A solid understanding of operating systems—especially Linux—is essential for DevOps engineers, as most production workloads run on Linux-based environments. This stage focuses on mastering core Linux commands, file system structure, permissions, process management, and basic networking to confidently operate and troubleshoot systems.

• Understand Linux fundamentals (Ubuntu, CentOS)
• Commands: cd, ls, top, ps, grep, chmod, etc.
• File system structure, permissions, networking

Version control is the backbone of DevOps collaboration and automation. DevOps engineers must be proficient with Git and platforms such as GitHub, GitLab, or Bitbucket to manage code, infrastructure, and pipeline definitions as a single source of truth. A clear understanding of branching, merging, pull requests, and rebasing enables safe collaboration, controlled releases, and fast rollbacks. Tools like Git and the GitHub CLI further support automation and integration of version control into CI/CD workflows. Practice Actions as -

• Actively use Git as your primary version control system for application code, infrastructure, and pipeline definitions.
• Work hands-on with GitHub, GitLab, or Bitbucket to manage repositories, issues, and pull/merge requests.
• Practice creating and managing branches for features, releases, and hotfixes using standard branching strategies.
• Gain confidence in merging, rebasing, and resolving conflicts, and use pull requests to enforce reviews and quality checks.
• Master Git & GitHub/GitLab/Bitbucket
• Understand branches, merges, pull requests, rebasing

Scripting is a core DevOps skill that enables automation of repetitive tasks and operational workflows. At this stage, engineers focus on Bash, Python, and YAML to handle file manipulation, text processing, error handling, and regular expressions, forming the foundation for automation and pipeline logic.

• Focus on scripting to automate tasks
• Languages: Bash, Python, YAML
• Learn regex, file manipulation, error handling

Continuous Integration and Continuous Deployment form the core execution engine of DevOps, enabling teams to deliver changes frequently, safely, and predictably. At this stage, engineers learn to design automated pipelines that validate code through testing, package artifacts, and deploy them across environments with minimal manual intervention.

• Understand what Continuous Integration and Continuous Deployment mean
• Learn how to build pipelines for test → build → deploy

Configuration management focuses on maintaining consistent, repeatable system states across environments through automation. DevOps engineers learn to use idempotent definitions, playbooks, and state management to provision, configure, and update servers reliably without configuration drift.

• Automate infrastructure and server configurations
• Concepts: idempotence, playbooks, state files

Containers enable applications to be packaged with their dependencies for consistent execution across environments, while orchestration platforms manage them at scale. At this stage, DevOps engineers learn Docker fundamentals and commands, then progress to Kubernetes concepts such as pods, deployments, services, and volumes to run resilient, scalable workloads in production.

• Learn how to containerize applications
• Understand Docker architecture and commands
• Dive into Kubernetes (pods, deployments, services, volumes)

Cloud platforms form the execution backbone of modern DevOps. Mastering at least one major cloud provider enables you to design scalable infrastructure, automate environments, integrate CI/CD pipelines, and operate production systems with reliability, security, and cost awareness. The goal is not tool exposure, but operational fluency.

AWS is the most widely adopted cloud and a common default in DevOps roles. It offers deep service maturity and fine-grained control, making it ideal for learning core cloud and DevOps primitives at scale.

Key focus areas include EC2 (compute), S3 (storage), VPC (networking), IAM (identity and access), CloudWatch (monitoring), and EKS (managed Kubernetes).

Azure is strong in enterprise, hybrid-cloud, and Microsoft-centric ecosystems. It integrates well with Active Directory, Windows workloads, and enterprise governance models, making it popular in large organizations.

DevOps engineers typically work with Azure VMs, Blob Storage, Virtual Networks, Azure Monitor, and AKS, along with Azure DevOps pipelines and GitHub Actions.

GCP is known for its Kubernetes-first design and clean, opinionated abstractions. It is widely used in data-heavy, cloud-native, and platform-driven environments.

Core services include Compute Engine, Cloud Storage, VPC, Cloud Monitoring, and GKE, which is often considered the reference implementation for managed Kubernetes.

Infrastructure as Code enables teams to provision and manage cloud resources using version-controlled definitions instead of manual configuration. This approach ensures repeatability, traceability, and consistency across environments while allowing infrastructure changes to follow the same review and deployment workflows as application code.

Define infrastructure using code (repeatable & version-controlled)

Site Reliability Engineering extends DevOps by applying engineering principles to system reliability and operations. At this stage, engineers learn to define and measure SLIs and SLOs, manage error budgets, and handle incidents systematically. Practices such as chaos engineering and load testing help validate system resilience under real-world failure conditions.

• Security scanning in pipelines
• Secrets Management
• IAM, roles, and access policies

Monitoring and logging provide the visibility required to operate systems reliably in production. DevOps engineers learn to track performance, availability, and errors through metrics, logs, and traces. Dashboards, alerts, and structured log analysis enable faster incident detection, diagnosis, and resolution.

• Track performance, uptime, and incidents
• Set up dashboards, alerts, and log analysis

Site Reliability Engineering focuses on maintaining system reliability through measurable objectives and disciplined operations. At this stage, engineers learn to define SLIs and SLOs, manage error budgets, and handle incidents using structured response and postmortem practices. Techniques such as chaos engineering and load testing are applied to proactively validate resilience and performance under failure and peak load conditions.

• Learn SLOs, SLIs, Error Budgets, incident management
• Implement chaos engineering, load testing

Effective DevOps practices rely heavily on strong communication and cross-functional collaboration. Engineers must understand Agile, Scrum, and Kanban methodologies to align delivery with iterative planning and continuous feedback. Working closely with development, QA, product, and business stakeholders ensures shared ownership of outcomes. Clear communication during planning, delivery, and incidents is critical to building trust and sustaining high-performing teams.

• Master Agile, Scrum, and Kanban methodologies
• Work effectively with dev teams, QA, and business teams