[CASCL-623] feat(cluster-agent): enhance DatadogPodAutoscaler metrics with dedicate metrics store#46833
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Go Package Import DifferencesBaseline: d75c25a
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Static quality checks✅ Please find below the results from static quality gates Successful checksInfo
30 successful checks with minimal change (< 2 KiB)
On-wire sizes (compressed)
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: d75c25a ❌ Experiments with retried target crashesThis is a critical error. One or more replicates failed with a non-zero exit code. These replicates may have been retried. See Replicate Execution Details for more information.
Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | +3.07 | [-0.05, +6.19] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | +3.07 | [-0.05, +6.19] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | +1.11 | [-0.37, +2.60] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_metrics_logs | memory utilization | +0.59 | [+0.37, +0.81] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_metrics | memory utilization | +0.54 | [+0.32, +0.75] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | +0.42 | [+0.35, +0.49] | 1 | Logs |
| ➖ | ddot_metrics_sum_delta | memory utilization | +0.34 | [+0.14, +0.53] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | +0.29 | [+0.13, +0.45] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | +0.13 | [+0.10, +0.16] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.05 | [-0.37, +0.46] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_v3 | ingress throughput | +0.02 | [-0.11, +0.15] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulative | memory utilization | +0.00 | [-0.16, +0.17] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.12, +0.12] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.00 | [-0.47, +0.47] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | -0.00 | [-0.04, +0.04] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.01 | [-0.10, +0.09] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.06 | [-0.44, +0.31] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.07 | [-0.11, -0.02] | 1 | Logs bounds checks dashboard |
| ➖ | file_tree | memory utilization | -0.13 | [-0.18, -0.07] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | -0.16 | [-0.22, -0.10] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulativetodelta_exporter | memory utilization | -0.21 | [-0.43, +0.02] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | -0.26 | [-0.31, -0.20] | 1 | Logs |
| ➖ | otlp_ingest_logs | memory utilization | -0.42 | [-0.51, -0.33] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -1.93 | [-2.02, -1.85] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency | 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_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 | bounds checks dashboard |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | 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:
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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".
Replicate Execution Details
We run multiple replicates for each experiment/variant. However, we allow replicates to be automatically retried if there are any failures, up to 8 times, at which point the replicate is marked dead and we are unable to run analysis for the entire experiment. We call each of these attempts at running replicates a replicate execution. This section lists all replicate executions that failed due to the target crashing or being oom killed.
Note: In the below tables we bucket failures by experiment, variant, and failure type. For each of these buckets we list out the replicate indexes that failed with an annotation signifying how many times said replicate failed with the given failure mode. In the below example the baseline variant of the experiment named experiment_with_failures had two replicates that failed by oom kills. Replicate 0, which failed 8 executions, and replicate 1 which failed 6 executions, all with the same failure mode.
| Experiment | Variant | Replicates | Failure | Logs | Debug Dashboard |
|---|---|---|---|---|---|
| experiment_with_failures | baseline | 0 (x8) 1 (x6) | Oom killed | Debug Dashboard |
The debug dashboard links will take you to a debugging dashboard specifically designed to investigate replicate execution failures.
