onboarding-summary

Générer un rapport de confirmation d'intégration en direct pour l'instrumentation en une seule étape (SSI) — vérifie que l'instrumentation APM fonctionne de bout en bout avec des liens profonds vers le…

npx skills add https://github.com/datadog-labs/agent-skills --skill onboarding-summary

APM Onboarding Summary

Triggers

Invoke this skill when:

  • All steps in verify-ssi have passed
  • All checks in troubleshoot-ssi have been resolved
  • The user asks "is everything working?", "show me the status", or "confirm APM is set up"

Do NOT invoke this skill if any verification or troubleshooting check is still failing — resolve those first.


Context to resolve before acting

VariableHow to resolve
AGENT_NAMESPACENamespace where Datadog Agent is installed
APP_NAMESPACENamespace of the application
APP_LABELCheck spec.selector.matchLabels.app in the Deployment manifest
CLUSTER_NAMEspec.global.clusterName in datadog-agent.yaml
SERVICE_NAMEtags.datadoghq.com/service label on the Deployment
ENVtags.datadoghq.com/env label on the Deployment
DD_SITEspec.global.site in datadog-agent.yaml

Prerequisites

Claude runs

pup auth status --site <DD_SITE>

If valid token — proceed.

ERROR: Not authenticated:

Claude runs

pup auth login --site <DD_SITE>

This opens a browser tab for OAuth. Complete the login there — Claude will continue once the command exits.


Collect live confirmation data

Run all of the following. Each populates a row in the final report.

Claude runs

# Agent pod count and status
kubectl get pods -n <AGENT_NAMESPACE> \
  -l app.kubernetes.io/component=agent \
  --no-headers

# SSI instrumentation config live in cluster
kubectl get datadogagent datadog -n <AGENT_NAMESPACE> \
  -o jsonpath='{.spec.features.apm.instrumentation}'

# Init container confirmed in app pod spec
kubectl get pod -l app=<APP_LABEL> -n <APP_NAMESPACE> \
  -o jsonpath='{.items[0].spec.initContainers[*].name}'

# Service visible and traced in APM
DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 1h

# Traces arriving in the last hour
DD_SITE=<DD_SITE> pup traces search --query "service:<SERVICE_NAME>" --from 1h --limit 5

Present the report

Fill in every value from live command output. Do not leave any placeholder unfilled. If a value cannot be confirmed, mark that row as failed and link to troubleshoot-ssi.


APM onboarding complete

CheckDetailStatus
Datadog Agent<N> pod(s) Running in <AGENT_NAMESPACE>OK
SSI enabledTargeting namespace <APP_NAMESPACE>, language <LANGUAGE> v<MAJOR_VERSION>OK
Init container injecteddatadog-lib-<language>-init present in pod specOK
Tracer reportingService <SERVICE_NAME> appears in pup apm services list with isTraced: trueOK
APM service visible<SERVICE_NAME> in env <ENV>OK
Traces arriving<N> trace(s) found in the last hourOK

Your service in Datadog — click to open:

Construct each URL by substituting real values. Do not print placeholder URLs.

ViewURL
Service overviewhttps://app.<DD_SITE>/apm/services/<SERVICE_NAME>?env=<ENV>
Traces explorerhttps://app.<DD_SITE>/apm/traces?query=service:<SERVICE_NAME>%20env:<ENV>
Service maphttps://app.<DD_SITE>/apm/map?env=<ENV>&service=<SERVICE_NAME>
Agent fleethttps://app.<DD_SITE>/fleet-automation

Security constraints

  • Never write a raw API key into any file or chat message

Plus de skills de datadog-labs

dd-audit
datadog-labs
Investigations de piste d'audit - qui a modifié quoi, compromission de clé, cause racine de pic de coût, preuve de conformité (SOC 2/PCI), et audit d'activité IA.
official
agent-install
datadog-labs
Installez l'Agent Datadog sur Kubernetes à l'aide de l'Operator Datadog — requis avant d'activer Single Step Instrumentation (SSI), qui automatiquement…
official
agent-observability-auto-experiment
datadog-labs
Exécute une montée de colline itérative d'amélioration de code sur de vraies données Datadog LLM-Obs, localement, avec Claude Code comme agent. Établit une évaluation de référence, effectue une…
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
End-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap evaluators, then (optionally)…
official
agent-observability-experiment-analyzer
datadog-labs
Analyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare…
official
agent-observability-replay-trace
datadog-labs
Use when a developer wants to iterate on ONE specific Agent Observability / LLM Obs trace whose output they didn't like — re-running that trace against their…
official
agent-observability-trace-rca
datadog-labs
Analyse des causes racines sur les traces LLM en production. Diagnostique pourquoi une application LLM échoue — fonctionne à partir des verdicts des juges d'évaluation, des erreurs d'exécution ou des éléments structurels…
official