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Main repository for Datadog Agent
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add otel agent integration test to gitlab ci #31452

Closed jackgopack4 closed 3 days ago

jackgopack4 commented 4 days ago

What does this PR do?

Adds the existing otel agent integration test to the gitlab pipeline

Motivation

This test is not run on CI, see https://github.com/DataDog/datadog-agent/pull/31437 where I set this test to assert 0=1 and all pipelines passed

Describe how to test/QA your changes

inv otel-agent.integration-test

Possible Drawbacks / Trade-offs

more overhead on pipelines

Additional Notes

Job passed on CI: https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/719768933

agent-platform-auto-pr[bot] commented 4 days ago

Gitlab CI Configuration Changes

Modified Jobs

integration_tests_otel ```diff integration_tests_otel: image: registry.ddbuild.io/ci/datadog-agent-buildimages/deb_x64$DATADOG_AGENT_BUILDIMAGES_SUFFIX:$DATADOG_AGENT_BUILDIMAGES needs: - go_deps rules: - if: $CI_PIPELINE_SOURCE =~ /^schedule.*$/ when: never - if: $CI_COMMIT_TAG when: never - if: $CI_COMMIT_MESSAGE =~ /.*\[skip cancel\].*/ when: never - if: $CI_COMMIT_REF_NAME =~ /.*-skip-cancel$/ when: never - when: always script: - mkdir -p $GOPATH/pkg/mod/cache && tar xJf modcache.tar.xz -C $GOPATH/pkg/mod/cache - rm -f modcache.tar.xz - inv check-otel-build - inv check-otel-module-versions + - inv otel-agent.integration-test stage: integration_test tags: - arch:amd64 ```

Changes Summary

Removed Modified Added Renamed
0 1 0 0

:information_source: Diff available in the job log.

jackgopack4 commented 3 days ago

how on earth this is a "medium review" smh

agent-platform-auto-pr[bot] commented 3 days ago

[Fast Unit Tests Report]

On pipeline 49910180 (CI Visibility). The following jobs did not run any unit tests:

Jobs: - tests_deb-arm64-py3 - tests_deb-x64-py3 - tests_flavor_dogstatsd_deb-x64 - tests_flavor_heroku_deb-x64 - tests_flavor_iot_deb-x64 - tests_rpm-arm64-py3 - tests_rpm-x64-py3 - tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-devx-help

cit-pr-commenter[bot] commented 3 days ago

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72

Baseline: 88703d8e3b462deac3f889d4e8efac46567d0e7e Comparison: d00be096b7359b83a4e9b26a95bf0b3a82db2d40 Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links | |------|----------------------------------------------|--------------------|----------|----------------|--------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | ➖ | pycheck_lots_of_tags | % cpu utilization | +2.75 | [-0.89, +6.39] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Apycheck_lots_of_tags%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | tcp_syslog_to_blackhole | ingress throughput | +1.52 | [+1.46, +1.59] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Atcp_syslog_to_blackhole%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_500ms_latency | egress throughput | +0.39 | [-0.37, +1.16] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_500ms_latency%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | quality_gate_idle | memory utilization | +0.35 | [+0.28, +0.42] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Aquality_gate_idle%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) [bounds checks dashboard](https://app.datadoghq.com/dashboard/vz3-jd5-bdi?fromUser=true&refresh_mode=paused&tpl_var_experiment%5B0%5D=quality_gate_idle&tpl_var_job_id%5B0%5D=92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&tpl_var_run-id%5B0%5D=92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&view=spans&from_ts=1732570804000&to_ts=1732571404000&live=false) | | ➖ | otel_to_otel_logs | ingress throughput | +0.11 | [-0.56, +0.78] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Aotel_to_otel_logs%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | +0.10 | [-0.36, +0.57] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_1000ms_latency_linear_load%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.05 | [-0.74, +0.84] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_1000ms_latency%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_300ms_latency | egress throughput | +0.05 | [-0.58, +0.68] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_300ms_latency%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.03 | [-0.70, +0.76] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_100ms_latency%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Atcp_dd_logs_filter_exclude%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | uds_dogstatsd_to_api | ingress throughput | -0.02 | [-0.14, +0.09] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Auds_dogstatsd_to_api%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_to_blackhole_0ms_latency | egress throughput | -0.19 | [-1.08, +0.71] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_to_blackhole_0ms_latency%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | file_tree | memory utilization | -0.33 | [-0.47, -0.20] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Afile_tree%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | quality_gate_idle_all_features | memory utilization | -0.36 | [-0.53, -0.20] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Aquality_gate_idle_all_features%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) [bounds checks dashboard](https://app.datadoghq.com/dashboard/vz3-jd5-bdi?fromUser=true&refresh_mode=paused&tpl_var_experiment%5B0%5D=quality_gate_idle_all_features&tpl_var_job_id%5B0%5D=92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&tpl_var_run-id%5B0%5D=92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&view=spans&from_ts=1732570804000&to_ts=1732571404000&live=false) | | ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.55 | [-1.28, +0.18] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Auds_dogstatsd_to_api_cpu%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) | | ➖ | basic_py_check | % cpu utilization | -1.38 | [-5.18, +2.42] | 1 | [Logs](https://app.datadoghq.com/logs?query=experiment%3Abasic_py_check%20run_id%3A92ab4c7a-09a0-49b2-92f0-6cc26a0fcb72&agg_m=count&agg_m_source=base&agg_q=%40span.url&agg_q_source=base&agg_t=count&fromUser=true&index=single-machine-performance-target-logs&messageDisplay=inline&refresh_mode=paused&storage=hot&stream_sort=time%2Cdesc&top_n=100&top_o=top&viz=stream&x_missing=true&from_ts=1732563604000&to_ts=1732575004000&live=false) |

Bounds Checks: ❌ Failed

perf experiment bounds_check_name replicates_passed links
❌ file_to_blackhole_500ms_latency lost_bytes 8/10
✅ file_to_blackhole_0ms_latency lost_bytes 10/10
✅ file_to_blackhole_0ms_latency memory_usage 10/10
✅ file_to_blackhole_1000ms_latency memory_usage 10/10
✅ file_to_blackhole_1000ms_latency_linear_load memory_usage 10/10
✅ file_to_blackhole_100ms_latency lost_bytes 10/10
✅ file_to_blackhole_100ms_latency memory_usage 10/10
✅ file_to_blackhole_300ms_latency lost_bytes 10/10
✅ file_to_blackhole_300ms_latency memory_usage 10/10
✅ file_to_blackhole_500ms_latency memory_usage 10/10
✅ quality_gate_idle memory_usage 10/10 bounds checks dashboard
✅ quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard

Explanation

**Confidence level:** 90.00% **Effect size tolerance:** |Δ mean %| ≥ 5.00% Performance changes are noted in the **perf** column of each table: * ✅ = significantly better comparison variant performance * ❌ = significantly worse comparison variant performance * ➖ = no significant change in performance A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI". For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true: 1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look. 2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that *if our statistical model is accurate*, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants. 3. Its configuration does not mark it "erratic".

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

jackgopack4 commented 3 days ago

/merge

dd-devflow[bot] commented 3 days ago

Devflow running: /merge

View all feedbacks in Devflow UI.

2024-11-26 18:44:39 UTC :information_source: MergeQueue: pull request added to the queue

The median merge time in main is 23m.