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Datadog APM

Datadog APM

by Datadog
v1.1.0
MIT
Repository Docs
markdown Development
datadogapmtracingdistributed-tracingkubernetesopentelemetryinstrumentation

Summary

Install, instrument and analyse Datadog APM from an agent — Kubernetes and Linux Single-Step Instrumentation, service remapping, trace search and service maps.

Features

  • Routing table that names the wrong-but-plausible install approaches
  • Kubernetes Single-Step Instrumentation: agent install, enable, verify
  • Linux SSI for single hosts and VMs
  • Service remapping at ingestion instead of redeploying with a new DD_SERVICE
  • Trace search by service, error status, duration and tag
  • Service maps, flow maps and the core trace.http.request metrics

Install This Skill

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This skill is plain instructions — it works with any assistant that accepts custom instructions or system prompts.

  1. Copy the skill content with the button below.
  2. Paste it into your agent's instruction file or system prompt (for example AGENTS.md, .cursorrules, or a custom instructions field).
  3. Ask the agent to apply the skill whenever the task matches.

Skill Content

Markdown Content

Copy this content and use it with your preferred AI agent

---
name: dd-apm
description: APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.
alwaysApply: true
metadata:
  version: "1.1.0"
  author: datadog-labs
  repository: https://github.com/datadog-labs/agent-skills
  tags: datadog,apm,tracing,performance,distributed-tracing,dd-apm,install,onboarding,instrumentation,ssi,agent
  globs: "**/ddtrace*,**/datadog*.yaml,**/*trace*"
---

# 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:

| Hint | Route to |
|---|---|
| Cluster orchestrator mentioned (EKS/GKE/AKS/kind/K3s/minikube) — even if "just one node" | k8s-ssi |
| Single host, VM, or EC2 with no orchestrator | linux-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](https://github.com/datadog-labs/agent-skills/tree/main?tab=readme-ov-file#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

```bash
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

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

### Service Stats

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

### Service Map

```bash
# 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

```bash
# 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

```bash
# 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

| Metric | What It Measures |
|--------|------------------|
| `trace.http.request.hits` | Request count |
| `trace.http.request.duration` | Latency |
| `trace.http.request.errors` | Error count |
| `trace.http.request.apdex` | User satisfaction |

## Service Level Objectives

Link APM to SLOs:

```bash
pup slos create --file slo.json
```

## Common Queries

| Goal | Query |
|------|-------|
| Slowest endpoints | `avg:trace.http.request.duration{*} by {resource_name}` |
| Error rate | `sum:trace.http.request.errors{*} / sum:trace.http.request.hits{*}` |
| Throughput | `sum:trace.http.request.hits{*}.as_rate()` |

## Troubleshooting

| Problem | Fix |
|---------|-----|
| No traces | Check ddtrace installed, DD_TRACE_ENABLED=true |
| Missing service | Verify DD_SERVICE env var |
| Traces not linked | Check trace headers propagated |
| High cardinality | Don't tag with user_id/request_id |

## References/Docs

- [APM Setup](https://docs.datadoghq.com/tracing/)
- [Trace Search](https://docs.datadoghq.com/tracing/trace_explorer/)

Usage Instructions

Learn how to use this skill with different AI agents.

Generic Instructions

Install the pup CLI, authenticate, then add the skill:

brew tap datadog-labs/pack
brew install datadog-labs/pack/pup
pup auth login

npx skills add datadog-labs/agent-skills --skill dd-apm --full-depth -y

dd-pup is the base skill the others assume; add it alongside any of them:

npx skills add datadog-labs/agent-skills --skill dd-pup --skill dd-apm --full-depth -y

Description

Datadog APM onboarding has a specific failure mode: the commands that look right are the ones that silently do nothing. This official skill is built around that problem. Rather than a flat reference, it opens with a routing table that matches the request to a sub-skill and — crucially — names the wrong approach that appears to work.

The traps it names

Installing Single-Step Instrumentation on Kubernetes via helm install datadog/datadog does not work, because the standard chart does not support SSI through the DatadogAgent custom resource. Adding ddtrace imports or ddtrace-run to the application is unnecessary and misleading, because SSI auto-instruments without code changes. The admission.datadoghq.com/enabled annotation configures admission-controller config injection, not SSI init-container injection. On Linux, apt-get install datadog-agent does not bring host auto-instrumentation with it. Each of these is called out explicitly, and the skill instructs the agent to read the relevant sub-skill rather than proceed from memory.

Routing and disambiguation

Three sub-skill paths are covered: Kubernetes SSI (agent install, enable, verify), Linux SSI (the same three steps for a single host or VM), and service remapping. The remapping guidance is a genuinely useful piece of platform knowledge — renaming a service by editing DD_SERVICE or tags.datadoghq.com/service requires a rollout and only affects new data, whereas a remapping rule rewrites the name at ingestion with no deployment. A tiebreaker table resolves requests that could fit more than one path, and where no sub-skill exists yet (reducing APM cost) it tells the agent to ask whether the user means sampling or retention filters instead of guessing.

Analysis

For day-to-day work it documents pup apm services list/stats, flow maps for dependencies, and trace search by service, error status, duration threshold and tag. The key trace.http.request.* metrics are tabulated with what each measures, along with the standard error-rate, throughput and slowest-endpoint queries. A troubleshooting table maps missing traces and unlinked spans to their usual causes, including the cardinality warning against tagging with user_id or request_id.

One nice detail: the quick start tells the agent to confirm the environment tag with the user rather than assuming prod. Requires the pup CLI. MIT-licensed, published by Datadog Labs.

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