Learn cloud and DevOps by building the pipeline, not watching one.
Live, instructor-led classes on AWS, Docker, Kubernetes, Terraform and CI/CD — every module ends in a real lab, on real cloud infrastructure, not a quiz.
Cloud and DevOps are practiced skills, not memorized ones.
You won't learn to run a production Kubernetes cluster from slides. Every class is built around a lab: you provision it, break it, fix it, and tear it down.
Real infrastructure
Labs run on actual AWS, Azure and GCP accounts — the same consoles, CLIs and quirks you'll face at work.
Build, don't just watch
Each session ends with something deployed: a pipeline, a cluster, a monitored service — not a completed slide deck.
Instructor in the loop
Get unblocked live when a terraform apply fails or a pod won't start — the errors are half the learning.
Pick a track based on where you're starting.
All courses are cloud and DevOps only — no general programming detours. Move between tracks as you progress.
Start here with no prior experience. Linux fundamentals, networking basics, Git, shell scripting, and your first steps into AWS.
Go deep on AWS: build and secure real infrastructure across IAM, VPC, EC2, S3, RDS and serverless with Lambda.
Our flagship track. Docker, Kubernetes, Terraform, CI/CD pipelines and monitoring, tied together into one production-style capstone project.
A focused, advanced track for engineers who already know containers: Helm, GitOps with ArgoCD, service mesh and cluster security.
Build security into the pipeline instead of bolting it on. Container and image scanning, secrets management, policy-as-code, and cloud security posture management.
The order things actually get built in.
Whichever course you start with, the underlying path looks like this — each stage unlocks the next.
Linux & networking fundamentals
The command line, file systems, processes, and how machines actually talk to each other over a network.
Git, scripting & automation
Version control workflows and shell/Python scripting to automate the repetitive parts of infrastructure work.
Cloud platform fundamentals
Core services across AWS, Azure and GCP — compute, storage, identity and networking, and how they map to each other.
Docker & containerization
Packaging applications so they run the same way on your laptop and in production.
Kubernetes & orchestration
Deploying, scaling and managing containerized workloads across a cluster.
CI/CD pipelines
Automating build, test and deploy with tools like GitHub Actions and Jenkins.
DevSecOps & shift-left security
Baking security into the pipeline itself: image and dependency scanning, secrets management, and policy-as-code with tools like OPA.
Infrastructure as code
Provisioning and managing infrastructure reproducibly with Terraform and Ansible.
AI in DevOps
Where AI actually helps day to day: AI-assisted incident response, anomaly detection, and copilots inside the CI/CD workflow — and where it doesn't.
Monitoring & observability
Knowing what's actually happening in production with Prometheus, Grafana and logging pipelines.
Capstone project
Design, build and deploy a full cloud/DevOps project end to end — the centerpiece of your portfolio.
Trending in cloud & DevOps right now.
The curriculum isn't frozen in 2019. These are the shifts we build into the courses above, not a separate add-on.
DevSecOps
Security has moved from a final gate to a step in every pipeline stage — scanning, secrets and policy checks run before code ships, not after.
AI in DevOps (AIOps)
AI-assisted anomaly detection, incident response and pipeline copilots are moving from experiments into standard team tooling.
Platform engineering
Internal developer platforms package cloud, CI/CD and observability behind self-service tooling, so teams ship without waiting on ops.
GitOps
Declarative, Git-driven deployment with tools like ArgoCD and Flux is now the standard way production Kubernetes clusters are managed.
FinOps
Cloud spend is treated as an engineering concern — tagging, budgeting and rightsizing built into how infrastructure gets designed.
Observability 2.0
Beyond dashboards: AI-assisted analysis of metrics, logs and traces that helps predict failures instead of just reporting them.
Built for people who want to be able to do the job.
Developers who want to own deployment and infrastructure, not just hand it off.
System admins moving from on-prem into cloud and automation.
Career-switchers with no prior cloud experience, starting from the foundations track.
Engineers preparing for AWS, Kubernetes or DevOps certifications who want real lab practice first.
"We built CloudProClasses because the industry doesn't hire people who just know what AWS or Kubernetes is—they hire the engineers who can build, secure, and scale it on day one. Hands-on learning is the only bridge between theory and a high-impact career"
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