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Dd Apm

OrganizationPopular
DataDog
dd-apm

APM - traces, services, dependencies, performance analysis.

Overview

PublisherDataDog
Repositorypup
Skill namedd-apm
Stars
1K
Forks
127
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by DataDog on GitHub. Read the source before you install it.

Installation

Install the Dd Apm AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/DataDog/pup/tree/main/skills/dd-apm
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/DataDog/pup.git /tmp/pup
mkdir -p .claude/skills
cp -r /tmp/pup/skills/dd-apm .claude/skills/dd-apm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dd Apm in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dd Apm on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dd Apm is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Datadog APM

Distributed tracing, service maps, and performance analysis.

Requirements

Datadog Labs Pup should be installed via:

bash
brew tap datadog-labs/pack
brew install pup

Quick Start

bash
pup auth login
pup apm services list --env production
pup traces search --query="service:api-gateway" --from="1h"

Services

List Services

--env is required for all apm services commands.

bash
pup apm services list --env production
pup apm services list --env staging

Service Statistics

bash
pup apm services stats --env production
pup apm services stats --env production --from 4h

Service Operations and Resources

bash
# List operations for a service
pup apm services operations --env production --service api-gateway

# List resources (endpoints) for an operation
pup apm services resources --env production --service api-gateway --name http.request

Service Dependencies

bash
pup apm dependencies list --env production

Flow Map

bash
# View service flow map (--query and --env required)
pup apm flow-map --query "service:api-gateway" --env production

Traces

Traces are searched via the top-level traces command (not under apm).

Important: APM durations are in nanoseconds: 1 second = 1,000,000,000 ns.

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 (>1 second = 1000000000 ns)
pup traces search --query="service:api-gateway @duration:>1000000000" --from="1h"

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

Aggregate Traces

bash
# Average duration by resource
pup traces aggregate \
  --query="service:api-gateway" \
  --compute="avg(@duration)" \
  --group-by="resource_name" \
  --from="1h"

# Error count by service
pup traces aggregate \
  --query="status:error" \
  --compute="count" \
  --group-by="service" \
  --from="1h"

# p99 latency
pup traces aggregate \
  --query="service:api-gateway" \
  --compute="percentile(@duration, 99)" \
  --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

⚠️ Trace Sampling

Not all traces are kept. Understand sampling:

ModeWhat's Kept
Head-basedRandom % at start
Error/SlowAll errors, slow traces
RetentionWhat's indexed (billed)

Trace Retention Costs

RetentionCost
Indexed spans$$$ per million
Ingested spans$ per million

Best practice: Only index what you need for search.

Service Level Objectives

Link APM to SLOs:

bash
pup slos create --file slo.json

Common Queries

GoalQuery
Slowest endpointspup traces aggregate --query="service:api" --compute="avg(@duration)" --group-by="resource_name" --from="1h"
Error rate by servicepup traces aggregate --query="status:error" --compute="count" --group-by="service" --from="1h"
Throughputpup traces aggregate --query="service:api" --compute="count" --group-by="resource_name" --from="1h"

Service Config

Query service instance metadata — instance IDs, hostnames, and config IDs for all running instances of a service. Returns up to 100 instances.

bash
# Get instance metadata for a service
pup apm service-config get --service-name my-service

# Filter by environment
pup apm service-config get --service-name my-service --env prod

# Filter by specific instance IDs
pup apm service-config get --service-name my-service --service-instance-ids "id-1,id-2"

Note on service identity: service_name and env come from the SDK telemetry pipeline and may differ from values in the Service Catalog.

Service Library Config

Query the APM tracer configuration deployed across all running instances of a service. Useful for auditing config drift — finding instances where tracing, profiling, or AppSec is misconfigured relative to the rest of the fleet.

bash
# Get tracer config for a service
pup apm service-library-config get --service-name my-service

# Filter by environment
pup apm service-library-config get --service-name my-service --env prod

# Filter by language
pup apm service-library-config get --service-name my-service --env prod --language python

# Only show configs where instances disagree (config drift)
pup apm service-library-config get --service-name my-service --mixed

Note on service identity: service_name, env, and language_name come from the SDK telemetry pipeline and reflect what the tracer reports at runtime. These may differ from values in the Service Catalog, which aggregates data from multiple sources (APM spans, USM, infrastructure tags, manual definitions).

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
--env required errorAlways pass --env to apm services commands

References/Docs

Frequently asked questions

What does the Dd Apm AI skill do?

APM - traces, services, dependencies, performance analysis.

Why use Dd Apm on TypingMind?

Because you install it once and use it with any model. Dd Apm is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dd Apm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DataDog/pup/tree/main/skills/dd-apm. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dd Apm?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dd Apm?

As many as you like. As long as a model supports skills, you can use Dd Apm with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dd Apm AI skill free?

Yes. It is published on GitHub by DataDog under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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