DevOps Placement Program

About this course

For people who have finished DevOps training but struggle with deeper interview questions about real pipelines. You build one end-to-end system through four DevOps roles, so you can explain how the tools connect.

Prerequisites: Completed DevOps training, with basic Linux, Git and familiarity with one cloud (AWS, Azure or GCP).

6

Learning units

48

Topics covered

4

Projects

11

Tools

1. 1

   Week 1

   AWS, Networking and Terraform Fundamentals

   • AWS account setup, IAM users, roles and policies
   • VPC: public/private subnets, NAT gateway, route tables and internet gateway
   • Security groups vs network ACLs
   • EKS architecture: control plane, node groups, OIDC and IRSA
   • RDS PostgreSQL in a private subnet
   • Terraform state, plan, apply, drift and locking
   • Terraform modules, providers, variables and outputs
   • Remote state in S3 with DynamoDB locking

   Assignment

   AWS setup, then read and diagram a production-style Terraform repository.

2. 2

   Week 2

   Terraform Pipeline and Infrastructure Provisioned

   • GitHub Actions: workflows, jobs, steps, runners, secrets and environments
   • OIDC authentication from GitHub to AWS, with no long-lived keys
   • Terraform CI: fmt, validate, plan-on-PR and apply-on-merge
   • Branch protection, approval gates, state locking and concurrency groups
   • Multi-environment strategy: directory-per-env vs workspaces
   • Trunk-based branching for infrastructure teams
   • Multi-account vs single-account AWS

   Assignment

   Provision your own VPC, EKS, RDS and ECR, then make four infrastructure changes through separate PRs.

3. 3

   Week 3

   Containers and CI Pipeline with DevSecOps

   • Docker: multi-stage builds, non-root containers and image hygiene
   • Secret scanning with Gitleaks
   • SAST with CodeQL and Semgrep
   • Dependency scanning with OWASP Dependency Check
   • Container vulnerability scanning with Trivy
   • Keyless image signing with Cosign
   • ECR authentication through OIDC, and image tagging strategies
   • Build once, deploy many
   • Two-tier CI, Gitflow hybrid branching and monorepo path filters

   Assignment

   Run the existing CI pipeline green, then add a new microservice with its Dockerfile and CI workflows.

4. 4

   Week 4

   Helm, ArgoCD and DEV Environment Live

   • Kubernetes core: Pod, Deployment, Service, Ingress, ConfigMap and Secret
   • Readiness vs liveness probes
   • Helm chart anatomy
   • Shared chart with per-environment values
   • GitOps: Git as source of truth, drift detection and self-healing
   • ArgoCD architecture, AppProject vs Application
   • Sync policies: automated with selfHeal vs manual
   • External Secrets Operator with IRSA

   Assignment

   Set up DEV, QA and PROD with 8 microservices, and compare the environments.

5. 5

   Week 5

   Image Promotion, Branching Strategies and Rollback

   • Three-tier image promotion: DEV, QA and PROD
   • Why each environment uses a different sync policy
   • Branching strategies for application, infrastructure and GitOps repositories
   • Hotfix flow
   • GitHub environments with required reviewers
   • Rolling updates: maxSurge, maxUnavailable and readiness gates
   • Rollback: git revert vs argocd app rollback

   Assignment

   Promote a code change from a git push through to PROD, then roll it back, with a documented timeline.

6. 6

   Week 6

   Monitoring, Observability and Interview Sprint

   • Prometheus and kube-prometheus-stack
   • Spring Boot Actuator and Micrometer
   • Grafana dashboards and the Four Golden Signals
   • RED and USE methods
   • Alertmanager, PrometheusRules and severity-based routing
   • Fluentbit and structured JSON logs
   • SLI, SLO and error budget vocabulary
   • Troubleshooting a deliberately broken cluster, and writing RCAs
   • STAR-format answers, project pitch and resume polishing

   Assignment

   Build the full observability stack, write a runbook and two RCAs, and record a 5-minute project pitch.

Projects you will build

These are training projects. Please describe them honestly as training work on your resume and in interviews.

Tools and technologies

• AWS
• Terraform
• Docker
• Kubernetes (EKS)
• GitHub Actions
• ArgoCD
• Helm
• Prometheus
• Grafana
• Alertmanager
• Fluentbit