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DevOps

AWS DevOps Mastery Program

Linux to Kubernetes — the complete, job-ready DevOps path

About this course

Become a job-ready DevOps engineer. This hands-on program takes you from Linux and shell scripting through Git, CI/CD with Jenkins and GitHub Actions, containers with Docker, orchestration with Kubernetes and Helm, infrastructure as code with Terraform, configuration management with Ansible, and production monitoring with Prometheus and Grafana — all on AWS. You'll work on real-world projects and finish with the practical skills, workflows, and confidence employers expect, backed by job assistance till placement.

Skills & tools you'll learn

Linux

  • Navigate and manage the Linux file system and permissions
  • Manage processes, services, and system resources
  • Configure networking and basic firewall rules

Shell Scripting

  • Automate repetitive operational tasks with Bash
  • Write scripts for backups, deployments, and monitoring
  • Use loops, conditionals, and functions effectively

Python

  • Write automation scripts for infrastructure tasks
  • Build simple tools and CLI utilities
  • Interact with cloud APIs using SDKs like boto3

Git

  • Track changes with commits, branches, and tags
  • Resolve merge conflicts confidently
  • Use rebasing and cherry-picking effectively

GitHub

  • Host and manage source code repositories
  • Automate workflows with GitHub Actions
  • Manage issues, pull requests, and code reviews

Jenkins

  • Build automated CI/CD pipelines
  • Configure jobs, triggers, and webhooks
  • Use declarative Jenkinsfiles for pipeline-as-code

JFrog Artifactory

  • Host and manage build artifacts centrally
  • Set up repositories for Docker, npm, and Maven
  • Manage versioning and artifact promotion

Docker

  • Build and run containerized applications
  • Write efficient, multi-stage Dockerfiles
  • Manage images, volumes, and networks

AWS

  • Provision compute, storage, and networking resources
  • Manage IAM roles, users, and permissions securely
  • Deploy applications using EC2, S3, and VPC

Kubernetes

  • Deploy and manage containerized workloads
  • Configure pods, deployments, and services
  • Scale applications and handle rolling updates

Grafana

  • Build dashboards to visualize system metrics
  • Connect data sources like Prometheus
  • Set up alerts based on thresholds

Prometheus

  • Collect and store time-series metrics
  • Write PromQL queries for monitoring
  • Set up alerting rules and notifications

Ansible

  • Automate configuration management at scale
  • Write playbooks for repeatable deployments
  • Manage inventories of servers and groups

Helm

  • Package Kubernetes applications as charts
  • Manage releases and rollbacks easily
  • Customize deployments with values files