Cloud DevOps Engineering
Go from zero to production-ready DevOps engineer in 18 weeks.
- Duration
- 18 weeks
- Duration
- Sessions
- 26
- Sessions
- Labs
- 26
- Labs
- Projects
- 3
- Projects
What You'll Be Able To Do
After completing this course, you will confidently:
- Architect production-grade cloud infrastructure on AWS with networking, IAM, and high-availability patterns
- Provision and manage multi-cloud resources using Terraform modules and remote state
- Automate server configuration and application deployment with Ansible playbooks and roles
- Build optimized Docker images and implement container security scanning with Trivy
- Deploy and operate microservices on Kubernetes using Deployments, Services, Ingress, and Helm charts
- Design end-to-end CI/CD pipelines with GitHub Actions and implement GitOps delivery with ArgoCD
- Set up production observability with Prometheus metrics, Grafana dashboards, and centralized logging
- Troubleshoot production incidents using war-room methodology and present a capstone project for interviews
What You'll Build
Real portfolio projects that showcase your skills to employers.
Multi-Tier Web Application on AWS
Design and deploy a three-tier web application on AWS using VPC, ALB, EC2 Auto Scaling Groups, and RDS. Implement blue-green deployment with Route 53 weighted routing.
Interview value:
Demonstrates end-to-end AWS architecture skills that are the baseline expectation for any cloud engineering role.
Kubernetes Microservices Platform
Containerize a microservices application, deploy to EKS with Helm charts, set up Ingress with TLS, implement HPA auto-scaling, and add Prometheus/Grafana monitoring.
Interview value:
Shows Kubernetes production readiness — the single most asked topic in DevOps interviews today.
Full GitOps CI/CD Pipeline (Capstone)
Build a complete GitOps pipeline: GitHub Actions for CI, ArgoCD for CD, Terraform for infrastructure, Ansible for configuration, Docker for packaging, and Kubernetes for orchestration. Includes monitoring, alerting, and a disaster recovery runbook.
Interview value:
The capstone integrates every skill in the course and serves as the centerpiece of your interview portfolio.
Course Curriculum
18 weeks of structured, hands-on learning.
1Foundation Alignment & DevOps Mindset
- DevOps principles and the SRE mindset
- SDLC evolution — waterfall to DevOps to platform engineering
- Environment setup — WSL, Docker Desktop, VS Code, AWS CLI
- Baseline assessment and personalized learning roadmap
2Linux Internals & Networking Fundamentals
- Linux process model, file-system hierarchy, permissions, and systemd
- Shell scripting — variables, loops, functions, cron automation
- TCP/IP, DNS resolution, HTTP lifecycle, and firewall rules
- SSH key management, port forwarding, and secure file transfer
3Networking Deep Dive & Manual EC2 Deployment
- Subnetting, CIDR blocks, NAT gateways, and routing tables
- Load-balancer architectures — L4 vs L7, health checks, sticky sessions
- Manual deployment workflow on a single EC2 instance
- Troubleshooting network connectivity with tcpdump, netstat, and traceroute
4AWS Cloud Fundamentals — IAM & VPC Architecture
- AWS global infrastructure — regions, AZs, edge locations
- IAM deep dive — users, groups, roles, policies, and least-privilege design
- VPC architecture — subnets, route tables, internet gateways, NAT gateways
- Security groups vs NACLs — stateful vs stateless filtering
5AWS Compute, Storage & Load Balancing
- EC2 instance types, AMIs, user data, and launch templates
- S3 buckets — lifecycle policies, versioning, cross-region replication
- Application Load Balancer — target groups, path-based routing, HTTPS termination
- Auto Scaling Groups — scaling policies, cooldown, and predictive scaling
6AWS Database, DNS & Cost Optimization
- RDS — Multi-AZ, read replicas, parameter groups, and backup strategies
- Route 53 — hosted zones, record types, routing policies, health checks
