[anomalydetection] Simplify reporters (5) by CelianR · Pull Request #52493 · DataDog/datadog-agent

CelianR · 2026-06-19T14:02:41Z

What does this PR do?

This moves deduplication and recurrence logic out of reporters into correlators.
Correlators now directly output events to send which is more convenient for the scorer (events like "high severity", "no more high severity")

We now have 3 types of alerts: entering high severity, leaving high severity and correlation events (new correlation / reoccurrence which is the previous type).

It basically adds a PendingEvents function to correlator to replace ActiveCorrelations (these are processed by the emitter new component).

Motivation

Describe how you validated your changes

Additional Notes

datadog-datadog-prod-us1 · 2026-06-19T14:02:53Z

🎯 Code Coverage (details)
• Patch Coverage: 40.68%
• Overall Coverage: 51.01% (-0.02%)

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: 6b83932 | Docs | Datadog PR Page | Give us feedback!}

dd-octo-sts · 2026-06-19T14:39:42Z

Files inventory check summary

File checks results against ancestor f91bb03e:

Results for datadog-agent_7.82.0~devel.git.389.6b83932.pipeline.121254224-1_amd64.deb:

No change detected

cit-pr-commenter-54b7da · 2026-06-19T15:00:14Z

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 480c61b5-6683-42ec-bcd3-16d01ae75bda

Baseline: eeaa480
Comparison: d5827b8
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_metrics_logs	memory utilization	+1.26	[+1.00, +1.51]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	+0.55	[+0.51, +0.59]	1	Logs bounds checks dashboard
➖	quality_gate_security_idle	memory utilization	+0.40	[+0.34, +0.46]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	+0.26	[+0.21, +0.32]	1	Logs bounds checks dashboard
➖	quality_gate_security_mean_fs_load	memory utilization	+0.09	[+0.05, +0.13]	1	Logs bounds checks dashboard
➖	quality_gate_security_no_fs_load	memory utilization	-0.13	[-0.22, -0.04]	1	Logs bounds checks dashboard
➖	quality_gate_logs	% cpu utilization	-0.42	[-1.52, +0.67]	1	Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	quality_gate_idle	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	146.66MiB ≤ 154MiB	bounds checks dashboard
✅	quality_gate_idle	total_bytes_received	10/10	577.05KiB ≤ 819.20KiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	488.28MiB ≤ 495MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	total_bytes_received	10/10	0.89MiB ≤ 1.25MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	182.31MiB ≤ 195MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_logs	total_bytes_received	10/10	264.20MiB ≤ 292MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	342.65 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	390.59MiB ≤ 430MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	total_bytes_received	10/10	0.86GiB ≤ 1.04GiB	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	28.57 ≤ 40	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	297.98MiB ≤ 330MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	61.04 ≤ 80	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	276.29MiB ≤ 310MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	22.18 ≤ 40	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	285.74MiB ≤ 320MiB	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:

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".

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 Profiling Replicate Execution Failures (ddprof)

Note: Profiling replicas may still be executing. See the debug dashboard for up to date status.

Experiment	Variant	Replicates	Failure	Debug Dashboard
quality_gate_idle_all_features	baseline	10	Oom killed	Debug Dashboard
quality_gate_idle_all_features	comparison	10	Oom killed	Debug Dashboard
quality_gate_logs	comparison	10	Oom killed	Debug Dashboard
quality_gate_metrics_logs	baseline	10	Oom killed	Debug Dashboard
quality_gate_metrics_logs	comparison	10	Oom killed	Debug Dashboard
quality_gate_security_no_fs_load	baseline	10	Oom killed	Debug Dashboard
quality_gate_security_no_fs_load	comparison	10	Oom killed	Debug Dashboard

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

quality_gate_logs, bounds check missed_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_logs, bounds check total_bytes_received: 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 missed_bytes: 10/10 replicas passed. Gate passed.
quality_gate_metrics_logs, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
quality_gate_metrics_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_security_no_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_no_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
quality_gate_idle_all_features, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_idle, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.
quality_gate_idle, 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_security_mean_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_mean_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_idle, bounds check cpu_usage: 10/10 replicas passed. Gate passed.

dd-octo-sts · 2026-06-19T15:44:29Z

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor f91bb03
📊 Static Quality Gates Dashboard
🔗 SQG Job

