU-s 0.72 100.00% 25.56MiB/CPU-s 701.83KiB/CPU-s 9.06KiB/CPU-s 0.0 0.026815 25.74MiB/CPU-s 787.79KiB/CPU-s 10.17KiB/CPU-s 0.0 0.029885 False False
enterprise_http_to_http ingress throughput 7.85KiB/CPU-s 0.06 94.52% 13.62MiB/CPU-s 278.99KiB/CPU-s 3.6KiB/CPU-s 0.0 0.020008 13.62MiB/CPU-s 149.59KiB/CPU-s 1.93KiB/CPU-s 0.0 0.010722 False False
fluent_elasticsearch ingress throughput -97.78B/CPU-s -0.00 13.84% 45.41MiB/CPU-s 30.34KiB/CPU-s 396.54B/CPU-s 0.0 0.000652 45.41MiB/CPU-s 30.32KiB/CPU-s 396.39B/CPU-s 0.0 0.000652 False False
splunk_hec_to_splunk_hec_logs_acks ingress throughput -214.19B/CPU-s -0.00 2.55% 13.61MiB/CPU-s 359.75KiB/CPU-s 4.64KiB/CPU-s 0.0 0.025804 13.61MiB/CPU-s 356.65KiB/CPU-s 4.6KiB/CPU-s 0.0 0.025582 False False
http_to_http_noack ingress throughput 126.28B/CPU-s 0.00 1.41% 13.61MiB/CPU-s 383.3KiB/CPU-s 4.94KiB/CPU-s 0.0 0.027508 13.61MiB/CPU-s 379.93KiB/CPU-s 4.9KiB/CPU-s 0.0 0.027267 False False
splunk_hec_to_splunk_hec_logs_noack ingress throughput 346.11B/CPU-s 0.00 5.45% 13.61MiB/CPU-s 272.05KiB/CPU-s 3.51KiB/CPU-s 0.0 0.019512 13.61MiB/CPU-s 269.67KiB/CPU-s 3.48KiB/CPU-s 0.0 0.019341 False False
splunk_hec_indexer_ack_blackhole ingress throughput -1.61KiB/CPU-s -0.01 27.05% 13.62MiB/CPU-s 251.82KiB/CPU-s 3.25KiB/CPU-s 0.0 0.018059 13.61MiB/CPU-s 259.37KiB/CPU-s 3.35KiB/CPU-s 0.0 0.018602 False False
syslog_log2metric_humio_metrics ingress throughput -2.75KiB/CPU-s -0.04 54.10% 6.44MiB/CPU-s 228.75KiB/CPU-s 2.95KiB/CPU-s 0.0 0.03469 6.44MiB/CPU-s 174.23KiB/CPU-s 2.25KiB/CPU-s 0.0 0.026433 False False
http_to_http_json ingress throughput -21.23KiB/CPU-s -0.15 99.99% 13.58MiB/CPU-s 291.29KiB/CPU-s 3.76KiB/CPU-s 0.0 0.020945 13.56MiB/CPU-s 321.09KiB/CPU-s 4.14KiB/CPU-s 0.0 0.023123 False False
syslog_loki ingress throughput -25.27KiB/CPU-s -0.29 100.00% 8.45MiB/CPU-s 355.24KiB/CPU-s 4.58KiB/CPU-s 0.0 0.041068 8.42MiB/CPU-s 230.16KiB/CPU-s 2.97KiB/CPU-s 0.0 0.026685 False False
datadog_agent_remap_datadog_logs_acks ingress throughput -101.2KiB/CPU-s -0.30 99.99% 32.6MiB/CPU-s 1.34MiB/CPU-s 17.74KiB/CPU-s 0.0 0.041183 32.5MiB/CPU-s 1.41MiB/CPU-s 18.6KiB/CPU-s 0.0 0.043308 False False
syslog_regex_logs2metric_ddmetrics ingress throughput -14.35KiB/CPU-s -0.39 98.12% 3.58MiB/CPU-s 348.81KiB/CPU-s 4.5KiB/CPU-s 0.0 0.095246 3.56MiB/CPU-s 319.5KiB/CPU-s 4.12KiB/CPU-s 0.0 0.087585 False True
http_to_http_acks ingress throughput -48.91KiB/CPU-s -0.90 65.71% 5.31MiB/CPU-s 2.75MiB/CPU-s 36.34KiB/CPU-s 0.0 0.517223 5.27MiB/CPU-s 2.77MiB/CPU-s 36.59KiB/CPU-s 0.0 0.525555 True False
syslog_log2metric_splunk_hec_metrics ingress throughput -96.42KiB/CPU-s -1.00 100.00% 9.37MiB/CPU-s 269.4KiB/CPU-s 3.48KiB/CPU-s 0.0 0.028062 9.28MiB/CPU-s 312.94KiB/CPU-s 4.04KiB/CPU-s 0.0 0.032928 False False
syslog_splunk_hec_logs ingress throughput -111.76KiB/CPU-s -1.22 100.00% 8.96MiB/CPU-s 249.84KiB/CPU-s 3.22KiB/CPU-s 0.0 0.027218 8.85MiB/CPU-s 257.26KiB/CPU-s 3.32KiB/CPU-s 0.0 0.028371 False False
splunk_hec_route_s3 ingress throughput -169.72KiB/CPU-s -1.41 100.00% 11.75MiB/CPU-s 628.52KiB/CPU-s 8.11KiB/CPU-s 0.0 0.052219 11.59MiB/CPU-s 669.17KiB/CPU-s 8.63KiB/CPU-s 0.0 0.056392 False False

