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Overview

How to integrate Datadog with Kubernetes on Qovery. While Qovery will soon provide basic metrics on apps resources usage, you might need a more advanced view on what happens on your infrastructure. There are many solutions on the market, one of them being Datadog. Datadog is one of the leading platforms for monitoring and observability, and it is pretty easy to integrate it with Qovery.

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Prerequisites

Before you begin, this guide assumes the following:
  • You have a Qovery cluster running
  • You have a dedicated Qovery project and environment to deploy Datadog (example: Project=Tooling, Environment=Production)
  • You have a Datadog account
  • You have already created a Datadog API Key here: https://app.datadoghq.<region>/organization-settings/api-keys
An API key is required, not an Application key. Please ensure you are using the correct key to authenticate.
Datadog - API Key

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Installation

In this tutorial, we will install the Datadog agent on a Qovery cluster to gather metrics about infrastructure and applications.
This tutorial is based on a specific version of Datadog. We have created it to assist our users, but Qovery is not responsible for any configuration issues—please contact Datadog support.

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Step 1: Add the Datadog Helm Repository

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Add Helm Repository

In Qovery Console:
  1. Go to Settings → Helm Repositories
  2. Click Add Repository
  3. Configure:
    • Repository name: Datadog
    • Kind: HTTPS
    • Repository URL: https://helm.datadoghq.com

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Step 2: Create the Datadog Service in Qovery

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Create Helm Service

In your environment:
  1. Click Create → Helm Chart
  2. Configure:
    • Application name: Datadog
    • Helm source: Helm repository
    • Repository: Datadog
    • Chart name: datadog
    • Version: 3.49.5 (or latest)
    • Allow cluster-wide resources: ✔️
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Add Values YAML

Use this minimal configuration in the Override as file section:
# The following YAML contains the minimum configuration required to deploy the Datadog Agent
datadog:
  apiKey: qovery.env.DD_API_KEY
  site: datadoghq.eu  # Use datadoghq.com for US
  clusterName: qoverycluster

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Step 3: Store the Datadog API Key as Secret

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Add Secret Variable

  1. Open service overview
  2. Go to Variables section
  3. Add Variable:
    • Variable = DD_API_KEY
    • Value = <your_API_KEY>
    • Scope = Service
    • Secret variable: ✔️
    Datadog Secret Configuration

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Step 4: Deploy the Chart

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Deploy

  1. Click the Deploy button
  2. Follow deployment logs
  3. Verify Datadog agent pods are running Deploy Datadog Datadog Pods Running

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Step 5: Verify Setup on Datadog

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Check Datadog Dashboard

  1. Access Datadog interface
  2. Navigate to Infrastructure → Containers → Kubernetes
  3. Confirm data is coming from your Qovery cluster Datadog Console

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Advanced Configuration

For more advanced Datadog configuration, you can extend the values.yaml through the Override as file section: 
datadog:
  apiKey: qovery.env.DD_API_KEY
  site: datadoghq.eu
  clusterName: qoverycluster

  # Enable logs collection
  logs:
    enabled: true
    containerCollectAll: true

  # Enable APM (Application Performance Monitoring)
  apm:
    portEnabled: true
    port: 8126

  # Enable process monitoring
  processAgent:
    enabled: true
    processCollection: true

  # Enable network monitoring
  networkMonitoring:
    enabled: true

# Agent configuration
agents:
  enabled: true

  # Resource limits
  resources:
    requests:
      cpu: 200m
      memory: 256Mi
    limits:
      cpu: 500m
      memory: 512Mi

# Cluster Agent (for Kubernetes metadata)
clusterAgent:
  enabled: true
  replicas: 2

  resources:
    requests:
      cpu: 200m
      memory: 256Mi
    limits:
      cpu: 500m
      memory: 512Mi

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Instrumenting Your Applications

To enable APM for your applications, add these environment variables in Qovery: 
DD_AGENT_HOST=datadog-agent.qovery.svc.cluster.local
DD_TRACE_AGENT_PORT=8126
DD_SERVICE=my-app
DD_ENV=production
DD_VERSION=$QOVERY_COMMIT_ID
Then instrument your application using the Datadog tracer for your language. See Datadog’s instrumentation docs for language-specific guides.

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Troubleshooting

Problem: Datadog agent pods crash or fail to startSolutions:
  • Check API key is valid: kubectl logs -n qovery datadog-agent-xxx
  • Verify secret exists: kubectl get secret -n qovery
  • Check resource limits (may need more memory)
  • Review values.yaml for syntax errors
Problem: Cluster appears in Datadog but no metricsSolutions:
  • Wait 5-10 minutes for initial data
  • Verify agent is scraping: Check agent logs
  • Ensure correct site (datadoghq.com vs datadoghq.eu)
  • Check firewall/network policies allow outbound to Datadog
Problem: On a cluster with Karpenter enabled, some applications have their logs properly visible in Datadog but the logs are missing for some other applications.Reason: The Datadog agent DaemonSet likely has node selectors or taints/tolerations that prevent it from running on the stable nodes where some of your services have been scheduled. Services with only one pod typically run on the stable node pool, which explains why logs from these services are missing when Karpenter is enabled.Solutions:
  • Option 1 - tolerate all taints (recommended):
tolerations:
- operator: Exists  # This will tolerate all taints
  • Option 2 - Specific node pool tolerations If you prefer to be more selective, use these specific tolerations:
tolerations:
  - key: "qovery.com/node-pool"
    operator: "Equal"
    value: "stable"
    effect: "NoSchedule"
  - key: "qovery.com/node-pool"
    operator: "Equal"
    value: "default"
    effect: "NoSchedule"
After updating your Datadog Helm chart with these tolerations, the agent should be able to collect logs from services running on both the default and stable node pools.

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Next Steps

Datadog Documentation

Official Datadog Kubernetes docs

Datadog Getting Started

Getting started guide

Kubecost

Monitor and reduce Kubernetes costs

Qovery Observe

Built-in observability option