DevOps Engineer: Docker, Kubernetes, Jenkins, Terraform, AWS

A warm welcome to The Complete DevOps Engineer Course: Docker, Kubernetes, Jenkins, AWS & Terraform course by Uplatz.

The Complete DevOps Engineer Course: Docker, Kubernetes, Jenkins, AWS & Terraform

Modern software development demands speed, reliability, and collaboration. This comprehensive course takes you from the foundations of DevOps to mastering the tools and practices that power today’s most successful technology companies.

You’ll start by understanding DevOps concepts—why it matters, how it transforms the Software Development Life Cycle (SDLC), and the culture of collaboration it creates. From there, you’ll build a strong foundation with Linux and WSL, essential for any DevOps professional, and manage source code using Git for version control.

Next, you’ll dive into Continuous Integration and Continuous Delivery (CI/CD) with Jenkins, automating builds, testing, and deployments. You’ll then step into the world of Docker, learning to containerize applications for consistency and scalability, before progressing to Kubernetes, the industry standard for orchestrating containerized workloads in production.

Cloud skills are essential for DevOps engineers, so you’ll gain hands-on experience with Amazon Web Services (AWS)—from compute (EC2) and storage (S3) to databases (RDS) and monitoring (CloudWatch). You’ll also learn to deliver reliable and repeatable infrastructure with Terraform, mastering Infrastructure as Code across multiple cloud environments.

The course goes further with observability tools like Prometheus and Grafana to monitor and visualize system performance, and Helm to simplify Kubernetes application management.

By the end of this course, you’ll be able to:

• Design and automate CI/CD pipelines with Jenkins.

• Build and run applications in Docker containers.

• Deploy, scale, and manage workloads with Kubernetes.

• Work confidently with AWS services for cloud-native DevOps.

• Implement Infrastructure as Code using Terraform.

• Monitor and secure your systems with Prometheus, Grafana, and RBAC.

Whether you are a beginner entering DevOps or an IT professional looking to upskill, this course equips you with end-to-end DevOps expertise through hands-on projects, real-world examples, and best practices.

Take the step toward becoming a skilled DevOps Engineer ready for high-demand roles in today’s cloud-driven world.

DevOps Concepts

DevOps is a culture and set of practices that bridge the gap between software development and IT operations. It focuses on collaboration, automation, continuous integration, and continuous delivery (CI/CD). The goal is to deliver software faster, more reliably, and with higher quality by combining development, testing, deployment, and monitoring into a unified workflow.

Linux and WSL

Linux is the backbone of most DevOps environments, providing powerful tools for automation, scripting, and system administration. Windows Subsystem for Linux (WSL) allows running Linux distributions on Windows without a virtual machine, making it easier for developers to practice Linux skills directly on their Windows systems.

Git and Version Control

Git is a distributed version control system that enables teams to track changes in code, collaborate efficiently, and manage software versions. Paired with GitHub or other repositories, Git supports branching, merging, and collaborative workflows that are critical in modern DevOps pipelines.

Jenkins

Jenkins is a widely used open-source automation server for building, testing, and deploying software. It enables Continuous Integration (CI) and Continuous Delivery (CD) by automating workflows through pipelines, plugins, and integrations with other tools. Jenkins helps ensure code changes are tested and delivered quickly and reliably.

Docker

Docker is a containerization platform that packages applications and their dependencies into lightweight, portable containers. Containers ensure that applications run consistently across environments, from development to production. Docker simplifies deployment, improves scalability, and is fundamental to cloud-native and microservices architectures.

Kubernetes

Kubernetes (K8s) is an open-source platform for automating the deployment, scaling, and management of containerized applications. It provides orchestration features such as load balancing, service discovery, rolling updates, and self-healing. Kubernetes is the industry standard for managing containerized workloads in production environments.