@neuronull
Copy link
Contributor

This seems to be blocked on hyperium/tonic#1350

@neuronull neuronull added the meta: blocked Anything that is blocked to the point where it cannot be worked on. label Apr 11, 2023
@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 13, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

5 similar comments
@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 14, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 14, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 19, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 19, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github Apr 20, 2023

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot rebase.

@dependabot dependabot bot force-pushed the dependabot/cargo/tonic-build-0.9.1 branch from 91c1042 to 99391e5 Compare April 24, 2023 21:48
@github-actions
Copy link

Regression Detector Results

Run ID: 7f36d273-0be8-4746-87e4-fdd6960d9a32
Baseline: ef15696
Comparison: 99391e5
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
datadog_agent_remap_datadog_logs_acks ingress throughput +4.02 [+3.90, +4.13] 100.00%
http_text_to_http_json ingress throughput +3.14 [+3.08, +3.21] 100.00%
file_to_blackhole egress throughput +2.95 [-0.48, +6.38] 72.90%
datadog_agent_remap_datadog_logs ingress throughput +2.73 [+2.65, +2.82] 100.00%
syslog_loki ingress throughput +0.67 [+0.59, +0.76] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput +0.43 [+0.35, +0.51] 100.00%
splunk_hec_route_s3 ingress throughput +0.41 [+0.28, +0.54] 99.99%
http_to_http_json ingress throughput +0.32 [+0.26, +0.39] 100.00%
syslog_humio_logs ingress throughput +0.28 [+0.20, +0.36] 100.00%
enterprise_http_to_http ingress throughput +0.04 [+0.01, +0.08] 89.59%
http_to_http_noack ingress throughput +0.03 [-0.03, +0.09] 47.51%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.01 [-0.06, +0.07] 8.00%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 59.06%
splunk_hec_indexer_ack_blackhole ingress throughput -0.01 [-0.05, +0.04] 19.33%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.01 [-0.06, +0.03] 34.02%
datadog_agent_remap_blackhole ingress throughput -0.17 [-0.26, -0.08] 98.36%
otlp_grpc_to_blackhole ingress throughput -0.21 [-0.33, -0.10] 98.14%
http_to_http_acks ingress throughput -0.33 [-1.56, +0.89] 27.35%
syslog_splunk_hec_logs ingress throughput -0.78 [-0.84, -0.71] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput -1.21 [-1.43, -0.99] 100.00%
syslog_log2metric_humio_metrics ingress throughput -1.33 [-1.42, -1.24] 100.00%
otlp_http_to_blackhole ingress throughput -1.33 [-1.50, -1.16] 100.00%
socket_to_socket_blackhole ingress throughput -1.63 [-1.69, -1.56] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -2.34 [-2.42, -2.25] 100.00%

