AMLII-440 Add command to show top dogstatsd contexts #20548
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Different from dogstatsd-stats, this shows the state of the aggregator, rather than the incoming traffic and thus more useful when troubleshooting memory usage. As this is mostly interesting when free memory is low and number of contexts is high, write the data into a file rather than passing it in the api response directly. The file can be removed from the system under pressure and analyzed on a different host even if the pod crashes.
vickenty
changed the title
Go Package Import DifferencesBaseline: 9ff294d
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Bloop Bleep... Dogbot HereRegression Detector ResultsRun ID: 007ab765-2e39-41f4-b2bb-a4c9a4aa04bd ExplanationA regression test is an integrated performance test for 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:
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.
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Co-authored-by: Pierre Gimalac <[email protected]>
What does this PR do?
Add a new command to show current contexts tracked by the dogstatsd aggregator.
Motivation
Help troubleshooting high memory usage by the agent.
Additional Notes
Different from the
dogstatsd-statscommand, this shows the state of the aggregator, rather than the incoming traffic and thus more useful when troubleshooting memory usage.As this is mostly interesting when free memory is low and number of contexts is high, write the data into a file rather than passing potentially large amount of data in the api response directly. The file can be removed from the system under pressure and analyzed on a different host even if the pod crashes.
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Run the agent and send some dogstatsd traffic to it.
Run
agent dogstatsd topand make sure the output matches supplied traffic.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 is not 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.