Successful checks

Info

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	+19.34 KiB (0.00% increase, -0.18% of buffer)	747.881 → 747.899 → 758.200
✅	agent_deb_amd64_fips	+19.34 KiB (0.00% increase, -0.31% of buffer)	703.819 → 703.838 → 709.840
✅	agent_heroku_amd64	+16.0 KiB (0.01% increase, -0.24% of buffer)	308.670 → 308.685 → 315.230
✅	agent_rpm_amd64	+19.34 KiB (0.00% increase, -0.18% of buffer)	747.864 → 747.883 → 758.170
✅	agent_rpm_amd64_fips	+19.34 KiB (0.00% increase, -0.31% of buffer)	703.803 → 703.822 → 709.840
✅	agent_rpm_arm64	+16.29 KiB (0.00% increase, -0.25% of buffer)	723.392 → 723.408 → 729.660
✅	agent_rpm_arm64_fips	+16.29 KiB (0.00% increase, -0.27% of buffer)	682.945 → 682.961 → 688.860
✅	agent_suse_amd64	+19.34 KiB (0.00% increase, -0.18% of buffer)	747.864 → 747.883 → 758.170
✅	agent_suse_amd64_fips	+19.34 KiB (0.00% increase, -0.31% of buffer)	703.803 → 703.822 → 709.840
✅	agent_suse_arm64	+16.29 KiB (0.00% increase, -0.25% of buffer)	723.392 → 723.408 → 729.660
✅	agent_suse_arm64_fips	+16.29 KiB (0.00% increase, -0.27% of buffer)	682.945 → 682.961 → 688.860
✅	docker_agent_amd64	+19.34 KiB (0.00% increase, -0.27% of buffer)	806.699 → 806.718 → 813.790
✅	docker_agent_arm64	+16.29 KiB (0.00% increase, -0.20% of buffer)	807.245 → 807.261 → 815.030
✅	docker_agent_jmx_amd64	+19.35 KiB (0.00% increase, -0.27% of buffer)	997.596 → 997.615 → 1004.550
✅	docker_agent_jmx_arm64	+16.29 KiB (0.00% increase, -0.20% of buffer)	986.796 → 986.812 → 994.710
✅	iot_agent_deb_arm64	+4.0 KiB (0.01% increase, -0.30% of buffer)	42.406 → 42.410 → 43.720

16 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	docker_cluster_agent_amd64	208.155 MiB
✅	docker_cluster_agent_arm64	221.377 MiB
✅	docker_cws_instrumentation_amd64	7.447 MiB
✅	docker_cws_instrumentation_arm64	6.877 MiB
✅	docker_dogstatsd_amd64	39.028 MiB
✅	docker_dogstatsd_arm64	37.180 MiB
✅	docker_host_profiler_amd64	305.034 MiB
✅	docker_host_profiler_arm64	316.119 MiB
✅	dogstatsd_deb_amd64	29.763 MiB
✅	dogstatsd_deb_arm64	27.818 MiB
✅	dogstatsd_rpm_amd64	29.763 MiB
✅	dogstatsd_suse_amd64	29.763 MiB
✅	iot_agent_deb_amd64	45.691 MiB
✅	iot_agent_deb_armhf	43.195 MiB
✅	iot_agent_rpm_amd64	45.692 MiB
✅	iot_agent_suse_amd64	45.691 MiB

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Eokye

looks good! some comments probably have to be updated along with the one i pointed out. i like the new dedup logic! it avoids needing a TTL and other complexities

### What does this PR do? Unifies the anomaly scorer into a single `anomalyScorer` struct implementing the `Correlator` interface in a single file. We can now benchmark the scorer. This removes the helper reporting logs, it's merged into this struct. This contains the main score logic and also the subscribe logic which is used to create events (high severity = event). > [!NOTE] > We use "the severity becomes high" and "the severity isn't high anymore" as start / end of correlation. This will be reworked in #52493 to directly emit event at the start. The config can now enable/disable logs and reporter events (telemetry always enabled if component enabled). New config keys for output: ```yaml anomaly_detection: anomaly_scorer: enabled: true output: logs: true correlation_events: false ``` #### Diagram ```mermaid flowchart LR IN["ProcessAnomaly(a)"] --> PEND["pending map"] PEND --> ADV subgraph ADV["Advance(t) — mu held"] EWMA["merge → evict → bucket → EWMA"] end ADV -->|"[]secEWMA\nmu released"| SUBS subgraph SUBS["Per-subscription state machines — subsMu"] FSM["Low / Medium / High FSM\n+ cooldown per sub"] FSM -->|"transition"| CB["Listener.OnSeverityTransition(evt)"] end CB -->|"self-sub\n(internal watcher)"| IW["gauges · logs · episode tracking"] IW --> AC["ActiveCorrelations()"] ADV --> SC["ScoreState() / LastScore()"] SUBS --> SB["Subscribe(cfg) → func()\nexposes via SubscribeScorer on Component"] ``` ### Motivation Nice score for kafka scenario, no false positives (using bocpd+tukey_biweight+holt_residual): <img width="531" height="304" alt="Screenshot 2026-06-19 at 11 20 44" src="https://github.com/user-attachments/assets/ace05855-359a-4064-b42c-994b6baf5a1e" /> ### Describe how you validated your changes ### Additional Notes Co-authored-by: celian.raimbault <celian.raimbault@datadoghq.com>

