Overview

AWS Fargate on EKS provides a fully managed experience for running Kubernetes workloads. Amazon Data Firehose can be used with EKS’s Fluent Bit log router to collect logs in Datadog. This guide provides a comparison of log forwarding through Amazon Data Firehose and CloudWatch logs, as well as a sample EKS Fargate application to send logs to Datadog through Amazon Data Firehose.

Amazon Data Firehose and CloudWatch log forwarding

The following are key differences between using Amazon Data Firehose and CloudWatch log forwarding.

• Metadata and tagging: Metadata, such as Kubernetes namespace and container ID, are accessible as structured attributes when sending logs with Amazon Data Firehose.

• AWS Costs: AWS Costs may vary for individual use cases but Amazon Data Firehose ingestion is generally less expensive than comparable Cloudwatch Log ingestion.

Requirements

1. The following command line tools: kubectl, aws.
2. An EKS cluster with a Fargate profile and Fargate pod execution role. In this guide, the cluster is named fargate-cluster with a Fargate profile named fargate-profile applied to the namespace fargate-namespace. If you don’t already have these resources, use Getting Started with Amazon EKS to create the cluster and Getting Started with AWS Fargate using Amazon EKS to create the Fargate profile and pod execution role.

Setup

The following steps outline the process for sending logs from a sample application deployed on an EKS cluster through Fluent Bit and an Amazon Data Firehose delivery stream to Datadog. To maximize consistency with standard Kubernetes tags in Datadog, instructions are included to remap selected attributes to tag keys.

1. Create an Amazon Data Firehose delivery stream that delivers logs to Datadog, along with an S3 Backup for any failed log deliveries.
2. Configure Fluent Bit for Firehose on EKS Fargate.
3. Deploy a sample application.
4. Apply remapper processors for correlation using Kubernetes tags and the container_id tag.

Create an Amazon Data Firehose delivery stream

See the Send AWS Services Logs with the Datadog Amazon Data Firehose Destination guide to set up an Amazon Data Firehose Delivery stream. Note: Set the Source as Direct PUT.

Configure Fluent Bit for Firehose on an EKS Fargate cluster

1. Create the aws-observability namespace.

kubectl create namespace aws-observability

2. Create the following Kubernetes ConfigMap for Fluent Bit as aws-logging-configmap.yaml. Substitute the name of your delivery stream.

apiVersion: v1
kind: ConfigMap
metadata:
  name: aws-logging
  namespace: aws-observability
data:
  filters.conf: |
    [FILTER]
        Name                kubernetes
        Match               kube.*
        Merge_Log           On
        Buffer_Size         0
        Kube_Meta_Cache_TTL 300s    

  flb_log_cw: 'true'

  output.conf: |
    [OUTPUT]
        Name kinesis_firehose
        Match kube.*
        region <REGION>
        delivery_stream <YOUR-DELIVERY-STREAM-NAME>    

3. Use kubectl to apply the ConfigMap manifest.

kubectl apply -f aws-logging-configmap.yaml

4. Create an IAM policy and attach it to the pod execution role to allow the log router running on AWS Fargate to write to the Amazon Data Firehose. You can use the example below, replacing the ARN in the Resource field with the ARN of your delivery stream, as well as specifying your region and account ID.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "firehose:PutRecord",
                "firehose:PutRecordBatch"
            ],
            "Resource":
       "arn:aws:firehose:<REGION>:<ACCOUNTID>:deliverystream/<DELIVERY-STREAM-NAME>"
       }
]
}

a. Create the policy.

aws iam create-policy \
         --policy-name FluentBitEKSFargate \
         --policy-document file://allow_firehose_put_permission.json

b. Retrieve the Fargate Pod Execution Role and attach the IAM policy.

