Deploying and Scaling Microservices in Production
The final step is getting your microservices running reliably in production. This lesson covers the deployment strategies, scaling approaches, and operational practices that keep production systems healthy. You will learn to deploy with zero downtime, scale individual services independently, and set up the monitoring that lets you sleep through the night.
Watch: Video Walkthrough
Key Concepts
- Blue-Green Deployment: Zero-downtime deployments by running two production environments
- Auto-Scaling: Scaling individual services based on CPU, memory, or custom metrics
- Service Mesh: Using Istio or Linkerd for traffic management and security between services
- Infrastructure as Code: Using Terraform or Pulumi with AI assistance to manage cloud resources
Hands-On Exercise
Task: Deploy your microservices stack to a cloud platform (AWS ECS, Google Cloud Run, or Railway). Configure auto-scaling for the Order Service based on CPU utilization. Perform a blue-green deployment of a code change and verify zero-downtime switchover using health check endpoints.
Pro Tips
Start with managed services wherever possible. Use managed databases (RDS, Cloud SQL), managed message queues (SQS, Cloud Pub/Sub), and managed container orchestration (ECS Fargate, Cloud Run). Running your own Kubernetes cluster is only justified at significant scale. Every piece of infrastructure you manage is infrastructure you have to operate at 3am.