@spencergilbert
Copy link
Contributor

@dependabot rebase

@dependabot dependabot bot force-pushed the dependabot/cargo/tonic-build-0.9.1 branch from 99391e5 to f28050c Compare April 26, 2023 13:09
@github-actions
Copy link

Regression Detector Results

Run ID: c7e1ea0-3a25-4052-babb-65f625a0c1b1
Baseline: c80c5eb
Comparison: f28050c
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
file_to_blackhole egress throughput +2.74 [-0.65, +6.13] 69.96%
datadog_agent_remap_datadog_logs ingress throughput +2.31 [+2.20, +2.43] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput +1.47 [+1.36, +1.59] 100.00%
socket_to_socket_blackhole ingress throughput +0.79 [+0.74, +0.85] 100.00%
syslog_log2metric_humio_metrics ingress throughput +0.65 [+0.55, +0.75] 100.00%
http_to_http_json ingress throughput +0.18 [+0.13, +0.24] 100.00%
syslog_loki ingress throughput +0.08 [+0.01, +0.15] 83.83%
http_to_http_noack ingress throughput +0.03 [-0.03, +0.09] 47.40%
enterprise_http_to_http ingress throughput +0.01 [-0.01, +0.04] 48.37%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.06, +0.07] 2.26%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 8.94%
splunk_hec_indexer_ack_blackhole ingress throughput -0.01 [-0.05, +0.03] 22.92%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.02 [-0.07, +0.02] 52.36%
datadog_agent_remap_blackhole ingress throughput -0.30 [-0.41, -0.19] 99.94%
http_to_http_acks ingress throughput -0.73 [-1.93, +0.48] 56.10%
syslog_regex_logs2metric_ddmetrics ingress throughput -0.97 [-1.21, -0.73] 100.00%
otlp_http_to_blackhole ingress throughput -1.08 [-1.23, -0.92] 100.00%
otlp_grpc_to_blackhole ingress throughput -1.10 [-1.21, -0.99] 100.00%
http_text_to_http_json ingress throughput -1.34 [-1.40, -1.28] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput -1.79 [-1.85, -1.73] 100.00%
splunk_hec_route_s3 ingress throughput -2.17 [-2.30, -2.05] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -2.64 [-2.72, -2.55] 100.00%
syslog_splunk_hec_logs ingress throughput -2.92 [-2.99, -2.85] 100.00%
syslog_humio_logs ingress throughput -3.66 [-3.73, -3.60] 100.00%

@dependabot dependabot bot force-pushed the dependabot/cargo/tonic-build-0.9.1 branch from f28050c to 87fb999 Compare April 26, 2023 14:47
Bumps [tonic-build](https://github.com/hyperium/tonic) from 0.8.4 to 0.9.1.
- [Release notes](https://github.com/hyperium/tonic/releases)
- [Changelog](https://github.com/hyperium/tonic/blob/master/CHANGELOG.md)
- [Commits](hyperium/tonic@v0.8.4...v0.9.1)

---
updated-dependencies:
- dependency-name: tonic-build
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot force-pushed the dependabot/cargo/tonic-build-0.9.1 branch from 87fb999 to 93703e1 Compare April 26, 2023 14:51
@github-actions
Copy link

