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Agent Install

DatadogOfficialCreated by datadog-labs

  • Skill
  • Workflow
  • Cloud and DevOps
  • MIT
  • Low risk

From the author

Install the Datadog Agent on Kubernetes using the Datadog Operator — required before enabling Single Step Instrumentation (SSI), which automatically instruments applications for APM without code changes. Only use if no Datadog Agent is deployed on the cluster yet.
— the description by datadog-labs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a step-by-step workflow for installing the Datadog Agent on a Kubernetes cluster. It utilizes the Datadog Operator to manage the deployment, ensuring that the Agent is correctly configured for monitoring, log collection, and cluster checks. The process includes environment validation, credential management via Kubernetes secrets, and verification of the Agent's health and authentication status.

What it does

  • Checks for existing Datadog Agent installations to prevent conflicts.
  • Installs the Datadog Operator via Helm.
  • Creates a secure Kubernetes secret for the Datadog API key.
  • Deploys the DatadogAgent custom resource with standard monitoring features.
  • Validates API key authentication and Agent pod health.
  • Automatically transitions to Single Step Instrumentation (SSI) setup upon completion.

When to use it

  • When you need to deploy the Datadog Agent on a Kubernetes cluster for the first time.
  • When preparing a cluster for Datadog APM and Single Step Instrumentation.
  • When you need to ensure the Datadog Operator is correctly managing your monitoring infrastructure.

Advantages

  • Follows security best practices by using Kubernetes secrets instead of raw API keys.
  • Automates the verification of credentials and pod readiness.
  • Provides a standardized, repeatable deployment pattern for Kubernetes environments.
  • Integrates seamlessly with subsequent Datadog instrumentation workflows.

Usage examples

“Install the Datadog Agent on my Kubernetes cluster.”
The agent will verify your environment, install the Datadog Operator, configure the necessary secrets, and deploy the DatadogAgent resource.
“I need to set up Datadog monitoring for my EKS cluster.”
The agent will guide you through setting your API key and site, then perform the operator-based installation tailored for managed Kubernetes.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/datadog-labs/agent-install/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip agent-install.zip -d .agents/skills

Documentation by datadog-labs

Install the Datadog Agent on Kubernetes

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.

Phase 0: Load Credentials

[ -f environment ] && source environment
echo "DD_API_KEY set: $([ -n "${DD_API_KEY:-}" ] && echo yes || echo no)"
echo "DD_SITE: ${DD_SITE:-not set}"
echo "helm: $(helm version --short 2>/dev/null || echo NOT FOUND)"

If helm is not found — tell the user:

helm is required for this skill. Install it with:

brew install helm        # macOS
# or see https://helm.sh/docs/intro/install/ for other platforms

Once installed, let me know and I'll continue.

Do not proceed until helm is available.

If DD_API_KEY is already set — proceed to Prerequisites.

If DD_API_KEY is not set — tell the user:

I need two things to continue:

1. Datadog API Key — used to authenticate the Agent with your Datadog account. You can find or create one at: https://app.datadoghq.com/organization-settings/api-keys

2. Datadog Site — the region your Datadog account is on. Most accounts use datadoghq.com. Check your Datadog URL to confirm (e.g. app.datadoghq.eu → site is datadoghq.eu). Other options: us3.datadoghq.com, us5.datadoghq.com, ap1.datadoghq.com.

Please run the following in this chat to set your credentials (the ! prefix executes it in this session):

! export DD_API_KEY=your-api-key-here
! export DD_SITE=datadoghq.com

Wait for the user to run the commands, then re-run the check above before continuing.


Prerequisites

  • [ ] Kubernetes v1.20+ — kubectl version

  • [ ] helm v3+ — helm version

  • [ ] kubectl configured to target cluster — kubectl config current-context

  • [ ] pup-cli installed — check with pup --version; if missing, install it now:

    brew tap datadog-labs/pack && brew install datadog-labs/pack/pup
    pup --version

    Without Homebrew, download the binary from the latest Pup release and check its published checksum before placing it on PATH. Do not skip — proceed only once pup --version succeeds.


Context to resolve before acting

VariableHow to resolve
CLUSTER_NAMECheck repo IaC, scripts, or kubectl config current-context
DD_SITEAsk the user. Default: datadoghq.com. Common options: datadoghq.eu, us3.datadoghq.com, us5.datadoghq.com, ap1.datadoghq.com. Full list: https://docs.datadoghq.com/getting_started/site/
AGENT_NAMESPACEUse datadog unless the repo already uses datadog-agent consistently
CHART_VERSIONRun helm search repo datadog/datadog-operator --versions | head -5 and use the latest stable

Step 1: Check for an Existing Agent Installation

Claude runs
helm list -A | grep -i datadog

If a release shows deployed — Agent already installed. Skip to Step 5 to confirm health, then exit.

If there is no output — no existing install. Continue to Step 2.


Step 2: Install the Datadog Operator

Claude runs
helm repo add datadog https://helm.datadoghq.com
helm repo update

helm upgrade --install datadog-operator datadog/datadog-operator \
  --namespace <AGENT_NAMESPACE> \
  --create-namespace \
  --version <CHART_VERSION>

kubectl wait --for=condition=Ready pod \
  -l app.kubernetes.io/name=datadog-operator \
  -n <AGENT_NAMESPACE> \
  --timeout=120s

If the Operator pod is Running — continue to Step 3.

