Top 10 DevOps Projects for Your Resume (Beginner to Advanced)
Ten hands-on DevOps projects that hiring managers actually want to see. Covers Docker, Kubernetes, Terraform, CI/CD, AWS, and monitoring — with real code and clear learning outcomes for every level.
Certifications tell employers you studied. Projects tell employers you can do the work.
DevOps hiring managers review hundreds of resumes that list the same tools: Docker, Kubernetes, Terraform, AWS. What separates candidates is evidence — GitHub repositories with working code, architecture diagrams, READMEs that explain real decisions.
Here are 10 projects that build genuine skills and make your resume stand out. They are ordered from beginner to advanced. Do not skip the early ones even if you are experienced. Each one teaches something specific.
Project 1: Containerise a Multi-Service Application
Level: Beginner
Skills: Docker, Docker Compose, Networking
Time: 3 to 5 hours
What you build
Take a real application with at least two components — a web server and a database — and containerise it with Docker and Docker Compose. A good choice is a simple to-do app with a Node.js or Python backend and PostgreSQL or MongoDB.
What to include
- A well-written
Dockerfilefor the application (multi-stage build, non-root user) - A
docker-compose.ymlthat defines the app and database services - A named volume for database persistence
- A custom Docker network for service communication
- Health checks on both containers
- Environment variable configuration via
.envfiles - A
.dockerignoreto keep images lean
What it demonstrates
You understand not just docker run but how to architect a multi-service application for containers, manage data persistence, handle secrets with env vars, and write a production-quality Dockerfile.
README tip
Include the architecture diagram (even a text-based one), the commands to run it locally, and an explanation of why you chose a multi-stage build.
Project 2: CI/CD Pipeline with GitHub Actions
Level: Beginner
Skills: GitHub Actions, Docker, CI/CD
Time: 4 to 6 hours
What you build
A GitHub Actions workflow that automatically tests, builds, and pushes a Docker image to a registry every time code is pushed to the main branch.
What to include
- A workflow triggered on push to
mainand on pull requests - A test job that runs your unit tests
- A build job (dependent on the test job passing) that builds the Docker image
- A push step that sends the image to Docker Hub or GitHub Container Registry (GHCR)
- Image tagging with the git commit SHA for traceability
- Docker layer caching with
cache-from: type=gha - Secrets for registry credentials (no credentials in YAML)
- Branch protection rules requiring the CI check to pass before merging
What it demonstrates
You can build a real CI/CD pipeline that follows security best practices, uses job dependencies correctly, and produces traceable artifacts.
Project 3: Infrastructure as Code with Terraform on AWS
Level: Beginner to Intermediate
Skills: Terraform, AWS, VPC, EC2
Time: 5 to 8 hours
What you build
Use Terraform to provision a complete AWS environment from scratch: a VPC with public and private subnets, an EC2 instance in the public subnet, a security group with proper rules, and an S3 bucket for state storage.
What to include
- A remote backend storing Terraform state in S3 with DynamoDB locking
- A reusable VPC module with public/private subnets across 2+ availability zones
- An EC2 instance with user-data to install and start your application
- Security groups with least-privilege rules (no 0.0.0.0/0 on SSH)
- Outputs exposing the instance public IP and VPC ID
- A
terraform.tfvarsfile for environment-specific values - A
.gitignorefor state files and sensitive data
What it demonstrates
You can write real Terraform beyond tutorials: remote state, modules, proper variable handling, and actual AWS resource creation. This project maps directly to what teams do every day.
Project 4: Deploy to Kubernetes with Helm
Level: Intermediate
Skills: Kubernetes, kubectl, Helm, Deployments, Services, Ingress
Time: 6 to 10 hours
What you build
Take the containerised app from Project 1 and deploy it to a local Kubernetes cluster (using kind or minikube), then to a real cloud-managed cluster (AWS EKS or GKE free tier).
