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Deploy a Container Service

This tutorial walks you through deploying a DataStream container service on your cloud provider. Select your platform and follow the steps below.

The deployment process is similar across platforms, but each has specific configuration requirements for networking, IAM, and container registries.

Step 1

First, configure your container registry. Push your DataStream image to the registry using the CLI:

aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 123456789.dkr.ecr.us-east-1.amazonaws.com
docker tag datastream:latest 123456789.dkr.ecr.us-east-1.amazonaws.com/datastream:latest
docker push 123456789.dkr.ecr.us-east-1.amazonaws.com/datastream:latest

Step 2

Create a task definition that specifies how your container should run. The task definition includes CPU and memory requirements, networking mode, and environment variables.

CANARY-HEADER-AWS-peak

{
  "family": "datastream-service",
  "networkMode": "awsvpc",
  "containerDefinitions": [
    {
      "name": "datastream",
      "image": "123456789.dkr.ecr.us-east-1.amazonaws.com/datastream:latest",
      "cpu": 512,
      "memory": 1024,
      "portMappings": [
        {
          "containerPort": 8080,
          "protocol": "tcp"
        }
      ],
      "environment": [
        { "name": "DS_REGION", "value": "us-east-1" },
        { "name": "DS_LOG_LEVEL", "value": "info" }
      ]
    }
  ],
  "requiresCompatibilities": ["FARGATE"],
  "executionRoleArn": "arn:aws:iam::123456789:role/ecsTaskExecutionRole"
}

Step 3

Create the service using the ECS CLI. Specify the cluster, desired count, and load balancer configuration:

aws ecs create-service \
  --cluster datastream-prod \
  --service-name datastream-api \
  --task-definition datastream-service:1 \
  --desired-count 3 \
  --launch-type FARGATE \
  --network-configuration "awsvpcConfiguration={subnets=[subnet-abc123],securityGroups=[sg-xyz789],assignPublicIp=ENABLED}"

Step 1

First, configure your container registry. Push your DataStream image to the registry using the CLI:

gcloud auth configure-docker
docker tag datastream:latest gcr.io/my-project/datastream:latest
docker push gcr.io/my-project/datastream:latest

Step 2

Create a service configuration that specifies how your container should run. The configuration includes CPU and memory requirements, scaling parameters, and environment variables.

CANARY-HEADER-GCP-valley

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: datastream-api
  namespace: default
spec:
  template:
    spec:
      containers:
      - image: gcr.io/my-project/datastream:latest
        ports:
        - containerPort: 8080
        resources:
          limits:
            cpu: "1"
            memory: "1Gi"
        env:
        - name: DS_REGION
          value: "us-central1"
        - name: DS_LOG_LEVEL
          value: "info"

Step 3

Deploy the service using the gcloud CLI:

gcloud run deploy datastream-api \
  --image gcr.io/my-project/datastream:latest \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated \
  --memory 1Gi \
  --cpu 1 \
  --min-instances 1 \
  --max-instances 10

Step 1

First, configure your container registry. Push your DataStream image to the registry using the CLI:

az acr login --name datastreamregistry
docker tag datastream:latest datastreamregistry.azurecr.io/datastream:latest
docker push datastreamregistry.azurecr.io/datastream:latest

Step 2

Create a container app configuration that specifies how your container should run. The configuration includes CPU and memory requirements, ingress settings, and environment variables.

CANARY-HEADER-AZURE-ridge

az containerapp create \
  --name datastream-api \
  --resource-group datastream-rg \
  --environment datastream-env \
  --image datastreamregistry.azurecr.io/datastream:latest \
  --target-port 8080 \
  --ingress external \
  --cpu 0.5 \
  --memory 1.0Gi \
  --min-replicas 1 \
  --max-replicas 10 \
  --env-vars DS_REGION=eastus DS_LOG_LEVEL=info

Step 3

Verify the deployment and retrieve the application URL:

az containerapp show \
  --name datastream-api \
  --resource-group datastream-rg \
  --query properties.configuration.ingress.fqdn \
  --output tsv

Verification

After deployment on any platform, verify your DataStream service is healthy by calling the health check endpoint:

curl https://<your-service-url>/health
# Expected: {"status": "ok", "version": "2.4.1"}