…rs, clean up reporters Move per-pattern deduplication and CorrelationDetected emission out of the reporter layer and into a per-correlator correlationEmitter helper. Reporters become stateless forwarders of typed CorrelatorEvents. Key changes: - Add correlationEmitter helper (Observe/Drain/Reset) tracking first-seen and recurrence per pattern; embed in TimeClusterCorrelator and CrossSignalCorrelator - Add CorrelatorEvent / CorrelatorEventKind to observer/def types: CorrelationDetected, EpisodeStarted, EpisodeEnded - anomalyScorer: remove closedEpisodes buffer; accumulate episode lifecycle events via PendingEvents() drained each engine advance cycle - engine: drain PendingEvents() from all correlators and include in ReportOutput as CorrelatorEvents; guard accumulation behind TrackCorrelationHistory flag - reporter/def: ReportOutput.CorrelatorEvents replaces CorrelationHistory - EventReporter: stateless forwarder; CorrelationDetected send failures buffered in retryPending (max 5 attempts) for next-cycle retry; episode events at-most-once - stdoutReporter: emittedCounter counts only CorrelationDetected events; ongoingCounter fires only for active patterns not newly detected this cycle - observer/impl/BUILD.bazel: add correlation_emitter.go and _test.go - AGENTS.md files and reporter.allium spec updated to reflect new model Co-authored-by: Cursor <cursoragent@cursor.com>

…AGENTS.md Co-authored-by: Cursor <cursoragent@cursor.com>

CelianR added changelog/no-changelog No changelog entry needed qa/done QA done before merge and regressions are covered by tests labels Jun 19, 2026

CelianR self-assigned this Jun 19, 2026

CelianR changed the title ~~refactor(anomaly_detection): move correlation emission into correlators, clean reporters~~ [anomalydetection] Simplify reporters Jun 19, 2026

CelianR force-pushed the celian/anomalyscorer-unify branch from 583c73d to a483af0 Compare June 22, 2026 08:16

CelianR mentioned this pull request Jun 22, 2026

[anomalydetection] Unify scorer, make it a correlator (4) #52492

Merged

CelianR changed the title ~~[anomalydetection] Simplify reporters~~ [anomalydetection] Simplify reporters (5) Jun 22, 2026

CelianR force-pushed the celian/refactor-correlators-reporters branch from df92d4b to 1213d9c Compare June 22, 2026 12:44

CelianR requested a review from Eokye June 22, 2026 12:53

CelianR marked this pull request as ready for review June 22, 2026 12:54

CelianR requested review from a team as code owners June 22, 2026 12:54

chatgpt-codex-connector Bot reviewed Jun 22, 2026

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Comment thread comp/anomalydetection/reporter/impl/reporter_event.go

github-actions Bot added the long review PR is complex, plan time to review it label Jun 22, 2026

JSGette approved these changes Jun 23, 2026

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Eokye approved these changes Jun 23, 2026

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Comment thread comp/anomalydetection/AGENTS.md Outdated

CelianR force-pushed the celian/anomalyscorer-unify branch from ccff034 to 05960f3 Compare June 26, 2026 07:24

CelianR requested review from a team as code owners June 26, 2026 07:24

CelianR requested a review from dustmop June 26, 2026 07:24

CelianR force-pushed the celian/anomalyscorer-unify branch from 05960f3 to 448d6d3 Compare June 26, 2026 08:08

CelianR force-pushed the celian/refactor-correlators-reporters branch from a6b3350 to 8fe503f Compare June 26, 2026 08:15

Base automatically changed from celian/anomalyscorer-unify to main June 26, 2026 10:35

CelianR and others added 2 commits June 26, 2026 13:20

docs(anomaly_detection): clarify EventReporter retryPending state in …

6b83932

…AGENTS.md Co-authored-by: Cursor <cursoragent@cursor.com>

CelianR force-pushed the celian/refactor-correlators-reporters branch from b23788e to 6b83932 Compare June 26, 2026 11:20

dd-octo-sts Bot added internal Identify a non-fork PR team/agent-build labels Jun 26, 2026

CelianR removed request for a team June 26, 2026 11:55

gh-worker-dd-mergequeue-cf854d Bot merged commit d5827b8 into main Jun 26, 2026
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gh-worker-dd-mergequeue-cf854d Bot deleted the celian/refactor-correlators-reporters branch June 26, 2026 13:18

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[anomalydetection] Simplify reporters (5)#52493

[anomalydetection] Simplify reporters (5)#52493
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Fine details of change detection per experiment

Bounds Checks: ✅ Passed

Explanation

Replicate Execution Details

❌ Retried Profiling Replicate Execution Failures (ddprof)

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What does this PR do?

Motivation

Describe how you validated your changes

Additional Notes

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Files inventory check summary

Results for datadog-agent_7.82.0~devel.git.389.6b83932.pipeline.121254224-1_amd64.deb:

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Regression Detector

Regression Detector Results

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

Bounds Checks: ✅ Passed

Explanation

Replicate Execution Details

❌ Retried Profiling Replicate Execution Failures (ddprof)

CI Pass/Fail Decision

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Static quality checks

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CelianR commented Jun 19, 2026 •

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