What to include
- Kubernetes manifests: Deployment, Service, ConfigMap, Secret, Ingress
- A Helm chart wrapping all your manifests with templated values
- Horizontal Pod Autoscaler based on CPU utilisation
- Resource requests and limits on all containers
- Readiness and liveness probes
- A
values.yamlfor dev andvalues-prod.yamlfor production - Deployment rollout with
kubectl rollout statusvalidation
What it demonstrates
You understand the difference between writing Kubernetes YAML and packaging applications properly with Helm. HPA and probes show you understand production concerns, not just getting containers to run.
Project 5: End-to-End GitOps Pipeline
Level: Intermediate
Skills: GitOps, ArgoCD or Flux, Kubernetes, CI/CD
Time: 8 to 12 hours
What you build
Implement GitOps: a Git repository is the single source of truth for what is deployed. When you merge a change to the repo, ArgoCD automatically syncs the cluster to match. No kubectl apply in pipelines.
What to include
- A separate GitOps repository that holds only Kubernetes manifests
- An application repository with a CI pipeline that updates the image tag in the GitOps repo on successful build
- ArgoCD installed in your cluster watching the GitOps repo
- Auto-sync with self-healing (ArgoCD reverts manual
kubectlchanges) - An ApplicationSet for managing multiple environments
- A README explaining the full flow: PR merge → CI builds image → manifest repo updated → ArgoCD detects change → cluster updated
What it demonstrates
GitOps is one of the fastest-growing practices in cloud-native. Knowing ArgoCD or Flux puts you ahead of most candidates.
Project 6: Full Observability Stack
Level: Intermediate
Skills: Prometheus, Grafana, Alertmanager, Loki, OpenTelemetry
Time: 8 to 12 hours
What you build
Deploy a complete observability stack for your application: metrics with Prometheus, dashboards with Grafana, log aggregation with Loki, and alerting with Alertmanager.
What to include
- Prometheus configured to scrape your application metrics endpoint
- A custom Grafana dashboard showing request rate, error rate, latency (RED metrics)
- An Alertmanager rule that fires when error rate exceeds 5% for 5 minutes
- Loki receiving structured JSON logs from your application
- A Grafana LogQL query correlating logs with spikes in error metrics
- A runbook document explaining what each alert means and how to respond
What it demonstrates
Most engineers can run a service. SREs and senior DevOps engineers can observe it. This project shows you understand the difference between a dashboard that looks impressive and one that helps you find and fix problems.
Project 7: Automated AWS Infrastructure with Terraform and CI/CD
Level: Intermediate to Advanced
Skills: Terraform, AWS, GitHub Actions, remote state, modules
Time: 10 to 15 hours
What you build
Combine Terraform and CI/CD: a pipeline that automatically runs terraform plan on pull requests (posting the plan as a PR comment) and terraform apply on merge to main.
What to include
- A modular Terraform codebase: separate modules for VPC, compute, database, and IAM
- GitHub Actions workflow using
hashicorp/setup-terraform terraform planoutput posted as a PR comment usingactions/github-scriptterraform applyrunning only on merge to main- AWS credentials passed via OIDC (not static keys — this is the modern, safer approach)
- Separate Terraform workspaces for dev and prod environments
- A Checkov or
tfsecsecurity scan step in the pipeline
What it demonstrates
This project combines two high-demand skills: Terraform expertise and pipeline automation. The OIDC authentication (no static AWS access keys) shows you understand security best practices.
Project 8: Self-Healing Infrastructure with Auto Scaling
Level: Advanced
Skills: AWS, Terraform, Auto Scaling, Load Balancers, CloudWatch
Time: 10 to 15 hours
What you build
An AWS application that automatically scales up under load and scales down when traffic drops, with zero-downtime deployments and a health check that routes traffic away from unhealthy instances.
What to include
- An Application Load Balancer with HTTPS (ACM certificate)
- An Auto Scaling group with a launch template
- Scale-out policy triggered by 70% average CPU
- Scale-in policy triggered by 30% average CPU
- CloudWatch dashboard for the ASG and ALB metrics
- A rolling deployment strategy (new instances, health check, traffic shift, old instances terminated)
- Everything provisioned with Terraform
What it demonstrates
You understand how production applications actually handle variable load. This project demonstrates cloud architecture skills that go beyond tutorials.
