Skip to content

eks_fargate

Directory actions

More options

Directory actions

More options

Latest commit

 

History

History
 
 

eks_fargate

README.md

Agent Check: eks_fargate

Overview

Amazon EKS on AWS Fargate is a managed Kubernetes service that automates certain aspects of deployment and maintenance for any standard Kubernetes environment. Kubernetes nodes are managed by AWS Fargate and abstracted away from the user.

Setup

These steps cover the setup of the Datadog Agent v7.17+ in a container within Amazon EKS on AWS Fargate. Refer to the Datadog-Amazon EKS integration documentation if you are not using AWS Fargate.

AWS Fargate pods are not physical pods, which means they exclude host-based system-checks, like CPU, memory, etc. In order to collect data from your AWS Fargate pods, you must run the Agent as a sidecar of your application pod with custom RBAC, which enables these features:

  • Kubernetes metrics collection from the pod running your application containers and the Agent
  • Autodiscovery
  • Configuration of custom Agent Checks to target containers in the same pod
  • APM and DogStatsD for containers in the same pod

EC2 Node

If you don't specify through AWS Fargate Profile that your pods should run on fargate, your pods can use classical EC2 machines. If it's the case refer to the Datadog-Amazon EKS integration setup in order to collect data from your them. This works by running the Agent as an EC2-type workload. The Agent setup is the same as that of the Kuberenetes Agent setup, and all options are available. To deploy the Agent on EC2 nodes, use the DaemonSet setup for the Datadog Agent.

Installation

To get the best observability coverage monitoring workloads in AWS EKS Fargate, install the Datadog integrations for:

Also, set up integrations for any other AWS services you are running with EKS (for example, ELB).

Manual Installation

To install, download the custom Agent image: datadog/agent with version v7.17 or above.

If the Agent is running as a sidecar, it can communicate only with containers on the same pod. Run an Agent for every pod you wish to monitor.

Configuration

To collect data from your applications running in AWS EKS Fargate over a Fargate node, follow these setup steps:

AWS EKS Fargate RBAC

Use the following Agent RBAC when deploying the Agent as a sidecar in AWS EKS Fargate:

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: datadog-agent
rules:
  - apiGroups:
      - ""
    resources:
      - nodes/metrics
      - nodes/spec
      - nodes/stats
      - nodes/proxy
      - nodes/pods
      - nodes/healthz
    verbs:
      - get
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: datadog-agent
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: datadog-agent
subjects:
  - kind: ServiceAccount
    name: datadog-agent
    namespace: default
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: datadog-agent
  namespace: default

Running the Agent as a sidecar

To start collecting data from your Fargate type pod, deploy the Datadog Agent v7.17+ as a sidecar of your application. This is the minimum configuration required to collect metrics from your application running in the pod, notice the adition of DD_EKS_FARGATE=true in the manifest to deploy your Datadog Agent sidecar.

apiVersion: apps/v1
kind: Deployment
metadata:
 name: "<APPLICATION_NAME>"
 namespace: default
spec:
 replicas: 1
 template:
   metadata:
     labels:
       app: "<APPLICATION_NAME>"
     name: "<POD_NAME>"
   spec:
     serviceAccountName: datadog-agent
     containers:
     - name: "<APPLICATION_NAME>"
       image: "<APPLICATION_IMAGE>"
     ## Running the Agent as a side-car
     - image: datadog/agent
       name: datadog-agent
       env:
       - name: DD_API_KEY
         value: "<YOUR_DATADOG_API_KEY>"
         ## Set DD_SITE to "datadoghq.eu" to send your
         ## Agent data to the Datadog EU site
       - name: DD_SITE
         value: "datadoghq.com"
       - name: DD_EKS_FARGATE
         value: "true"
       - name: DD_KUBERNETES_KUBELET_NODENAME
         valueFrom:
           fieldRef:
             apiVersion: v1
             fieldPath: spec.nodeName
      resources:
          requests:
            memory: "256Mi"
            cpu: "200m"
          limits:
            memory: "256Mi"
            cpu: "200m"

Note: Don't forget to replace <YOUR_DATADOG_API_KEY> with the Datadog API key from your organization.

Metrics Collection

Integration metrics

Use Autodiscovery labels with your application container to start collecting its metrics for the supported Agent integrations.

