dd-apm

作者: datadog-labs

APM - 安裝、入門、儀器化、啟用、設定、配置、追蹤、服務、相依性、效能分析。用於任何涉及 Datadog APM 的請求…

npx skills add https://github.com/datadog-labs/agent-skills --skill dd-apm

Datadog APM

Distributed tracing, service maps, and performance analysis.

Routing — Read This First

Match the user's request to one of the entries below. Each entry has the same shape: triggers → which sub-skill to load → the anti-pattern to avoid. If a request seems to fit more than one entry, see "Overlap disambiguation". If nothing matches, see "None of the above" at the end.


Kubernetes APM install / instrument / onboard — trigger when the user mentions Kubernetes, K8s, EKS, GKE, AKS, kind, minikube, K3s, helm, DatadogAgent CR, kubectl, SSI on a cluster, pod injection, or init containers.

Immediately read .claude/skills/dd-apm/k8s-ssi/agent-install/SKILL.md now, then .claude/skills/dd-apm/k8s-ssi/enable-ssi/SKILL.md, then .claude/skills/dd-apm/k8s-ssi/verify-ssi/SKILL.md — do not proceed from memory.

Common wrong approaches that LOOK like they work but silently fail:

  • helm install datadog datadog/datadog — the standard chart does NOT support SSI via DatadogAgent CR.
  • Adding ddtrace imports or ddtrace-run to the app — SSI auto-instruments WITHOUT any code changes.
  • admission.datadoghq.com/enabled annotations — that's admission controller config injection, not SSI init container injection.

Linux APM install / instrument / onboard — trigger when the user mentions a single host, VM, EC2 instance, bare-metal, RHEL/Ubuntu/Debian, systemd, or no orchestrator.

Immediately read .claude/skills/dd-apm/linux-ssi/agent-install/SKILL.md now, then .claude/skills/dd-apm/linux-ssi/enable-ssi/SKILL.md, then .claude/skills/dd-apm/linux-ssi/verify-ssi/SKILL.md — do not proceed from memory.

Do NOT install the agent via plain apt-get install datadog-agent (or yum equivalent) and assume SSI follows — host auto-instrumentation requires the install script with the SSI flags, which the sub-skill walks through.


Service rename / service remapping — trigger when the user mentions renaming a service, collapsing multiple service names, stripping suffixes/prefixes, or cleaning up inferred services.

Immediately read .claude/skills/dd-apm/service-remapping/SKILL.md now — do not proceed from memory.

Do NOT change tags.datadoghq.com/service labels or DD_SERVICE env vars to rename a service in Datadog. That requires a rollout and only affects new data. Use a service remapping rule — it rewrites the name at ingestion time with no deployment change.


Overlap disambiguation

When a request could plausibly fit more than one entry above, use these tiebreakers:

HintRoute to
Cluster orchestrator mentioned (EKS/GKE/AKS/kind/K3s/minikube) — even if "just one node"k8s-ssi
Single host, VM, or EC2 with no orchestratorlinux-ssi
"Several services that should be one"service-remapping — the sub-skill picks the rule type based on whether the duplicates are real instrumented services or inferred entities (DBs, queues, external APIs)
"My service shows under the wrong name"First check DD_SERVICE on the deploy. If correct and the name is still wrong → service-remapping.
"Reduce APM volume / cost / noise"No sub-skill yet. Ask whether the user means sampling (fewer ingested traces) or retention filters (less indexed data) before suggesting commands.

None of the above

If the request doesn't match any entry above, continue reading the trace-search, service analysis, and metrics content below. If even that doesn't fit, ask the user to clarify — do not invent a workflow.


Requirements

Datadog Labs Pup should be installed. See Setup Pup if not.

Command Execution Order (Token-Efficient)

For scoped commands, use this order:

  1. Check context first (prior outputs, conversation, saved values).
  2. If a required value is missing, run a discovery command first.
  3. If still ambiguous, ask the user to confirm.
  4. Then run the target command.
  5. Avoid speculative commands likely to fail.

Quick Start

pup auth login
# Confirm env tag with the user first (do not assume production/prod/prd).
pup apm services list --env <env> --from 1h --to now
pup traces search --query "service:api-gateway" --from 1h

Services

List Services

pup apm services list --env <env> --from 1h --to now
pup apm services stats --env <env> --from 1h --to now

Service Stats

pup apm services stats --env <env> --from 1h --to now

Service Map

# View dependencies
pup apm flow-map --query "service:api-gateway&from=$(($(date +%s)-3600))000&to=$(date +%s)000" --env <env> --limit 10

Traces

Search Traces

# By service
pup traces search --query "service:api-gateway" --from 1h

# Errors only
pup traces search --query "service:api-gateway status:error" --from 1h

# Slow traces (>1s)
pup traces search --query "service:api-gateway @duration:>1000ms" --from 1h

# With specific tag
pup traces search --query "service:api-gateway @http.url:/api/users" --from 1h

Trace Detail

# No direct get command for a single trace ID.
# Use traces search with a narrow query and time window.
pup traces search --query "trace_id:<trace_id>" --from 1h

Key Metrics

MetricWhat It Measures
trace.http.request.hitsRequest count
trace.http.request.durationLatency
trace.http.request.errorsError count
trace.http.request.apdexUser satisfaction

Service Level Objectives

Link APM to SLOs:

pup slos create --file slo.json

Common Queries

GoalQuery
Slowest endpointsavg:trace.http.request.duration{*} by {resource_name}
Error ratesum:trace.http.request.errors{*} / sum:trace.http.request.hits{*}
Throughputsum:trace.http.request.hits{*}.as_rate()

Troubleshooting

ProblemFix
No tracesCheck ddtrace installed, DD_TRACE_ENABLED=true
Missing serviceVerify DD_SERVICE env var
Traces not linkedCheck trace headers propagated
High cardinalityDon't tag with user_id/request_id

References/Docs

來自 datadog-labs 的更多技能

dd-audit
datadog-labs
稽核軌跡調查——誰變更了什麼、金鑰遭入侵、成本飆升的根本原因、合規證據(SOC 2/PCI),以及AI活動稽核。
official
agent-install
datadog-labs
Install the Datadog Agent on Kubernetes using the Datadog Operator — required before enabling Single Step Instrumentation (SSI), which automatically…
official
agent-observability-auto-experiment
datadog-labs
針對真實的 Datadog LLM-Obs 資料執行迭代式程式碼改進爬山演算法,以 Claude Code 作為代理程式在本機端運行。建立基準評估,逐步進行…
official
agent-observability-eval-bootstrap
datadog-labs
Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts…
official
agent-observability-eval-pipeline
datadog-labs
為已儀器化的 ml_app 設計的端到端 Agent Observability 管線 — 分類生產追蹤、根因分析故障、啟動評估器,然後(可選地)…
official
agent-observability-experiment-analyzer
datadog-labs
分析LLM實驗結果。處理單一或對比實驗,探索性或問答模式。當使用者說「分析實驗」、「比較…」時使用。
official
agent-observability-replay-trace
datadog-labs
當開發者想要針對某一個特定的 Agent Observability / LLM Obs trace(其輸出結果不盡理想)進行迭代時使用——將該 trace 重新對其……
official
agent-observability-trace-rca
datadog-labs
Root cause analysis on production LLM traces. Diagnoses why an LLM application is failing — works from eval judge verdicts, runtime errors, or structural…
official