[Orchestrator] add new check to collect ecs tasks#22060
[Orchestrator] add new check to collect ecs tasks#22060dd-mergequeue[bot] merged 5 commits intomainfrom
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Bloop Bleep... Dogbot HereRegression Detector ResultsRun ID: d9233538-ba17-4993-bdc8-1153e942e6ee Performance changes are noted in the perf column of each table:
No significant changes in experiment optimization goalsConfidence level: 90.00% There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
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| perf | experiment | goal | Δ mean % | Δ mean % CI |
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| ➖ | file_to_blackhole | % cpu utilization | +0.02 | [-6.28, +6.32] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | otel_to_otel_logs | ingress throughput | +1.30 | [+0.64, +1.95] |
| ➖ | process_agent_standard_check | memory utilization | +0.63 | [+0.59, +0.67] |
| ➖ | idle | memory utilization | +0.38 | [+0.34, +0.43] |
| ➖ | file_to_blackhole | % cpu utilization | +0.02 | [-6.28, +6.32] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.02 | [-0.04, +0.07] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.06, +0.06] |
| ➖ | trace_agent_json | ingress throughput | +0.00 | [-0.01, +0.01] |
| ➖ | trace_agent_msgpack | ingress throughput | -0.02 | [-0.03, -0.01] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | -0.04 | [-0.09, -0.00] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.18 | [-2.98, +2.62] |
| ➖ | file_tree | memory utilization | -0.68 | [-0.78, -0.58] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.83 | [-0.87, -0.78] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.95 | [-1.03, -0.87] |
| ➖ | basic_py_check | % cpu utilization | -2.04 | [-4.28, +0.21] |
| ➖ | pycheck_1000_100byte_tags | % cpu utilization | -2.63 | [-7.52, +2.25] |
Explanation
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".
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release notes approved by docs
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LGTM for files owned by agent shared components
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I created a new PR only updates code structure #23823 |
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Test changes on VMUse this command from test-infra-definitions to manually test this PR changes on a VM: inv create-vm --pipeline-id=30572198 --os-family=ubuntu |
Regression DetectorRegression Detector ResultsRun ID: cf9295b8-f32c-4900-9c2c-31aeda2746e4 Performance changes are noted in the perf column of each table:
No significant changes in experiment optimization goalsConfidence level: 90.00% There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
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| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_to_blackhole | % cpu utilization | +1.32 | [-5.10, +7.75] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_to_blackhole | % cpu utilization | +1.32 | [-5.10, +7.75] |
| ➖ | idle | memory utilization | +0.29 | [+0.26, +0.32] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +0.15 | [+0.07, +0.23] |
| ➖ | otel_to_otel_logs | ingress throughput | +0.11 | [-0.31, +0.52] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | +0.06 | [+0.04, +0.09] |
| ➖ | trace_agent_msgpack | ingress throughput | +0.03 | [+0.01, +0.04] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.02 | [-0.02, +0.05] |
| ➖ | trace_agent_json | ingress throughput | +0.00 | [-0.03, +0.04] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.20, +0.20] |
| ➖ | pycheck_1000_100byte_tags | % cpu utilization | -0.07 | [-4.97, +4.83] |
| ➖ | file_tree | memory utilization | -0.24 | [-0.33, -0.16] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.59 | [-0.62, -0.56] |
| ➖ | process_agent_standard_check | memory utilization | -0.63 | [-0.67, -0.59] |
| ➖ | basic_py_check | % cpu utilization | -1.14 | [-3.62, +1.34] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -2.94 | [-5.60, -0.28] |
Explanation
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:
-
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".
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| taskModel.Tags = tags | ||
| taskModel.EcsTags = toTags(task.Task.Tags) |
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Is there any normalization needed for those tags?
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I'm not sure if we should do the normalisation here as the tag standard of ecs and datadog are different, changing tags can confuse user. We can probably leave it as it is for now
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…cs-new-core-check
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* add new check to collect ecs tasks * address feedback * bump agent payload version
What does this PR do?
This PR requires
New check
orchestrator_ecsorchestrator_ecsin core checks to collect running tasks from ecs-ec2 and ecs-fargate.DD_ORCHESTRATOR_EXPLORER_ENABLEDandDD_ORCHESTRATOR_EXPLORER_ECS_COLLECTION_ENABLEDWorkloadmetafor pulling tasks in every run https://github.com/DataDog/datadog-agent/blob/f67c3d667e00dcf6350a9d80a7075998e57ad9e3/pkg/collector/corechecks/cluster/orchestrator/collectors/ecs/task.go#L57Motivation
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Reviewer's Checklist
Triagemilestone is set.major_changelabel if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.changelog/no-changeloglabel has been applied.qa/skip-qalabel, with required eitherqa/doneorqa/no-code-changelabels, are applied.team/..label has been applied, indicating the team(s) that should QA this change.need-change/operatorandneed-change/helmlabels have been applied.k8s/<min-version>label, indicating the lowest Kubernetes version compatible with this feature.