Roadmap

1. DevOps Terms

This section covers the foundational concepts and terminology essential for understanding the field.

• Introduction to DevOps: What is DevOps?

• Career Alignment: Is DevOps Good For Me?

• Core Concepts: Familiarization with terms like:

  • Infrastructure

  • Scaling

  • Monitoring

  • Automation

2. Programming / Scripting

This branch is divided into two primary languages: Python and Shell Scripting, categorized by difficulty levels.

A. Python Programming

• Basics:

  • Loops

  • Conditionals

  • Functions

  • OOPs (Object-Oriented Programming)

  • Exception / File Handling

• Intermediate:

  • Boto3 (AWS SDK for Python)

  • Logging

  • Flask (Web Framework)

B. Shell Scripting

• Basics:

  • Automating Backups

  • Copying, Moving, and Transferring Code/Files

  • User Management and Automation

• Intermediate:

  • Integration with AWS CLI

  • Makefiles

  • Integration with other Tools & Services

3. Networking

This section focuses on the connectivity and security protocols required to manage infrastructure.

• OSI Model (Theoretical framework for networking)

• Network Protocols (TCP/IP, HTTP, etc.)

• Subnets / CIDR (IP addressing and network segmentation)

• SSH / SCP (Secure remote access and file transfer)

• SSL / HTTPS (Encryption and secure web traffic)

• Network Troubleshooting (Diagnosing connectivity issues)

• DNS (Domain Name System)

4. Cloud Services

This section focuses on mastering major providers like AWS, Azure, or GCP to manage infrastructure.

• Compute Servers: Managing virtual machines and instances.

• Database Servers: Handling managed and self-hosted database solutions.

• VPCs & Networking: Designing virtual private clouds and network isolation.

• Managed Services: Utilizing platform-specific automated tools.

• IAM / RBAC: Identity and Access Management and Role-Based Access Control for security.

5. Linux Operating System

A deep dive into the environment where most DevOps tools and servers operate.

• Installation / Setup: Basic OS configuration.

• Command Line Interface (CLI): Mastery of the terminal.

• Filesystem / Storage / User Permissions: Understanding directory structures and security.

• Package Management: Using tools like apt or yum.

• Virtualization: Concepts and practical application.

• Utilities & Tools: Power tools like grep, find, awk, and sed.

6. Containers / Orchestration

Focuses on packaging applications and managing them at scale.

A. Docker

• Dockerfiles, Images, Containers: Building and running portable apps.

• Volumes, Networks: Data persistence and inter-container communication.

• Compose, Scout, Init: Multi-container orchestration and environment setup.

B. Kubernetes

• Pods, Deployment, Services, Ingress: Core building blocks of a cluster.

• Storage, PersistentVolumes: Handling stateful data in a cluster.

• Networking Policies: Controlling traffic between services.

• Role Based Access Control (RBAC): Fine-grained cluster security.

• HELM, Kustomize: Package management and configuration for K8s.

• Istio: Advanced service mesh for traffic and security management.

7. CICD Pipelines

Tools and platforms used to automate the build, test, and deployment process.

• Jenkins:

  • Declarative Pipelines

  • Shared Libraries

  • Tools & Plugins

  • Agents

  • Email Alerts

• GitLab:

  • GitLab CI Pipelines

  • Self-hosted Runners

• GitHub:

  • Repositories & Source Code Management

  • GitHub Actions for automation

  • Webhooks for event-driven tasks

• ArgoCD:

  • K8s Deployments (GitOps approach)

  • Workflows and ArgoCD CLI

8. Infrastructure As Code (IaC)

This section focuses on automating the provisioning and configuration of infrastructure through code.

• Terraform:

  • HCL (HashiCorp Configuration Language)

  • Providers (Plugins to interact with cloud APIs)

  • Modules (Containers for multiple resources)

  • State Management (Tracking the current state of infrastructure)

• Ansible:

  • Configuration Management

  • Playbooks (YAML files for task automation)

  • Roles & Templates

9. Monitoring

Essential for maintaining system health, observability, and performance tracking.

• Grafana:

  • Dashboards and Visualization

  • k6 Load Testing (Performance testing tool)

• Prometheus:

  • Metrics collection

  • Alerting (Notification systems)

• ELK Stack:

  • Elasticsearch (Search and analytics engine)

  • Logstash (Server-side data processing pipeline)

  • Kibana Dashboards (Data visualization for Elasticsearch)

10. MLOps

The intersection of Machine Learning, DevOps, and Data Engineering to manage the ML lifecycle.

• KubeFlow: A machine learning toolkit for Kubernetes.

• MLFlow: An open-source platform for managing the end-to-end ML lifecycle.

11. Real World Test (Career & Community)

Practical steps to translate technical skills into professional opportunities.

• LinkedIn:

  • SSI Score (Social Selling Index)

  • Profile Optimisation

  • Posting, Commenting, and Networking

• Resume:

  • ATS Friendly formatting

  • Keywords, Projects, and Best Practices

• Community:

  • Learn In Public

  • Meetups and Events

  • Challenges and Hackathons

• Generative AI tools:

  • Leveraging ChatGPT, Gemini, and Dall-e for productivity and learning.