AWS (Amazon Web Services)

AWS is the world’s leading cloud platform, offering infrastructure and platform services on demand. DevOps engineers use AWS services like EC2 (compute), S3 (storage), RDS (databases), and CloudWatch (monitoring) to build scalable, secure, and flexible systems. AWS is essential for implementing cloud-native DevOps practices and CI/CD pipelines.

Prometheus and Grafana

Prometheus is an open-source monitoring system that collects time-series data on system and application performance. Grafana is a visualization tool that turns this data into dashboards for real-time monitoring and alerting. Together, they provide observability into DevOps workflows, helping identify and resolve issues quickly.

Terraform

Terraform is an Infrastructure as Code (IaC) tool that enables DevOps teams to define and provision cloud resources using declarative configuration files. It works across multiple cloud providers (AWS, Azure, GCP), ensuring consistent infrastructure deployment, scalability, and version control for infrastructure resources.

Helm

Helm is a package manager for Kubernetes that simplifies deploying and managing applications on a Kubernetes cluster. With Helm charts, DevOps engineers can standardize, version, and reuse complex Kubernetes configurations, making application delivery faster and more manageable.

In Summary

This course covers the full DevOps toolchain: from foundational concepts (DevOps, Linux, Git) to essential CI/CD tools (Jenkins), containerization (Docker), orchestration (Kubernetes, Helm), cloud platforms (AWS), monitoring (Prometheus, Grafana), and Infrastructure as Code (Terraform). Together, these technologies provide a comprehensive skill set for any aspiring or practicing DevOps engineer.

The Complete DevOps Engineer Course: Docker, Kubernetes, Jenkins, AWS & Terraform - Course Curriculum

Topic 1: DevOps Foundations

• Session 1: What is DevOps

• Session 2: What is SDLC

• Session 3: Why DevOps is Required

• Session 4: Overview of Different DevOps Tools

Topic 2: Linux and WSL Essentials

• Session 5: Why Learning Linux is Essential for DevOps Professionals

• Session 6: Introduction to Linux and WSL

• Session 7: WSL Installation And Setup Guide

• Session 8: Essential Shell Commands for Ubuntu (Part 1)

• Session 9: Essential Shell Commands for Ubuntu (Part 2)

• Session 10: Ubuntu File System And WSL Integration

• Session 11: From Nano to Vim to VS Code

• Session 12: Bash Scripting in WSL

• Session 13: Networking in WSL

Topic 3: Source Control and CI/CD Basics

• Session 14: Version Control Systems Using Git

• Session 15: Git Branching, Merging, GitHub, Merge Conflicts and .gitignore

• Session 16: CI/CD Concepts

Topic 4: Jenkins Foundations

• Session 17: Introduction to CI/CD Jenkins

• Session 18: Jenkins Installation and Configuration

• Session 19: Jenkins Essential

• Session 20: Jenkins Pipeline as Code

Topic 5: Networking for DevOps

• Session 21: Network Fundamentals for DevOps - Part 1

• Session 22: Network Fundamentals for DevOps - Part 2

Topic 6: Docker Fundamentals

• Session 23: Introduction to Docker

• Session 24: Docker Basics - Essential Commands and Container Management (Part 1)

• Session 25: Docker Basics - Essential Commands and Container Management (Part 2)

Topic 7: Docker Images and Dockerfile

• Session 26: Working with Docker Images (Part 1)

• Session 27: Working with Docker Images (Part 2)

• Session 28: Working with Docker Images (Part 3)

• Session 29: Custom Docker Images

• Session 30: Advanced Dockerfile Instructions

• Session 31: Dockerfile Best Practices

Topic 8: Docker Data Management

• Session 32: Managing Data in Docker

• Session 33: Working with Docker Volumes

• Session 34: Understanding Bind Mounts

• Session 35: Real-World Example - Web Development Environment

• Session 36: Troubleshooting Common Issues for Docker Data

Topic 9: Docker Networking, Compose and Debugging

• Session 37: Docker Networking

• Session 38: Docker Compose

• Session 39: Docker Debugging and Logs

• Session 40: Docker Image Management

• Session 41: Docker for Development

• Session 42: Docker Tips and Best Practices

Topic 10: Docker Capstone

• Session 43: Docker Real-World Project

Topic 11: Version Control Deep Dive

• Session 44: Introduction to Version Control Systems (extra)