Project 9: Multi-Environment Kubernetes Platform
Level: Advanced
Skills: Kubernetes, Terraform, EKS, namespaces, RBAC, network policies
Time: 15 to 20 hours
What you build
A Kubernetes platform with separate namespaces for dev, staging, and production environments — with proper RBAC so developers can deploy to dev/staging but not production, network policies isolating environments, and resource quotas.
What to include
- AWS EKS cluster provisioned with Terraform (using the official EKS module)
- Three namespaces:
dev,staging,production - RBAC: developer role with deploy access to dev/staging, SRE role with full access
- Network policies: pods in
devcannot communicate with pods inproduction - LimitRange and ResourceQuota on each namespace
- Cluster Autoscaler for automatic node scaling
- External Secrets Operator syncing secrets from AWS Secrets Manager
- A CI/CD pipeline that promotes images from dev → staging → production with manual approval gates
What it demonstrates
Platform engineering skills. You are not just deploying applications — you are building the platform that other engineers deploy to. This is what senior DevOps and platform engineering roles actually require.
Project 10: Full-Stack DevOps Deployment
Level: Advanced
Skills: All of the above combined
Time: 20 to 30 hours
What you build
Everything, end to end. A microservices application (at least two services that communicate with each other), deployed to Kubernetes on AWS, provisioned with Terraform, deployed via GitOps, monitored with Prometheus and Grafana, with a CI/CD pipeline that goes from commit to production with all the right gates.
What to include
- Two or more services (e.g. an API and a worker) in separate repositories
- Terraform for all AWS infrastructure (VPC, EKS, RDS, ECR, Secrets Manager)
- GitOps with ArgoCD for deployments
- CI pipeline per service: test, build image, push to ECR, update GitOps repo
- Prometheus and Grafana for metrics (using the Prometheus Operator Helm chart)
- Loki for logs
- Alertmanager rules with a Slack or email notification
- HTTPS via cert-manager and Let's Encrypt
- Documentation: architecture diagram, runbook, deployment guide
What it demonstrates
This is a portfolio centrepiece. It touches every skill on a DevOps job description. Done well, with thorough documentation and a clear README, this is the kind of project that gets interviews.
How to present projects on your resume
GitHub is your portfolio. Make every repository public. Write a README that covers:
- What the project does (one paragraph)
- Architecture diagram (tools like draw.io or Excalidraw are free)
- Technologies used (bullet list)
- Key decisions and why you made them
- How to run it locally
- What you would do differently with more time
Do not list tools. Show outcomes.
Weak: "Used Terraform, Docker, and Kubernetes"
Strong: "Provisioned a multi-environment AWS EKS platform with Terraform, reducing environment provisioning time from 3 hours of manual steps to under 10 minutes"
Keep it real. Recruiters and hiring managers have seen every cloud tutorial project. What stands out is evidence of problem-solving: something that broke, what you discovered, what you changed.
Where to start
If you are new to DevOps, start with Project 1. Build each project before moving to the next. Resist the urge to jump to Kubernetes before you are comfortable with Docker.
Use these resources to get the foundation right:
Frequently asked questions
What DevOps projects should I put on my resume?
Focus on projects that demonstrate the full deployment lifecycle: containerise an app, build a CI/CD pipeline that deploys it, provision the infrastructure with Terraform, and add monitoring. One well-documented end-to-end project is worth more than ten shallow ones.
Do I need AWS for DevOps projects?
AWS experience is the most in-demand, but Azure and GCP are equally valid. What matters is demonstrating cloud infrastructure skills — VPCs, compute, managed services, IAM. The specific provider matters less than showing you understand the concepts.
Should I put personal projects on a DevOps resume?
Absolutely. Personal projects, especially ones on GitHub with clear READMEs explaining what you built and why you made certain decisions, are taken seriously by hiring managers. They demonstrate initiative and real skills beyond certifications.
How do I show DevOps projects if I have no work experience?
Build the projects in this guide, host the code on GitHub, write a README for each one that describes the problem it solves, the architecture, the tools used, and the challenges you faced. This becomes your portfolio. Link it on your CV and LinkedIn.