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dd-apmDD APM 搜索

Agent Skill

dd-apm 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,334

周安装

477

GitHub Stars

97

下载量

3,969
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dd-apm(DD APM 搜索)
来源仓库:https://github.com/datadog-labs/agent-skills
仓库路径:skills/dd-apm
安装命令:
npx skills add https://github.com/datadog-labs/agent-skills --skill dd-apm
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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

简介

dd-apm 提供分布式追踪、服务地图和性能分析能力,用于定位微服务架构中的延迟和故障点。

  • 适合在 Kubernetes 环境中实施应用性能监控,需配合特定 Helm chart 配置而非通用 Datadog Agent。
  • 支持 traces、metrics 和 logs 关联查询,但要求精确的服务名称和标签过滤以提高查询效率。
  • 使用前必须完成 OAuth2 认证,并避免使用非官方推荐的部署方式以免导致监控盲区。
  • dd-apm 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Datadog APM

Distributed tracing, service maps, and performance analysis.

Routing — Read This First

For Kubernetes APM install / instrument / onboard tasks — follow this procedure exactly:

⚠️ 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. Do NOT use it. - Adding ddtrace imports or ddtrace-run to the app — SSI auto-instruments WITHOUT any code changes. - admission.datadoghq.com/enabled annotations — this is admission controller config injection, not SSI init container injection.

Step 0: Pre-flight checks (MANDATORY — run before installing anything)

# Check for ddtrace/otel — even without imports it SILENTLY DISABLES SSI at runtime
grep -rn "ddtrace\|dd-trace\|opentelemetry" requirements.txt package.json Gemfile go.mod pom.xml 2>/dev/null || echo "No tracer dependency found"

If ddtrace found → remove that line entirely from the dependency file, rebuild image, reload into cluster, restart pod.

Step 1: Install the Datadog Operator (NOT datadog/datadog)

helm repo add datadog https://helm.datadoghq.com && helm repo update
helm upgrade --install datadog-operator datadog/datadog-operator \
  --namespace datadog --create-namespace
kubectl wait --for=condition=Ready pod \
  -l app.kubernetes.io/name=datadog-operator -n datadog --timeout=120s

kubectl create secret generic datadog-secret \
  --from-literal api-key=$DD_API_KEY -n datadog

Step 2: Create DatadogAgent CR with SSI enabled

Save as datadog-agent.yaml, then kubectl apply -f datadog-agent.yaml:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
  namespace: datadog
spec:
  global:
    site: <DD_SITE>
    credentials:
      apiSecret:
        secretName: datadog-secret
        keyName: api-key
    kubelet:
      tlsVerify: false  # required for kind/minikube; omit for cloud clusters
  features:
    apm:
      instrumentation:
        enabled: true

Step 3: Apply Unified Service Tags to the application Deployment

Add to both metadata.labels and spec.template.metadata.labels:

tags.datadoghq.com/env: "dev"
tags.datadoghq.com/service: "<service-name>"
tags.datadoghq.com/version: "1.0.0"

Step 4: Restart app pods and verify SSI init containers

Confirm with the user before restarting. Tell the user: "I need to restart <name> in <namespace> for SSI to inject into the pods. This will cause a brief outage. Ready to proceed?" Wait for confirmation.
kubectl rollout restart deployment/<name> -n <namespace>
kubectl get pods -A -o json | grep -o '"datadog-lib[^"]*"' | sort -u

Expected: "datadog-lib-python-init" (or the language-appropriate init container).

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


For Linux APM install/instrument tasks: Immediately read .claude/skills/dd-apm/linux-ssi/agent-install/SKILL.md now, then enable-ssi then verify-ssi — do not proceed from memory or the summary above.

For trace search, service analysis, metrics: Continue below.

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

32.93%
按下载量换算1,307

Claude

31.05%
按下载量换算1,232

Cursor

18.09%
按下载量换算718

Gemini CLI

8.83%
按下载量换算350

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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