apiVersion: apps/v1
kind: Deployment
metadata:
 name: "<APPLICATION_NAME>"
 namespace: default
spec:
 replicas: 1
 template:
   metadata:
     labels:
       app: "<APPLICATION_NAME>"
     name: "<POD_NAME>"
     annotations:
      ad.datadoghq.com/<CONTAINER_NAME>.check_names: '[<CHECK_NAME>]'
      ad.datadoghq.com/<CONTAINER_IDENTIFIER>.init_configs: '[<INIT_CONFIG>]'
      ad.datadoghq.com/<CONTAINER_IDENTIFIER>.instances: '[<INSTANCE_CONFIG>]'
   spec:
     serviceAccountName: datadog-agent
     containers:
     - name: "<APPLICATION_NAME>"
       image: "<APPLICATION_IMAGE>"
     ## Running the Agent as a side-car
     - image: datadog/agent
       name: datadog-agent
       env:
       - name: DD_API_KEY
         value: "<YOUR_DATADOG_API_KEY>"
         ## Set DD_SITE to "datadoghq.eu" to send your
         ## Agent data to the Datadog EU site
       - name: DD_SITE
         value: "datadoghq.com"
       - name: DD_EKS_FARGATE
         value: "true"
       - name: DD_KUBERNETES_KUBELET_NODENAME
         valueFrom:
           fieldRef:
             apiVersion: v1
             fieldPath: spec.nodeName
      resources:
          requests:
            memory: "256Mi"
            cpu: "200m"
          limits:
            memory: "256Mi"
            cpu: "200m"

Note: Don't forget to replace <YOUR_DATADOG_API_KEY> with the Datadog API key from your organization.

DogStatsD

Set up the container port 8125 over your Agent container to forward DogStatsD metrics from your application container to Datadog.

apiVersion: apps/v1
kind: Deployment
metadata:
 name: "<APPLICATION_NAME>"
 namespace: default
spec:
 replicas: 1
 template:
   metadata:
     labels:
       app: "<APPLICATION_NAME>"
     name: "<POD_NAME>"
   spec:
     serviceAccountName: datadog-agent
     containers:
     - name: "<APPLICATION_NAME>"
       image: "<APPLICATION_IMAGE>"
     ## Running the Agent as a side-car
     - image: datadog/agent
       name: datadog-agent
       ## Enabling port 8125 for DogStatsD metric collection
       ports:
        - containerPort: 8125
          name: dogstatsdport
          protocol: UDP
       env:
       - name: DD_API_KEY
         value: "<YOUR_DATADOG_API_KEY>"
         ## Set DD_SITE to "datadoghq.eu" to send your
         ## Agent data to the Datadog EU site
       - name: DD_SITE
         value: "datadoghq.com"
       - name: DD_EKS_FARGATE
         value: "true"
       - name: DD_KUBERNETES_KUBELET_NODENAME
         valueFrom:
           fieldRef:
             apiVersion: v1
             fieldPath: spec.nodeName
      resources:
          requests:
            memory: "256Mi"
            cpu: "200m"
          limits:
            memory: "256Mi"
            cpu: "200m"

Note: Don't forget to replace <YOUR_DATADOG_API_KEY> with the Datadog API key from your organization.

Traces Collection

Set up the container port 8126 over your Agent container to collect traces from your application container. Read more about how to set up tracing.

apiVersion: apps/v1
kind: Deployment
metadata:
 name: "<APPLICATION_NAME>"
 namespace: default
spec:
 replicas: 1
 template:
   metadata:
     labels:
       app: "<APPLICATION_NAME>"
     name: "<POD_NAME>"
   spec:
     serviceAccountName: datadog-agent
     containers:
     - name: "<APPLICATION_NAME>"
       image: "<APPLICATION_IMAGE>"
     ## Running the Agent as a side-car
     - image: datadog/agent
       name: datadog-agent
       ## Enabling port 8126 for Trace collection
       ports:
        - containerPort: 8126
          name: traceport
          protocol: TCP
       env:
       - name: DD_API_KEY
         value: "<YOUR_DATADOG_API_KEY>"
         ## Set DD_SITE to "datadoghq.eu" to send your
         ## Agent data to the Datadog EU site
       - name: DD_SITE
         value: "datadoghq.com"
       - name: DD_EKS_FARGATE
         value: "true"
       - name: DD_APM_ENABLED
         value: "true"
       - name: DD_KUBERNETES_KUBELET_NODENAME
         valueFrom:
           fieldRef:
             apiVersion: v1
             fieldPath: spec.nodeName
      resources:
          requests:
            memory: "256Mi"
            cpu: "200m"
          limits:
            memory: "256Mi"
            cpu: "200m"

Note: Don't forget to replace <YOUR_DATADOG_API_KEY> with the Datadog API key from your organization.

Events Collection

To collect events from your AWS EKS Fargate API server, run a Datadog Cluster Agent over an AWS EKS EC2 pod within your Kubernetes cluster:

  1. Setup the Datadog Cluster Agent.
  2. Enable Event collection for your Cluster Agent.

Optionally, deploy cluster check runners in addition to setting up the Datadog Cluster Agent to enable cluster checks.

Note: You can also collect events if you run the Datadog Cluster Agent in a pod in Fargate.

Data Collected

Metrics

The eks_fargate check submits a heartbeat metric eks.fargate.pods.running that is tagged by pod_name and virtual_node so you can keep track of how many pods are running.

Service Checks

eks_fargate does not include any service checks.

Events

eks_fargate does not include any events.

Troubleshooting

Need help? Contact Datadog support.