Regression Detector Results

Run ID: 0f17be8a-9f1a-471f-848b-452fa76699f6
Baseline: 410aa3c
Comparison: 87fb999
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_text_to_http_json ingress throughput +2.98 [+2.91, +3.05] 100.00%
file_to_blackhole egress throughput +2.43 [-1.09, +5.95] 62.36%
syslog_log2metric_splunk_hec_metrics ingress throughput +2.41 [+2.33, +2.48] 100.00%
syslog_log2metric_humio_metrics ingress throughput +2.25 [+2.16, +2.34] 100.00%
socket_to_socket_blackhole ingress throughput +2.04 [+1.97, +2.11] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput +1.90 [+1.81, +1.99] 100.00%
datadog_agent_remap_blackhole ingress throughput +1.62 [+1.51, +1.74] 100.00%
http_to_http_json ingress throughput +1.60 [+1.55, +1.66] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput +1.23 [+1.12, +1.34] 100.00%
syslog_humio_logs ingress throughput +1.08 [+1.00, +1.16] 100.00%
syslog_splunk_hec_logs ingress throughput +1.00 [+0.94, +1.07] 100.00%
datadog_agent_remap_datadog_logs ingress throughput +0.54 [+0.43, +0.65] 100.00%
otlp_http_to_blackhole ingress throughput +0.49 [+0.34, +0.65] 99.99%
enterprise_http_to_http ingress throughput +0.03 [-0.00, +0.06] 77.80%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.04, +0.05] 18.81%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.06, +0.07] 5.09%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 7.53%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.02 [-0.06, +0.03] 37.54%
http_to_http_noack ingress throughput -0.05 [-0.10, +0.01] 71.85%
otlp_grpc_to_blackhole ingress throughput -0.25 [-0.36, -0.14] 99.64%
http_to_http_acks ingress throughput -0.33 [-1.55, +0.89] 26.89%
splunk_hec_route_s3 ingress throughput -0.39 [-0.51, -0.26] 99.99%
syslog_loki ingress throughput -1.48 [-1.56, -1.39] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput -2.46 [-2.70, -2.22] 100.00%

@github-actions
Copy link

Regression Detector Results

Run ID: 1fa8935c-5d81-43c9-810e-fcddad21db22
Baseline: 410aa3c
Comparison: 93703e1
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
file_to_blackhole egress throughput +2.66 [-0.86, +6.19] 66.71%
datadog_agent_remap_datadog_logs_acks ingress throughput +2.44 [+2.34, +2.53] 100.00%
datadog_agent_remap_blackhole ingress throughput +2.25 [+2.16, +2.35] 100.00%
syslog_log2metric_humio_metrics ingress throughput +1.10 [+1.02, +1.18] 100.00%
splunk_hec_route_s3 ingress throughput +0.95 [+0.81, +1.08] 100.00%
http_text_to_http_json ingress throughput +0.11 [+0.05, +0.18] 97.78%
enterprise_http_to_http ingress throughput +0.07 [+0.03, +0.11] 98.14%
http_to_http_noack ingress throughput +0.01 [-0.05, +0.07] 23.07%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 37.23%
splunk_hec_indexer_ack_blackhole ingress throughput +0.00 [-0.04, +0.04] 0.62%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.06, +0.06] 0.07%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.01 [-0.06, +0.04] 23.02%
otlp_grpc_to_blackhole ingress throughput -0.09 [-0.19, +0.02] 68.78%
http_to_http_json ingress throughput -0.33 [-0.40, -0.26] 100.00%
http_to_http_acks ingress throughput -0.48 [-1.69, +0.74] 38.45%
syslog_humio_logs ingress throughput -0.62 [-0.70, -0.55] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -0.77 [-0.86, -0.69] 100.00%
syslog_loki ingress throughput -1.22 [-1.31, -1.12] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -1.39 [-1.48, -1.30] 100.00%
otlp_http_to_blackhole ingress throughput -1.42 [-1.59, -1.26] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput -2.11 [-2.18, -2.03] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput -2.12 [-2.36, -1.88] 100.00%
syslog_splunk_hec_logs ingress throughput -2.17 [-2.26, -2.09] 100.00%
socket_to_socket_blackhole ingress throughput -2.69 [-2.75, -2.62] 100.00%

@dependabot @github
Copy link
Contributor Author

dependabot bot commented on behalf of github May 2, 2023

Superseded by #17274.

@dependabot dependabot bot closed this May 2, 2023
@dependabot dependabot bot deleted the dependabot/cargo/tonic-build-0.9.1 branch May 2, 2023 05:05
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
domain: deps Anything related to Vector's dependencies meta: blocked Anything that is blocked to the point where it cannot be worked on.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

4 participants