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verify-ssi
Verify Single Step Instrumentation (SSI) is working end-to-end on Kubernetes — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run.
Übersicht
Verify Single Step Instrumentation (SSI) is working end-to-end on Kubernetes — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run.
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Verify APM SSI on Linux
Before doing anything else: Fully resolve all variables in
## Context to resolve before acting. Do not begin Step 1 until every variable has a concrete value.
Triggers
Invoke this skill when the user expresses intent to:
- Confirm SSI is working after installing the Datadog Agent on Linux
- Check whether a Linux process is being instrumented
- Verify the tracer is running and reporting telemetry
Do NOT invoke this skill if:
- SSI has not been enabled yet — run
agent-installfirst - Services have not been restarted since the agent was installed — restart them first, then verify
Prerequisites
-
agent-installis complete - Application services have been restarted since the agent was installed
pup-cli: check, install, and authenticate
Claude runs
pup --version
If not found:
Claude runs
brew tap datadog-labs/pack
brew install pup
Check auth:
pup auth status --site <DD_SITE>
If 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.
If valid token — proceed.
ERROR: No browser available: export DD_APP_KEY=<your-app-key>
Context to resolve before acting
| Variable | How to resolve |
|---|---|
DD_HOSTNAME | Hostname as Datadog sees it — from sudo datadog-agent status output |
SERVICE_NAME | Expected service name in APM — ask the user |
ENV | Environment tag — ask the user |
DD_SITE | grep "^site:" /etc/datadog-agent/datadog.yaml via SSH, or ask the user |
SSH_KEY | Path to SSH private key |
SSH_USER | SSH username |
SSH_HOST | Hostname or IP of the target host |
Step 1: Confirm the Process is Injected
Use /proc/<pid>/maps — this is the authoritative check. It shows the actual shared libraries loaded into the running process, which is the only way to confirm the launcher and tracer .so files were actually loaded.
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"pgrep -a -f '<SERVICE_NAME>' | head -5"
Use the PID from above:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo cat /proc/<PID>/maps | grep -E 'launcher|apm-library|datadog'"
If the output includes both the launcher (e.g. launcher.preload.so) and a language library (e.g. apm-library-python) — injection succeeded for this process.
ERROR: Launcher present but no language library — launcher ran but couldn't inject. Check for injection errors:
Claude runs
pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h
ERROR: Neither present — process was not injected. Check /etc/ld.so.preload:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> "cat /etc/ld.so.preload"
If empty — install did not set up the launcher. Re-run the install script with DD_APM_INSTRUMENTATION_ENABLED=host. If non-empty but the process still isn't injected — the process was started before the launcher was installed. Restart the service and recheck.
Step 2: Confirm the Agent is Receiving Traces
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo datadog-agent status 2>&1 | grep -A 15 'APM Agent'"
Healthy output shows:
feature_auto_instrumentation_enabled: trueReceiver (previous minute)with> 0traces
ERROR: feature_auto_instrumentation_enabled: false — SSI not active on the agent. Check apm_config in /etc/datadog-agent/datadog.yaml.
ERROR: Receiver (previous minute): 0 — agent running but no traces yet. Generate traffic first (see Step 3), then recheck.
Step 3: Confirm the Service is Visible in Datadog
Claude runs
DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 1h
If <SERVICE_NAME> appears with isTraced: true — traces are reaching the Datadog backend.
Flask / ddtrace v3 naming note: With ddtrace >=3.x, Flask spans are emitted as
service:flaskrather thanservice:<DD_SERVICE>. TheDD_SERVICEvalue appears asbase_serviceon the spans. If you setDD_SERVICE=my-app, search forservice:flaskin the APM UI — the service list will showflask, notmy-app. Check thebase_servicetag to confirm it matches yourDD_SERVICE.