- Secrets Manager and Parameter Store for credential management
- CloudWatch metrics, alarms, and AWS cost optimization strategies
7Azure & Multi-Cloud Fundamentals
- Azure resource model — subscriptions, resource groups, regions
- Azure Virtual Networks, NSGs, and Azure Load Balancer
- Azure DevOps Pipelines overview and multi-cloud strategy
- GCP overview — Compute Engine, Cloud Run, GKE basics
8Terraform Fundamentals & State Management
- IaC philosophy — why Terraform over CloudFormation and Pulumi
- HCL syntax, providers, resources, data sources, and outputs
- State management — remote backends, state locking, import
- Variables, locals, and conditional expressions
9Terraform Modules & Multi-Cloud IaC
- Module design patterns — composition, reusability, and versioning
- Terraform workspaces and environment separation
- Terraform for Azure — resource groups, VNets, and VMs
- Terraform best practices — code review, plan output, and drift detection
10Ansible Architecture & Playbooks
- Ansible architecture — control node, inventory, SSH-based agentless model
- Playbook structure — plays, tasks, handlers, and idempotency
- Variables, facts, conditionals, and loops in Ansible
- Terraform + Ansible integration — provisioning then configuring
11Ansible Roles, Vault & Advanced Patterns
- Role directory structure and Ansible Galaxy
- Ansible Vault — encrypting secrets and integrating with CI/CD
- Multi-tier application deployment with roles
- Testing Ansible with Molecule and linting with ansible-lint
12Docker Architecture & Containerization
- Container vs VM — namespaces, cgroups, and union file systems
- Dockerfile best practices — multi-stage builds, layer caching, .dockerignore
- Docker networking — bridge, host, overlay, and DNS resolution
- Docker Compose for multi-container local development
13Container Registries & Security Scanning
- Docker Hub, ECR, and ACR — push, pull, and tag strategies
- Image security scanning with Trivy and Snyk
- Container runtime security — read-only root, non-root users, seccomp profiles
- Image signing and supply-chain security basics
14Kubernetes Architecture & Core Objects
- Kubernetes architecture — control plane, kubelet, kube-proxy, etcd
- Pods, ReplicaSets, Deployments, and rollout strategies
- Services — ClusterIP, NodePort, LoadBalancer, and headless
- Namespaces, labels, selectors, and resource quotas
15Kubernetes Config, Secrets & Storage
- ConfigMaps and Secrets — mounting as volumes and environment variables
- Persistent Volumes, Persistent Volume Claims, and StorageClasses
- StatefulSets for databases and ordered deployments
- Horizontal Pod Autoscaler and Vertical Pod Autoscaler
16Kubernetes Networking, Ingress & Helm
- Ingress controllers — Nginx Ingress, path-based and host-based routing
- TLS termination and cert-manager with Let's Encrypt
- Network Policies for pod-to-pod traffic control
- Helm charts — templating, values files, and chart repositories
17EKS Deployment & CI/CD Pipeline Design
- EKS cluster provisioning with Terraform and eksctl
- EKS networking — VPC CNI, ALB Ingress Controller, and IAM for Service Accounts
- CI pipeline design with GitHub Actions — build, test, scan, push
- CD pipeline design — deployment strategies (rolling, blue-green, canary)
18GitOps, Observability & Capstone
- ArgoCD GitOps — application sets, sync policies, and rollback
- Prometheus metrics collection, PromQL, and alerting rules
- Grafana dashboards, data sources, and alert channels
- Centralized logging with Loki or EFK stack
- Capstone project presentation and interview preparation
Hands-On Labs Included
You build these yourself — guided exercises with real tools, not passive demos.
Linux Command Mastery
Docker Lab2 hours
VPC Architecture Build
AWS Free Tier3 hours
Uses AWS Free Tier. Terminate resources after lab to avoid charges.
Terraform — Provision AWS VPC + EC2
AWS Free Tier2.5 hours
Uses AWS Free Tier. Run terraform destroy after lab.
