Workflow Refactoring: Jobs vs. Service Containers
By decoupling workloads into dedicated job and service containers, we have achieved:- Isolated processing: Batch tasks no longer compete with live services.
- Reduced database load: Production database performance improved significantly.
- Enhanced reliability: Scheduled jobs now complete without conflicts.
Using separate containers for one-off jobs helps maintain consistent performance for core microservices.
Deployment Requirements
Before advancing to the staging and production phases, ensure the following components are in place:| Requirement | Description | Example Command |
|---|---|---|
| Container Registry | Centralized storage for versioned Docker images | docker push registry.example.com/myapp:1.0.0 |
| CI/CD Pipeline | Automated build, test, and deployment workflows | GitHub Actions, GitLab CI, or Jenkins |
| Configuration Files | Kubernetes manifests or Helm charts | deployment.yaml, service.yaml, values.yaml |
| Cluster Access | kubeconfig and RBAC roles configured | kubectl config use-context staging-cluster |
Verify your
kubeconfig context before running kubectl apply to avoid unintended cluster changes.Kubernetes Fundamentals
Understanding these core Kubernetes resources will streamline our deployment process:| Resource Type | Purpose | Example CLI |
|---|---|---|
| Pod | Smallest deployable unit | kubectl run nginx --image=nginx |
| Deployment | Declarative updates and scaling of pods | kubectl create deployment web --image=myapp |
| Service | Exposes pods internally or externally | kubectl expose deployment web --port=80 |
| Job | Runs batch or one-time tasks | kubectl create job migrate-db --image=alpine |