ERROR: Service missing — generate traffic to trigger trace creation:
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo ss -tlnp 2>/dev/null | grep <PID> || sudo netstat -tlnp 2>/dev/null | grep <PID>"
Use the port from above:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"for i in \$(seq 1 10); do curl -s -o /dev/null http://localhost:<PORT>/; done"
Wait 30 seconds, then retry:
DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 10m
DD_SITE=<DD_SITE> pup traces search --query "service:<SERVICE_NAME>" --from 10m --limit 5
ERROR: Still missing — check for injection errors and go to troubleshoot-ssi:
pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h
Done
Exit when ALL of the following are true:
- Step 1: launcher + language library both visible in
/proc/<PID>/maps - Step 2: agent APM receiver shows
> 0traces/min - Step 3: service appears in
pup apm services list
If any check fails, go to troubleshoot-ssi.
When all steps pass, automatically proceed to onboarding-summary now — do not ask the user for permission.
Security constraints
- Never write a raw API key into any file or chat message
- Always confirm before restarting production services
Dateimetadaten
name: verify-ssi description: Verify Single Step Instrumentation (SSI) is working end-to-end on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run. metadata: version: "1.0.0" author: datadog-labs repository: https://github.com/datadog-labs/agent-skills tags: datadog,apm,linux,ssi,verification,instrumentation,ld-preload alwaysApply: "false"
Originaltext anzeigen
--- name: verify-ssi description: Verify Single Step Instrumentation (SSI) is working end-to-end on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run. metadata: version: "1.0.0" author: datadog-labs repository: https://github.com/datadog-labs/agent-skills tags: datadog,apm,linux,ssi,verification,instrumentation,ld-preload alwaysApply: "false" --- # Verify APM SSI on Linux > **Before doing anything else:** Fully resolve all variables in `## Context to resolve before acting`. Do not begin Step 1 until every variable has a concrete value. ## Triggers Invoke this skill when the user expresses intent to: - Confirm SSI is working after installing the Datadog Agent on Linux - Check whether a Linux process is being instrumented - Verify the tracer is running and reporting telemetry Do NOT invoke this skill if: - SSI has not been enabled yet — run `agent-install` first - Services have not been restarted since the agent was installed — restart them first, then verify --- ## Prerequisites - [ ] `agent-install` is complete - [ ] Application services have been restarted since the agent was installed ### pup-cli: check, install, and authenticate ### Claude runs ```bash pup --version ``` If not found: ### Claude runs ```bash brew tap datadog-labs/pack brew install pup ``` Check auth: ```bash pup auth status --site <DD_SITE> ``` If not authenticated: ### Claude runs ```bash pup auth login --site <DD_SITE> ``` > This opens a browser tab for OAuth. Complete the login there — Claude will continue once the command exits. If valid token — proceed. ERROR: No browser available: `export DD_APP_KEY=<your-app-key>` --- ## Context to resolve before acting | Variable | How to resolve | |---|---| | `DD_HOSTNAME` | Hostname as Datadog sees it — from `sudo datadog-agent status` output | | `SERVICE_NAME` | Expected service name in APM — ask the user | | `ENV` | Environment tag — ask the user | | `DD_SITE` | `grep "^site:" /etc/datadog-agent/datadog.yaml` via SSH, or ask the user | | `SSH_KEY` | Path to SSH private key | | `SSH_USER` | SSH username | | `SSH_HOST` | Hostname or IP of the target host | --- ## Step 1: Confirm the Process is Injected Use `/proc/<pid>/maps` — this is the authoritative check. It shows the actual shared libraries loaded into the running process, which is the only way to confirm the launcher and tracer `.so` files were actually loaded. ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "pgrep -a -f '<SERVICE_NAME>' | head -5" ``` Use the PID from above: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo cat /proc/<PID>/maps | grep -E 'launcher|apm-library|datadog'" ``` If the output includes both the launcher (e.g. `launcher.preload.so`) and a language library (e.g. `apm-library-python`) — injection succeeded for this process. ERROR: Launcher present but no language library — launcher ran but couldn't inject. Check for injection errors: ### Claude runs ```bash pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h ``` ERROR: Neither present — process was not injected. Check `/etc/ld.so.preload`: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> "cat /etc/ld.so.preload" ``` If empty — install did not set up the launcher. Re-run the install script with `DD_APM_INSTRUMENTATION_ENABLED=host`. If non-empty but the process still isn't injected — the process was started before the launcher was installed. Restart the service and recheck. --- ## Step 2: Confirm the Agent is Receiving Traces ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo datadog-agent status 2>&1 | grep -A 15 'APM Agent'" ``` Healthy output shows: - `feature_auto_instrumentation_enabled: true` - `Receiver (previous minute)` with `> 0` traces ERROR: `feature_auto_instrumentation_enabled: false` — SSI not active on the agent. Check `apm_config` in `/etc/datadog-agent/datadog.yaml`. ERROR: `Receiver (previous minute): 0` — agent running but no traces yet. Generate traffic first (see Step 3), then recheck. --- ## Step 3: Confirm the Service is Visible in Datadog ### Claude runs ```bash DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 1h ``` If `<SERVICE_NAME>` appears with `isTraced: true` — traces are reaching the Datadog backend. > **Flask / ddtrace v3 naming note:** With ddtrace >=3.x, Flask spans are emitted as `service:flask` rather than `service:<DD_SERVICE>`. The `DD_SERVICE` value appears as `base_service` on the spans. If you set `DD_SERVICE=my-app`, search for `service:flask` in the APM UI — the service list will show `flask`, not `my-app`. Check the `base_service` tag to confirm it matches your `DD_SERVICE`. ERROR: Service missing — generate traffic to trigger trace creation: ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo ss -tlnp 2>/dev/null | grep <PID> || sudo netstat -tlnp 2>/dev/null | grep <PID>" ``` Use the port from above: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "for i in \$(seq 1 10); do curl -s -o /dev/null http://localhost:<PORT>/; done" ``` Wait 30 seconds, then retry: ```bash DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 10m DD_SITE=<DD_SITE> pup traces search --query "service:<SERVICE_NAME>" --from 10m --limit 5 ``` ERROR: Still missing — check for injection errors and go to `troubleshoot-ssi`: ```bash pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h ``` --- ## Done Exit when ALL of the following are true: - [ ] Step 1: launcher + language library both visible in `/proc/<PID>/maps` - [ ] Step 2: agent APM receiver shows `> 0` traces/min - [ ] Step 3: service appears in `pup apm services list` If any check fails, go to `troubleshoot-ssi`. When all steps pass, automatically proceed to `onboarding-summary` now — do not ask the user for permission. --- ## Security constraints - Never write a raw API key into any file or chat message - Always confirm before restarting production services
Quelle prüfen
Preis und Betriebskosten
- Skill beziehen
- Preis unbestätigt
- Ausführen
- Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
- Lizenz
- MIT
- Preis unbestätigt
- Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.
Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →
Quelle erneut prüfen
Die Quelle wurde geändert oder konnte nicht synchronisiert werden. Vor der Installation prüfen.
Vor Installation prüfen: Automatische Installation vermeiden
Lizenz: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.
Mit einer kleinen Aufgabe beginnen
- 1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
- 2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
- 3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.
Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.
Quelle und Nutzungshinweise
Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.
- Quell-Repository
- datadog-labs/agent-skills
- Lizenz
- MIT
- Version
- 1.0.0
- Letzter GitHub-Push
- 26. Aug. 2026
- Verzeichnis aktualisiert
- 6. Sept. 2026
- Anleitungspfad
- dd-apm/linux-ssi/verify-ssi/SKILL.md @ 157edafdc100
Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.
Qualität
66/100
Vielversprechend
Vertrauen
63/100
Nur Sandbox
Audit
75/100
Riskant
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Ergebnisse
- —
Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.
Agent-Zugang
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Weitere Details
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"endpoints": {
"web": "https://www.openagentskill.com/skills/datadog-labs-verify-ssi",
"api": "https://www.openagentskill.com/api/agent/skills/datadog-labs-verify-ssi",
"audit": "https://www.openagentskill.com/skills/datadog-labs-verify-ssi/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=datadog-labs-verify-ssi&task=Use%20verify-ssi%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20verify-ssi%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20verify-ssi%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/datadog-labs-verify-ssi/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/datadog-labs-verify-ssi"
}
}Für Ersteller
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- datadog-labs
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird datadog-labs zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Share-Kit
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](https://www.openagentskill.com/skills/datadog-labs-verify-ssi?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datadog-labs-verify-ssi?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datadog-labs-verify-ssi/audit)
[](https://www.openagentskill.com/skills/datadog-labs-verify-ssi?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