❌ Retried Normal Replicate Execution Failures (non-profiling)
| Experiment | Variant | Replicates | Failure | Debug Dashboard |
|---|---|---|---|---|
| uds_dogstatsd_20mb_12k_contexts_20_senders | baseline | 1 | Failed to shutdown when requested | Debug Dashboard |
CI Pass/Fail Decision
✅ Passed. All Quality Gates 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_logs, bounds check memory_usage: 10/10 replicas passed. Gate 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_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check intake_connections: 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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HemeryJu
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I'm not fully familiar with the agent so you might want another review from someone else. But otherwise looks good :)
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Files inventory check summaryFile checks results against ancestor d75c25ac: Results for datadog-agent_7.78.0~devel.git.124.5d0021b.pipeline.99408206-1_amd64.deb:No change detected |
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… checks and tests
Improve the metrics generation and submission for DatadogPodAutoscaler:
* **Observer pattern enhancement**: Changed autoscaling.ObserverFunc signature
from func(string, string) to func(string, interface{}) to allow observers
direct access to stored objects without additional lookups
* **Centralized tag generation**: Refactored generator.go to use helper
functions (baseAutoscalerTags, autoscalerTagsWithSource,
autoscalerTagsWithContainer, conditionTags) making it easier to add or
modify tags across all metrics
* **Leader-only metric submission**: Added isLeader checks to
SenderMetricsWriter, horizontalController, and verticalController to
prevent non-leader instances from submitting duplicate metrics
* **Backward compatibility**: Retained isLeader:true tag on all metrics
via baseAutoscalerTags helper function
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Scope of This PR
This PR revisits the previous attempt:
#42547
The focus here is strictly on refactoring the existing metric generation logic, without introducing new metrics.
A follow-up PR will build on this foundation to introduce additional DPA metrics.
Motivation
Today,
DatadogPodAutoscaler(DPA) resource metrics are exposed as OpenMetrics/Prometheus metrics and scraped by thedatadog_cluster_agentcheck.While functional, this approach has several drawbacks:
pod_name,kube_namespace,kube_container_name, etc.).Proposed Approach
This PR changes how DPA metrics are generated.
Instead of exposing them via OpenMetrics and relying on the
datadog_cluster_agentcheck for collection, DPA metrics are now produced directly within the Cluster Agent autoscaling component — following the same pattern used forkubernetes_statemetrics.This provides:
Summary
Core changes
ObserverFuncsignature from(string, string)to(string, interface{})to pass the actual object to observers, enabling richer metric generationpkg/clusteragent/autoscaling/workload/metricspackage with aPodAutoscalerMetricsStorethat generates and periodically sends structured metrics (gauges/counts) forDatadogPodAutoscalerobjects viasender.Sendertelemetry.gotag-based metrics) with leader-aware metric submission; metrics are only emitted by the leaderAction metrics consolidation
Submit*functions incounters.gointo the state-basedGeneratePodAutoscalerMetricsgeneratorcounters.goentirely (SubmitReceivedRecommendationsVersionwas dead code; remainingSubmit*functions replaced by the generator)senderandisLeaderfromhorizontalControllerandverticalControllersince they were only used for the now-removedSubmit*callsMetrics emitted
received_recommendations_versionhorizontal_scaling_received_replicasvertical_scaling_received_requestsvertical_scaling_received_limitshorizontal_scaling_applied_replicashorizontal_scaling_actionsstatus:okorstatus:errorvertical_rollout_triggeredstatus:okorstatus:errorautoscaler_conditionslocal_fallback_enabledModel changes
mainScalingValuesVersion uint64toPodAutoscalerInternalto persist the remote config version of the last received main scaling valuesUpdateFromMainValuesto accept and persist the RC version;RemoveMainValuesresets it to 0horizontalActionErrorCount/horizontalActionSuccessCountandverticalActionErrorCount/verticalActionSuccessCountcounter fields, incremented on each action outcomeMainScalingValuesVersion(),HorizontalActionErrorCount(),HorizontalActionSuccessCount(),VerticalActionErrorCount(),VerticalActionSuccessCount()Test plan
metrics/store,metrics/generator, andmetrics/writergenerator_test.gocovers all 9 metrics including bothstatus:okandstatus:errorcount variantsconfig_retriever_values_test.goupdated with expectedMainScalingValuesVersionvaluescontroller_horizontal_test.goupdated to assertHorizontalActionSuccessCount/HorizontalActionErrorCountworkloadcontroller tests updated to remove now-deletedsender/isLeaderfixturespkg/clusteragent/autoscaling/...pass locally🤖 Generated with Claude Code