chore(ci): update Datadog Agent version to 7.82.0

[dd-octo-sts]

Summary

This PR updates the Datadog Agent version used for builds and testing to 7.82.0.

Details of change

• Current version: 7.81.3
• Updated version: 7.82.0
• Release: https://github.com/DataDog/datadog-agent/releases/tag/7.82.0

This PR was automatically generated by the Update Datadog Agent Version workflow.

Change Type

• Bug fix
• New feature
• Non-functional (chore, refactoring, docs)
• Performance

[chatgpt-codex-connector]

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[chatgpt-codex-connector]

Skip the known-bad Agent 7.82.0 pin

When these pins feed the converged/public Agent image, deploying it on multi-GPU Hopper/Blackwell hosts with GPU monitoring enabled can hit the upstream 7.82.0 known issue where GPU Monitoring can trigger a kernel panic; the 7.82.0 release notes recommend disabling gpu.parallel_collectors, staying on 7.81.3, or moving to 7.82.1 when available. Holding this repo at 7.81.3 or skipping to a fixed patch release avoids publishing/test-pinning a build with that host-crashing Agent defect.

Useful? React with 👍 / 👎.

[webern]

I don't think we depend on gpu monitoring for any of our testing workflows, CI passed, and we don't exactly incorporate Agent behavior into our ADP product, so this seems fine to me.

[datadog-datadog-prod-us1-2]

More details

The 7.82.0 pin activates the intended 7.82 OTLP scope-metadata boundary while keeping Linux, Windows, macOS, and Antithesis references aligned with the Agent’s image and package naming conventions.

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_{📊 Validated against 7 scenarios · Open Bits AI session}

_{🤖 Datadog Autotest · Commit 3522e90 · What is Autotest? · @DataDog review to ask questions · Any feedback? Reach out in #autotest}

[pr-commenter]

Binary Size Analysis (Agent Data Plane)

Baseline: e497e8d · Comparison: 3522e90 · diff
Analysis Configuration: stripped binaries · Pass/Fail Threshold: +5%
Sizes: 41.64 MiB (baseline) vs 41.64 MiB (comparison)
Size Change: +0 B (+0.00%)

✅ Binary size difference within threshold

Changes by Module

Module	File Size	Symbols
anon.44a0faa3240fa409baa379409d152aec.1.llvm.3197582161353810168	+129 B	1
anon.44a0faa3240fa409baa379409d152aec.1.llvm.7688587471901361655	-129 B	1
anon.44a0faa3240fa409baa379409d152aec.4.llvm.3197582161353810168	+113 B	1
anon.44a0faa3240fa409baa379409d152aec.4.llvm.7688587471901361655	-113 B	1
anon.44a0faa3240fa409baa379409d152aec.3.llvm.3197582161353810168	+108 B	1
anon.44a0faa3240fa409baa379409d152aec.3.llvm.7688587471901361655	-108 B	1
anon.44a0faa3240fa409baa379409d152aec.0.llvm.3197582161353810168	+96 B	1
anon.44a0faa3240fa409baa379409d152aec.0.llvm.7688587471901361655	-96 B	1
anon.44a0faa3240fa409baa379409d152aec.2.llvm.3197582161353810168	+94 B	1
anon.44a0faa3240fa409baa379409d152aec.2.llvm.7688587471901361655	-94 B	1

Detailed Symbol Changes

    FILE SIZE        VM SIZE    
 --------------  -------------- 
  [NEW]    +129  [NEW]     +40    anon.44a0faa3240fa409baa379409d152aec.1.llvm.3197582161353810168
  [NEW]    +113  [NEW]     +24    anon.44a0faa3240fa409baa379409d152aec.4.llvm.3197582161353810168
  [NEW]    +108  [NEW]     +19    anon.44a0faa3240fa409baa379409d152aec.3.llvm.3197582161353810168
  [NEW]     +96  [NEW]      +7    anon.44a0faa3240fa409baa379409d152aec.0.llvm.3197582161353810168
  [NEW]     +94  [NEW]      +5    anon.44a0faa3240fa409baa379409d152aec.2.llvm.3197582161353810168
  [DEL]     -94  [DEL]      -5    anon.44a0faa3240fa409baa379409d152aec.2.llvm.7688587471901361655
  [DEL]     -96  [DEL]      -7    anon.44a0faa3240fa409baa379409d152aec.0.llvm.7688587471901361655
  [DEL]    -108  [DEL]     -19    anon.44a0faa3240fa409baa379409d152aec.3.llvm.7688587471901361655
  [DEL]    -113  [DEL]     -24    anon.44a0faa3240fa409baa379409d152aec.4.llvm.7688587471901361655
  [DEL]    -129  [DEL]     -40    anon.44a0faa3240fa409baa379409d152aec.1.llvm.7688587471901361655
  [ = ]       0  [ = ]       0    TOTAL

[pr-commenter]

Regression Detector (Agent Data Plane)

Run ID: 1e876c47-1dfb-45da-bda8-489703332747
Baseline: e497e8df · Comparison: 3522e900 · diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment (5)

Experiments configured erratic: true are tagged (ignored) and skipped when determining which experiments regressed or improved. Experiments which are detected as erratic at runtime are tagged (erratic) to flag that the run's sample dispersion was high, but their regression / improvement signal still counts.

experiment	goal	Δ mean %	links
quality_gates_rss_dsd_ultraheavy	memory	⚪ +0.85	metrics profiles logs
quality_gates_rss_dsd_medium	memory	⚪ +0.36	metrics profiles logs
quality_gates_rss_dsd_low	memory	⚪ +0.03	metrics profiles logs
quality_gates_rss_dsd_heavy	memory	⚪ -0.00	metrics profiles logs
quality_gates_rss_idle	memory	⚪ -0.37	metrics profiles logs

Bounds Checks: ✅ Passed (5)

experiment	check	replicates	observed	links
quality_gates_rss_dsd_heavy	memory_usage	10/10	✅ 230 MiB ≤ 250 MiB	metrics profiles logs
quality_gates_rss_dsd_low	memory_usage	10/10	✅ 51.4 MiB ≤ 60 MiB	metrics profiles logs
quality_gates_rss_dsd_medium	memory_usage	10/10	✅ 90.2 MiB ≤ 100 MiB	metrics profiles logs
quality_gates_rss_dsd_ultraheavy	memory_usage	10/10	✅ 401 MiB ≤ 420 MiB	metrics profiles logs
quality_gates_rss_idle	memory_usage	10/10	✅ 32.1 MiB ≤ 40 MiB	metrics profiles logs

Explanation

A change is flagged as a regression when |Δ mean %| > 5.00% in the regressing direction for its optimization goal AND SMP marks the experiment as a regression (is_regression: true). Improvements use the matching criteria for the improving direction. Experiments configured erratic: true (tagged (ignored)) are skipped outright; experiments detected as erratic at runtime (tagged (erratic)) still count, since that flag describes sample dispersion rather than directional certainty. The Δ mean % cell is colored accordingly: 🟢 = improvement, 🔴 = regression, ⚪ = neutral. Reduction in CPU or memory is an improvement; reduction in ingress throughput is a regression.

[webern]

I don't think we depend on gpu monitoring for any of our testing workflows, CI passed, and we don't exactly incorporate Agent behavior into our ADP product, so this seems fine to me.