Dockerfile Mastery — Multi-Stage Builds
Docker Lab2 hours
K8s Fundamentals — Deploy a Microservice
Docker Lab2.5 hours
GitHub Actions CI Pipeline
Docker Lab2 hours
ArgoCD GitOps Deployment
Docker Lab2.5 hours
Prometheus + Grafana Observability Stack
Docker Lab2.5 hours
Who Is This For?
Freshers & Graduates
Just graduated or finishing your degree? This course gives you the practical skills and portfolio projects that campus placements and entry-level interviews demand.
Career Switchers
Moving from another domain into tech? The structured curriculum and real-world projects bridge the gap between theory and what employers actually look for.
Ideal If You Are:
- Fresh graduates from CS, IT, or related engineering disciplines
- IT support and system administration professionals moving into DevOps
- Manual testers and QA engineers transitioning to automation and infrastructure
- Backend developers who want to add cloud and infrastructure skills
Prerequisites
- Basic familiarity with the Linux command line (ls, cd, grep, ssh)
- Understanding of how web applications work (HTTP, client-server model)
- A laptop with at least 8 GB RAM and a stable internet connection
- An AWS Free Tier account (setup guided in Week 1)
Career Support Included
We don't just teach you — we help you land the job.
Mock Interviews
Practice with real-world interview scenarios. Get feedback on technical depth, communication, and problem-solving approach.
Resume Review
One-on-one review sessions to craft a resume that highlights your projects, skills, and achievements the right way.
Portfolio Coaching
Guidance on presenting your course projects as professional portfolio pieces that stand out to hiring managers.
LinkedIn Optimization
Tips and templates to optimize your LinkedIn profile so recruiters find you and reach out.
Learn from Industry Practitioners
Our instructors are working professionals who build production systems daily. They bring real-world experience, battle-tested patterns, and the kind of practical insight that textbooks can't teach.
Course Details
| Format | Live Online |
|---|---|
| Duration | 18 weeks |
| Schedule | 26 sessions |
| Batch Size | Max 15 students |
| Certificate | Yes, on completion |
| Lab Setup | Docker-based (runs on your laptop) |
| Price | Enquire for pricing |
Frequently Asked Questions
Will I get a job after completing this program?
We cannot guarantee placement, but our curriculum is designed by an architect with 20+ years of hiring experience at Oracle, IBM, Walmart, and Samsung. The program includes resume reviews, mock interviews, and portfolio projects that directly address what hiring managers look for. Graduates who complete all labs and the capstone project are well-prepared for DevOps and Cloud Engineering interviews.
Do I need prior DevOps or cloud experience?
No. The program starts with Linux fundamentals and builds up systematically. You need basic command-line familiarity and an understanding of how web applications work, but no prior AWS, Docker, or Kubernetes experience is required.
What cloud platform does the course focus on?
AWS is the primary platform — approximately 70% of hands-on work is on AWS. Azure is covered as a secondary platform with dedicated sessions. GCP fundamentals are introduced for multi-cloud awareness. This reflects the job market where AWS dominates but multi-cloud skills are increasingly valued.
Will the labs cost me money on AWS?
Most labs run in Docker containers on your local machine at zero cost. Labs that use AWS are designed for the Free Tier. We provide clear instructions on resource cleanup after every AWS lab. Typical AWS spend for the entire course is under $5 if you follow the cleanup steps.
How are the live sessions structured?
Sessions run twice a week, each lasting 1.5 to 2 hours. The instructor covers architectural concepts and design reasoning in the live session. Labs, quizzes, and war-room scenarios are available on the student portal for self-paced practice. All live sessions are recorded and available for replay.
What if I miss a live session?
All live sessions are recorded and uploaded to the student portal within 24 hours. You can watch the recording and complete the associated lab at your own pace. The instructor and teaching assistants are available on Slack for questions between sessions.
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Ready to Start Your Cloud DevOps Engineering Journey?
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