11 real-world use cases. One production capstone.
You don't just watch Kubernetes, you solve real problems on a real cluster: migrations, security, releases, storage, routing, placement, self-healing, GitOps and AI-assisted review.
01Migrate a Legacy Website to Kubernetes
- You must:
- Create a new namespace
- Deploy the application from scratch with a Deployment YAML
- Create a ClusterIP Service and verify internally
- Organize manifests properly
02Secure Backend Services
- You must:
- Deploy the applications
- Write NetworkPolicies
- Verify allowed and blocked traffic
- Document the testing
03Database Initialization
- You must:
- Create an Init Container
- Delay application startup until the DB is ready
04Blue-Green Release
- You must:
- Deploy the Blue version
- Deploy the Green version
- Create Services
- Switch traffic (no Ingress or Gateway API)
05Externalize Application Configuration
- You must:
- Store configuration in ConfigMaps
- Store passwords in Secrets
- Mount environment variables
- Verify changes without rebuilding images
06Persistent Upload Storage
- You must:
- Create a PV and a PVC
- Mount the storage
- Verify data survives Pod recreation
07Multiple Applications Behind One Gateway
- You must:
- Expose all apps using a Gateway
- Configure HTTPRoute and hostnames
08High Availability Placement
- You must:
- Implement appropriate affinity and scheduling rules
- Validate placement across nodes
09Self-Healing Application
- You must:
- Configure all probes correctly
- Validate behavior during startup, traffic and simulated failures
10New Microservice Onboarding
- You must:
- Create Kubernetes manifests
- Add manifests to a Git repository
- Create an Argo CD Application
- Validate automatic synchronization, with no manual apply
11AI-Assisted Cluster Review
- You must:
- Install K8sGPT and connect Ollama
- Scan the cluster and interpret AI recommendations
- Validate findings manually with kubectl before correcting
GitHub Actions + Argo CD driven problem-solving
Deploy and stabilize a customer-facing static web application using GitHub Actions, Argo CD, Gateway API, Helm and AI-assisted troubleshooting with K8sGPT.
What you do
- Build and test the app through GitHub Actions, push the image to a registry
- Use Argo CD to deploy into the cluster from Git
- Expose the app through Gateway API
- Add runtime controls: requests and limits, probes, affinity, or taints and tolerations
- Package with Helm for a realistic deployment layer
- Break something intentionally, then troubleshoot with kubectl and K8sGPT + Ollama
Real problems to solve
- The app is not coming up after deployment
- One pod keeps restarting
- Traffic is not reaching the service correctly
- The new release causes unstable behavior
What you walk away with, and where you grow
Ten days in, you have real Kubernetes skills and proof. Then you keep growing through our community and freelancing network.
A recognised certificate
Earn a CareerByteCode certificate showing you completed a hands-on, production-focused Kubernetes bootcamp.
11 use cases + a capstone
A portfolio of real deployments you can demo: migrations, GitOps, Gateway API, Helm and AI-assisted troubleshooting.
Production-ready skills
Confident, practical Kubernetes: deploy, scale, secure, automate and debug real workloads.
Grow through our community
Join a global community of engineers. Showcase your work, stay visible to recruiters, and speed up the opportunities that come your way.
Earn through freelancing
Turn your DevOps and Kubernetes skills into income. Strong candidates are invited into our freelancing programs to get paid for real work.
Turn 11 use cases into a Kubernetes portfolio
Build proof you can deploy, automate and debug, then grow through our community and freelancing network.