• Session 45: Git Installation and Configuration (extra)

• Session 46: Git Core Commands

Topic 12: Jenkins Integrations and Operations

• Session 47: Jenkins with Docker - Step-by-Step Tutorial

• Session 48: How to Secure Docker with Jenkins

• Session 49: Configuring Git SCM in Jenkins

• Session 50: Jenkins Basic Plugin Management

• Session 51: Jenkins Notifications

Topic 13: Kubernetes Foundations

• Session 52: What is Kubernetes

• Session 53: Kubernetes Key Concepts and Terminology

• Session 54: Kubernetes Architecture Overview

• Session 55: Installing Kubernetes (Local Setup)

• Session 56: First Hands-On Steps with Kubernetes Using Minikube

Topic 14: Kubernetes Workloads and Services

• Session 57: Kubernetes Pods in Depth

• Session 58: Kubernetes Deployments

• Session 59: Kubernetes Services

• Session 60: Kubernetes Labels and Selectors

Topic 15: Kubernetes Namespaces, Data and Config

• Session 61: Kubernetes Namespaces

• Session 62: Running MySQL with Kubernetes

• Session 63: Kubernetes ConfigMaps & Secrets

• Session 64: Kubernetes Volumes Tutorial - Part 1 - Basic Volumes

• Session 65: Kubernetes Volumes Tutorial - Part 2 - Persistent Storage

• Session 66: Kubernetes Volumes Tutorial - Part 3 - StorageClass

Topic 16: Kubernetes Reliability and Workload Management

• Session 67: Kubernetes Probes - Liveness, Readiness, Startup

• Session 68: Kubernetes Resource Management

• Session 69: Kubernetes ReplicaSets and Horizontal Pod Autoscaling (HPA)

• Session 70: Kubernetes Job and CronJob

Topic 17: Kubernetes Security and Networking

• Session 71: Kubernetes RBAC Tutorial

• Session 72: Kubernetes Network Policies

Topic 18: Kubernetes Observability

• Session 73: Kubernetes Logs and Monitoring

Topic 19: Helm and Application Delivery

• Session 74: Introduction to Helm

• Session 75: Simple Web App Deployment on Kubernetes

Topic 20: CI/CD with Kubernetes

• Session 76: CI/CD with Kubernetes

Topic 21: AWS Foundations

• Session 77: Introduction to AWS

• Session 78: Introduction to AWS Management Console and AWS CLI

Topic 22: AWS Core Services

• Session 79: Amazon EC2

• Session 80: Amazon S3

• Session 81: Amazon RDS

• Session 82: AWS CloudWatch

Topic 23: CI/CD on AWS

• Session 83: CI/CD on AWS

Topic 24: Observability with Prometheus and Grafana

• Session 84: Monitoring and Logging with Prometheus & Grafana - Part 1 - Foundations

• Session 85: Monitoring and Logging with Prometheus & Grafana - Part 2

• Session 86: Monitoring Tutorial Series (Part 3) - Overview

• Session 87: Monitoring Tutorial - Part 3A Basic Setup

• Session 88: Monitoring Tutorial - Part 3B Prometheus Setup

• Session 89: Monitoring Tutorial - Part 3C Grafana Dashboards

• Session 90: Monitoring Tutorial - Part 3D Advanced Monitoring

Topic 25: Infrastructure as Code with Terraform

• Session 91: Getting Started with Terraform (Part 1)

• Session 92: Working with Variables and Outputs (Part 2)

• Session 93: Understanding State and Basic AWS (Part 3)

• Session 94: Building Real Infrastructure and Best Practices (Part 4)