DevOps Training With Real-World Projects
Build practical technology skills through instructor-led training, hands-on labs and real-world projects across DevOps, cloud, Kubernetes and AI.
Why This Program Stands Out
- ✓Instructor-Led Live Training with Real-Time Production Labs
- ✓Hands-on practice across Linux, Docker, Kubernetes, CI/CD, AWS & Terraform
- ✓Job-Ready Portfolio Building & Resume Optimization
- ✓End-to-end support from Learning -> Live Projects -> Interviews -> Job Placement
DevOps Training With Real-World Projects
Hands-on Practice & Production Workflows
Our Secret Sauce for Exam and Career Success
Training Mode & Deliverables
Live, 1-to-1, or corporate · Recordings & live labs
Comprehensive Masterclass
Exam-ready + job-ready in one program
Flexible Learning Options
Your pace · 24/7 access · Mentor support
Lifetime Support
Resources, resume & interview prep, placement assistance
Learn DevOps Through Hands-On Practice
Build practical technology skills through instructor-led training, hands-on labs and real-world projects across DevOps, cloud, Kubernetes and AI. Rather than learning isolated command syntax from pre-recorded videos, you build end-to-end continuous integration and continuous delivery (CI/CD) pipelines, orchestrate microservices, and manage resilient cloud infrastructure hands-on.
What You'll Learn
Real-World DevOps Projects
Visual representation of the production project workflows you will build, deploy, and manage hands-on during training.
Project 1 — Automated CI/CD Pipeline Flow
End-to-end continuous delivery workflow from source code to production monitoring
Project 2 — Kubernetes Application Delivery Flow
Enterprise microservices architecture with Ingress controller and auto-scaling
Project 3 — Cloud DevOps & Infrastructure as Code Flow
Declarative multi-cloud provisioning using Terraform & GitHub Actions
DevOps Tools & Technologies
Course Curriculum
Module 1: Linux Administration & Shell Script Automation
Server management, Linux permissions, process monitoring, log analysis, and Bash automation.
Module 2: Version Control & Branching Workflows with Git & GitHub
Trunk-based development, feature branching, pull request policies, merge conflict resolution, and webhooks.
Module 3: Containerization with Docker & Container Security
Building optimized Docker images, multi-stage Dockerfiles, Docker Compose multi-container setups, and image security scanning.
Module 4: Continuous Integration & Continuous Delivery (CI/CD)
Building automated deployment pipelines using Jenkins and GitHub Actions with stage gates, unit testing, and artifact management.
Module 5: Kubernetes Cluster Orchestration (EKS & Local Clusters)
Deploying pods, services, ingress routing, ConfigMaps, Secrets, PersistentVolumes, Helm charts, and Pod Autoscaling.
Module 6: Infrastructure as Code (IaC) with HashiCorp Terraform
Writing modular HCL templates, remote state locking with S3/DynamoDB, multi-environment workspaces, and automated plans.
Module 7: Cloud Operations & Real-Time Monitoring (Prometheus & Grafana)
Metrics collection, custom dashboards, alertmanager notification routing, CloudWatch insights, and incident triage.
Module 8: Capstone Real-World DevOps Production Project
Designing and deploying a high-availability microservices architecture with zero-downtime CI/CD and automated rollback.
What Makes Project-Based DevOps Training Different?
Compare traditional theoretical training with NexGenium's practical project-based learning model.
| Feature | Traditional Learning | NexGenium Project-Based Training |
|---|---|---|
| Learning Focus | Theoretical concepts & slide presentations | Hands-on production implementation & live labs |
| Workflows | Isolated single-tool CLI commands | Complete end-to-end CI/CD & IaC automation |
| Infrastructure Environment | Toy local apps on localhost | Real enterprise AWS/Kubernetes cloud environments |
| Troubleshooting | Scripted happy-path lab exercises | Real-world incident triage, log analysis & debugging |
| Career & Portfolio Outcome | Basic completion certificate | Job-ready portfolio with production project experience |
Who Should Take This Training?
📋 Prerequisites
- ✓Basic Linux command-line operations
- ✓Fundamental understanding of IT infrastructure
- ✓Basic Git knowledge
- ✓Enthusiasm to learn cloud automation
🎓 Training Format
Instructor-Led Live Online Sessions | 6-8 Weeks | Weekend & Evening Batches
Projects & Practical Labs
Production CI/CD Automation Pipeline
Build an automated pipeline that builds, tests, security-scans, and deploys microservices upon every Git commit.
Enterprise Kubernetes Application Delivery
Deploy a multi-tier microservice application to Amazon EKS featuring NGINX Ingress, TLS certificates, and auto-scaling.
Multi-Cloud Infrastructure Codification with Terraform
Provision production-grade VPCs, Kubernetes clusters, and databases across cloud environments using reusable Terraform modules.
Related DevOps Courses & Specialized Modules
AWS DevOps Training
Master AWS CodePipeline, CloudFormation, EKS, and production cloud operations.
Azure DevOps Training
Build multi-stage Azure Pipelines, Bicep, and Azure Kubernetes Service (AKS).
Kubernetes Administrator (CKA)
Certified Kubernetes Administrator prep with cluster management & CNI networking.
Terraform & Infrastructure as Code
Automate multi-cloud infrastructure with HashiCorp HCL & GitHub Actions.
DevSecOps & Secure Pipelines
Integrate security scanning, Trivy, SonarQube, and Zero Trust into deployment pipelines.
Generative AI for DevOps & Cloud
Leverage LLMs for automated incident triage, IaC generation, and self-healing pipelines.
Enterprise Commercial Services & Consulting
Learn how modern DevOps teams manage production cloud infrastructure through our managed DevOps services.
Explore Managed DevOps Services→Want to understand the architecture behind modern cloud deployments? Explore our AI & Cloud Consulting services.
Explore AI & Cloud Consulting→Frequently Asked Questions
Enroll in DevOps Training
Start Your DevOps Learning Journey
Build practical technology skills through instructor-led training, hands-on labs and real-world projects across DevOps, cloud, Kubernetes and AI.