datadog-agent
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Update Workloadmeta ECS collector to use metadata v4 endpoint
What does this PR do?
This PR is based on
- https://github.com/DataDog/datadog-agent/pull/23248
- https://github.com/DataDog/datadog-agent/pull/23250
Related PR
- https://github.com/DataDog/datadog-agent/pull/23253
This PR is used by
- https://github.com/DataDog/datadog-agent/pull/22060
ECS Collector
- If
ecs_metadata_use_v4is true, the ECS agent V4 metadata endpoint will be queried for each task from the v1/tasks endpoint. - Due to the ECS agent metadata endpoint's default rate limit of 40,60 (source), a rate limiter is implemented to prevent throttling. https://github.com/DataDog/datadog-agent/blob/f67c3d667e00dcf6350a9d80a7075998e57ad9e3/comp/core/workloadmeta/collectors/internal/ecs/ecs.go#L86
- A task queue is introduced to manage the volume per pull, with a default maximum of 1000 tasks for querying the V4 metadata endpoint.
- Retry logic is in place for querying the V4 metadata endpoint, with three attempts and wait times of 250ms, 500ms, and 1000ms. https://github.com/DataDog/datadog-agent/blob/f67c3d667e00dcf6350a9d80a7075998e57ad9e3/comp/core/workloadmeta/collectors/internal/ecs/ecs.go#L330-L340
Motivation
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Reviewer's Checklist
- [x] If known, an appropriate milestone has been selected; otherwise the
Triagemilestone is set. - [ ] Use the
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. - [x] A release note has been added or the
changelog/no-changeloglabel has been applied. - [x] Changed code has automated tests for its functionality.
- [ ] Adequate QA/testing plan information is provided. Except if the
qa/skip-qalabel, with required eitherqa/doneorqa/no-code-changelabels, are applied. - [x] At least one
team/..label has been applied, indicating the team(s) that should QA this change. - [ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
- [ ] If applicable, the
need-change/operatorandneed-change/helmlabels have been applied. - [ ] If applicable, the
k8s/<min-version>label, indicating the lowest Kubernetes version compatible with this feature. - [ ] If applicable, the config template has been updated.
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: f3698333-5b33-4754-bdac-88bce0a5e340 Baseline: b4f0a172d309dc5b7689bc9674e0487e4fd0cf1b Comparison: 3caa3f280dab682ad77246406c45570e0e29284c
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
No significant changes in experiment optimization goals
Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%
There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
Experiments ignored for regressions
Regressions in experiments with settings containing erratic: true are ignored.
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_to_blackhole | % cpu utilization | +4.01 | [-2.51, +10.53] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_to_blackhole | % cpu utilization | +4.01 | [-2.51, +10.53] |
| ➖ | basic_py_check | % cpu utilization | +2.34 | [-0.07, +4.74] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.06, +0.06] |
| ➖ | trace_agent_msgpack | ingress throughput | +0.00 | [-0.00, +0.00] |
| ➖ | trace_agent_json | ingress throughput | -0.00 | [-0.01, +0.01] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.06, +0.06] |
| ➖ | file_tree | memory utilization | -0.31 | [-0.42, -0.21] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | -0.36 | [-0.39, -0.33] |
| ➖ | process_agent_standard_check | memory utilization | -0.62 | [-0.66, -0.59] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.64 | [-0.68, -0.61] |
| ➖ | idle | memory utilization | -0.79 | [-0.82, -0.76] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.27 | [-1.35, -1.20] |
| ➖ | pycheck_1000_100byte_tags | % cpu utilization | -1.30 | [-6.20, +3.60] |
| ➖ | otel_to_otel_logs | ingress throughput | -1.72 | [-2.37, -1.08] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -2.24 | [-4.95, +0.47] |
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.
-
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.
-
Its configuration does not mark it "erratic".
@kangyili, fantastic work 🎉
One thing I found reviewing all of the changes is that is quite difficult to be able to hold all of the changes in my head during the review. Not saying you have to, but if possible splitting the work into smaller PRs to make the process of reviewing them easier would be fantastic
@kangyili, fantastic work 🎉
One thing I found reviewing all of the changes is that is quite difficult to be able to hold all of the changes in my head during the review. Not saying you have to, but if possible splitting the work into smaller PRs to make the process of reviewing them easier would be fantastic
@GustavoCaso Thanks for the review! I've split this PR into two parts now. This current one includes only the changes made in Workloadmeta. The other PR is on the new check https://github.com/DataDog/datadog-agent/pull/22060
Test changes on VM
Use this command from test-infra-definitions to manually test this PR changes on a VM:
inv create-vm --pipeline-id=32185219 --os-family=ubuntu
Regression Detector
Regression Detector Results
Run ID: 172bb7cd-7395-4543-b28b-93b8f362f53e Baseline: 98de5502bfd1ba107861f3f3b46d858498561ece Comparison: 1421173b92cb1792dbe9b2bbee52317ee36fba19
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
No significant changes in experiment optimization goals
Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%
There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
Experiments ignored for regressions
Regressions in experiments with settings containing erratic: true are ignored.
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | file_to_blackhole | % cpu utilization | -2.02 | [-7.42, +3.37] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | basic_py_check | % cpu utilization | +3.61 | [+0.97, +6.25] |
| ➖ | file_tree | memory utilization | +1.61 | [+1.49, +1.72] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +0.76 | [-2.23, +3.74] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | +0.09 | [+0.04, +0.14] |
| ➖ | idle | memory utilization | +0.03 | [-0.01, +0.08] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.02 | [-0.18, +0.22] |
| ➖ | trace_agent_msgpack | ingress throughput | -0.00 | [-0.00, +0.00] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.01 | [-0.05, +0.04] |
| ➖ | process_agent_standard_check | memory utilization | -0.01 | [-0.06, +0.05] |
| ➖ | otel_to_otel_logs | ingress throughput | -0.02 | [-0.43, +0.39] |
| ➖ | trace_agent_json | ingress throughput | -0.03 | [-0.05, -0.01] |
| ➖ | pycheck_1000_100byte_tags | % cpu utilization | -0.37 | [-5.28, +4.53] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.48 | [-0.56, -0.40] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.73 | [-0.78, -0.68] |
| ➖ | file_to_blackhole | % cpu utilization | -2.02 | [-7.42, +3.37] |
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.
-
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.
-
Its configuration does not mark it "erratic".
Can you update QA information?
LGTM
/merge
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