ERROR: Pod not ready after 120s — check image pull: kubectl describe pod -l app.kubernetes.io/name=datadog-operator -n <AGENT_NAMESPACE>.


Step 3: Create the API Key Secret

What you need to do in a terminal
export DD_API_KEY=<your-api-key>

kubectl create secret generic datadog-secret \
  --from-literal api-key=$DD_API_KEY \
  --namespace <AGENT_NAMESPACE>

If secret/datadog-secret created — continue to Step 4.

ERROR: AlreadyExists — confirm which key it holds via Step 5 before deciding whether to recreate.


Step 4: Deploy the DatadogAgent Resource

[DECISION: cluster type]

  • Self-hosted (minikube, kind): include kubelet.tlsVerify: false inside spec.global

  • Managed (GKE, EKS, AKS): omit kubelet.tlsVerify entirely

[DECISION: APM/SSI also being enabled in this session]

  • If yes: do not create a separate DatadogAgent for APM — extend this same manifest with features.apm per enable-ssi. One manifest, not two.

  • If no: use the manifest below as-is.

Save the following as datadog-agent.yaml:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
  namespace: <AGENT_NAMESPACE>
spec:
  global:
    clusterName: <CLUSTER_NAME>
    site: <DD_SITE>
    credentials:
      apiSecret:
        secretName: datadog-secret
        keyName: api-key
    # Self-hosted clusters only (minikube, kind):
    # kubelet:
    #   tlsVerify: false
  features:
    orchestratorExplorer:
      enabled: true
    clusterChecks:
      enabled: true
    logCollection:
      enabled: true
      containerCollectAll: false
Claude runs
kubectl apply -f datadog-agent.yaml

kubectl wait --for=condition=Ready pod \
  -l app.kubernetes.io/component=agent \
  -n <AGENT_NAMESPACE> \
  --timeout=120s 2>/dev/null || true

Step 5: Verify the API Key

Claude runs
kubectl logs -l app.kubernetes.io/component=agent \
  -n <AGENT_NAMESPACE> \
  --tail=50 2>/dev/null \
  | grep -iE "invalid.*api\.?key|api\.?key.*invalid" \
  || echo "No authentication errors found"

If No authentication errors found — key is accepted.

ERROR: Authentication errors found — validate credentials directly:

Claude runs
# Prefer pup (OAuth) — fall back to curl with API key
if pup auth status 2>/dev/null | grep -q "Logged in"; then
  echo "pup OAuth authenticated"
elif [ -n "${DD_API_KEY:-}" ]; then
  RESPONSE=$(curl -s -o /dev/null -w "%{http_code}" \
    -X GET "https://api.<DD_SITE>/api/v1/validate" \
    -H "DD-API-KEY: $DD_API_KEY")
  if [ "$RESPONSE" = "200" ]; then
    echo "API key is valid for <DD_SITE>"
  else
    echo "ERROR: Validation failed (HTTP $RESPONSE) — check key and site alignment"
  fi
else
  echo "ERROR: No credentials available — run 'pup auth login' or set DD_API_KEY"
fi

If key is invalid:

What you need to do in a terminal
export DD_API_KEY=<new-api-key>

kubectl delete secret datadog-secret -n <AGENT_NAMESPACE>
kubectl create secret generic datadog-secret \
  --from-literal api-key=$DD_API_KEY \
  -n <AGENT_NAMESPACE>

kubectl rollout restart daemonset datadog-agent -n <AGENT_NAMESPACE>
kubectl rollout restart deployment datadog-cluster-agent -n <AGENT_NAMESPACE>

Done

Exit when ALL of the following are true:

  • [ ] Datadog Operator pod is Running in AGENT_NAMESPACE

  • [ ] datadog-secret exists in AGENT_NAMESPACE

  • [ ] Agent DaemonSet pods are Running

  • [ ] Step 5 returns no authentication errors

Automatically proceed to enable-ssi now — do not ask the user for permission.


Security constraints

  • Never write a raw API key into any file, YAML block, or chat message — always use $DD_API_KEY

  • Never create a Kubernetes Secret manifest file — always use kubectl create secret imperatively

  • Never use apiKey: directly in DatadogAgent spec — always use apiSecret: with a secret reference

  • Never use --set datadog.apiKey=... in any Helm command

  • Never use namespace default for Datadog Agent resources

  • Never run kubectl delete without user confirmation

Files

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "agent-install", distributed by AutoGineer (https://autogineer.com/agent-skills).

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

  • ATTRIBUTION.md: this file, written by AutoGineer

  • LICENSE: copied from LICENSE

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs a command-line tool

Security

What our scanner noticed· Low risk

  • Phrasing that asks for actions without confirmation

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
datadog-labs
Publisher
Datadog (Official)
Source
datadog-labs/agent-skills · dd-apm/k8s-ssi/agent-install · commit 8e1306a
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by datadog-labs or Datadog.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download agent-install.zip