 POD_EXEC_ROLE=$(aws eks describe-fargate-profile \
   --cluster-name fargate-cluster \
   --fargate-profile-name fargate-profile \
   --query 'fargateProfile.podExecutionRoleArn' --output text |cut -d '/' -f 2)
 aws iam attach-role-policy \
         --policy-arn arn:aws:iam::<ACCOUNTID>:policy/FluentBitEKSFargate \
         --role-name $POD_EXEC_ROLE

Deploy a sample application

To generate logs and test the Amazon Data Firehose delivery stream, deploy a sample workload to your EKS Fargate cluster.

1. Create a deployment manifest sample-deployment.yaml.

 apiVersion: apps/v1
 kind: Deployment
 metadata:
   name: sample-app
   namespace: fargate-namespace
 spec:
   selector:
     matchLabels:
       app: nginx
   replicas: 1
   template:
     metadata:
       labels:
         app: nginx
     spec:
       containers:
       - name: nginx
         image: nginx
         ports:
         - containerPort: 80

2. Create the fargate-namespace namespace.

 kubectl create namespace fargate-namespace
 

3. Use kubectl to apply the deployment manifest.

 kubectl apply -f sample-deployment.yaml
 

Validation

1. Verify that sample-app pods are running in the namespace fargate-namespace.

 kubectl get pods -n fargate-namespace
 

Expected output:

 NAME                          READY   STATUS    RESTARTS   AGE
 sample-app-6c8b449b8f-kq2qz   1/1     Running   0          3m56s
 sample-app-6c8b449b8f-nn2w7   1/1     Running   0          3m56s
 sample-app-6c8b449b8f-wzsjj   1/1     Running   0          3m56s
 

2. Use kubectl describe pod to confirm that the Fargate logging feature is enabled.

 kubectl describe pod <POD-NAME> -n fargate-namespace |grep Logging
 

Expected output:

                    Logging: LoggingEnabled
 Normal  LoggingEnabled   5m   fargate-scheduler  Successfully enabled logging for pod
 

3. Inspect deployment logs.

 kubectl logs -l app=nginx -n fargate-namespace
 

Expected output:

 /docker-entrypoint.sh: Launching /docker-entrypoint.d/30-tune-worker-processes.sh
 /docker-entrypoint.sh: Configuration complete; ready for start up
 2023/01/27 16:53:42 [notice] 1#1: using the "epoll" event method
 2023/01/27 16:53:42 [notice] 1#1: nginx/1.23.3
 2023/01/27 16:53:42 [notice] 1#1: built by gcc 10.2.1 20210110 (Debian 10.2.1-6)
 2023/01/27 16:53:42 [notice] 1#1: OS: Linux 4.14.294-220.533.amzn2.x86_64
 2023/01/27 16:53:42 [notice] 1#1: getrlimit(RLIMIT_NOFILE): 1024:65535
 2023/01/27 16:53:42 [notice] 1#1: start worker processes
 ...
 

4. Verify the logs are in Datadog. In the Datadog Log Explorer, search for @aws.firehose.arn:"<ARN>", replacing <ARN> with your Amazon Data Firehose ARN, to filter for logs from the Amazon Data Firehose.

Remap attributes for log correlation

Logs from this configuration require some attributes to be remapped to maximize consistency with standard Kubernetes tags in Datadog.

1. Go to the Datadog Log Pipelines page.

2. Create a new pipeline with Name EKS Fargate Log Pipeline and Filter service:aws source:aws.

3. Create four Remapper processors to remap the following attributes to tag keys:

   Attribute to remap	Target Tag Key
   kubernetes.container_name	kube_container_name
   kubernetes.namespace_name	kube_namespace
   kubernetes.pod_name	pod_name
   kubernetes.docker_id	container_id

4. After creating this pipeline, logs emitted by the sample app are tagged like this example with the log attributes remapped to Kubernetes tags:

Further Reading

Additional helpful documentation, links, and articles:

ProcessorsDOCUMENTATION Fargate loggingDOCUMENTATION AWS Fargate profileDOCUMENTATION