CI: DCA: use gitlab artifacts for the binaries instead of an S3 bucket #33698
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chouquette
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[Fast Unit Tests Report] On pipeline 54935124 (CI Visibility). The following jobs did not run any unit tests: Jobs:
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 |
Uncompressed package size comparisonComparison with ancestor Diff per package
Decision✅ Passed |
CelianR
approved these changes
Feb 4, 2025
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| - cp $CLUSTER_AGENT_BINARIES_DIR/datadog-cluster-agent $BUILD_CONTEXT/ | ||
| - cp -R $CWS_INSTRUMENTATION_BINARIES_DIR $BUILD_CONTEXT/ |
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Wouldn't it be better with mv? I'm not sure why cp is used and not mv but I may miss something (same for other jobs)
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I don't think it changes much since the repo will be cleaned right after the job, but it doesn't hurt to do so :)
chouetz
approved these changes
Feb 4, 2025
| @@ -5,7 +5,10 @@ | |||
| script: | |||
| - inv check-go-version | |||
| - inv -e cws-instrumentation.build | |||
| - $S3_CP_CMD $CI_PROJECT_DIR/$CWS_INSTRUMENTATION_BINARIES_DIR/cws-instrumentation $S3_ARTIFACTS_URI/datadog-cws-instrumentation/cws-instrumentation.$ARCH | |||
| - mv $CI_PROJECT_DIR/$CWS_INSTRUMENTATION_BINARIES_DIR/cws-instrumentation $CI_PROJECT_DIR/$CWS_INSTRUMENTATION_BINARIES_DIR/cws-instrumentation.$ARCH | |||
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This is strange to have such a mv command here, I suppose we could create the correct artefact from the invoke task directly (as a follow-up)
| variables: | ||
| IMAGE: registry.ddbuild.io/ci/datadog-agent/cws-instrumentation | ||
| BUILD_CONTEXT: Dockerfiles/cws-instrumentation | ||
| before_script: | ||
| - cp $CWS_INSTRUMENTATION_BINARIES_DIR/cws-instrumentation.amd64 $BUILD_CONTEXT/ |
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We could probably have $ARCH as variable like in the build jobs (even if such factorisation is not really great for readability here). As previously, this is a possible follow-up task
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turns out it was already defined so I included the change :) Thanks!
L3n41c
approved these changes
Feb 4, 2025
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 0ef59f7 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | quality_gate_logs | % cpu utilization | +2.79 | [-0.33, +5.91] | 1 | Logs |
| ➖ | file_tree | memory utilization | +0.41 | [+0.35, +0.48] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.31 | [-0.47, +1.09] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http1 | egress throughput | +0.05 | [-0.85, +0.95] | 1 | Logs |
| ➖ | file_to_blackhole_300ms_latency | egress throughput | +0.03 | [-0.60, +0.67] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.01, +0.02] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http2 | egress throughput | -0.00 | [-0.94, +0.94] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.00 | [-0.29, +0.28] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | -0.01 | [-0.71, +0.69] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | -0.03 | [-0.95, +0.89] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.09 | [-0.12, -0.05] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | -0.11 | [-0.57, +0.36] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.12 | [-0.90, +0.67] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.38 | [-0.44, -0.32] | 1 | Logs bounds checks dashboard |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -1.17 | [-2.05, -0.28] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.92 | [-1.97, -1.86] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | 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 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | |
| ✅ | quality_gate_logs | memory_usage | 10/10 |
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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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Its configuration does not mark it "erratic".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
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This build is now only based on gitlab artifacts
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Gitlab CI Configuration Changes
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| Removed | Modified | Added | Renamed |
|---|---|---|---|
| 0 | 10 | 0 | 0 |
ℹ️ Diff available in the job log.
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/merge |
Devflow running:
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Static quality checks ✅Please find below the results from static quality gates Info
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What does this PR do?
Stop manually uploading binaries to S3 and rely on gitlab artifacts
Motivation
Simplifying our pipelines & access control
Describe how you validated your changes
Possible Drawbacks / Trade-offs
Additional Notes