Skip to main content

Technical Skills & Preparation

This section covers the core technical topics you need to master for Platform Engineering, SRE, and DevOps interviews.

🚀 Featured: AI/ML Platform Engineering​

The intersection of AI and infrastructure is creating unprecedented opportunities. Master these specialized skills:

AI/ML Infrastructure​

Why it matters: AI platform engineers command 20-30% salary premiums and work on cutting-edge infrastructure powering the AI revolution.

Core Topics Overview​

Deep Dive Guides​

1. Linux & System Programming​

Essential for understanding how applications interact with the operating system.

Key Resources:

Must-Know Topics:

  • File descriptors, pipes, and sockets
  • Process management and signals
  • Memory management
  • System calls
  • Shell scripting (Bash)

2. Networking​

Understanding networking is crucial for debugging distributed systems.

Key Resources:

Must-Know Topics:

  • OSI model and TCP/IP stack
  • HTTP/HTTPS, DNS, Load Balancing
  • Network troubleshooting (tcpdump, netstat, dig)
  • CDNs and reverse proxies
  • VPNs and network security

3. Containerization & Orchestration​

Docker:

Kubernetes:

4. Cloud Platforms​

AWS:

Google Cloud Platform:

Azure:

5. Infrastructure as Code​

Terraform:

Ansible:

6. CI/CD​

Jenkins:

GitLab CI/CD:

GitHub Actions:

ArgoCD:

7. Monitoring & Observability​

Prometheus & Grafana:

ELK Stack:

8. System Design for Reliability​

Key Resources:

Must-Know Concepts:

  • Load balancing strategies
  • Caching layers
  • Database scaling (replication, sharding)
  • Message queues and event-driven architecture
  • Microservices patterns
  • Failure modes and resilience patterns

9. Programming & Scripting​

Languages to Know:

  • Python - Most common for automation and tooling
  • Go - Increasingly popular for infrastructure tools
  • Bash - Essential for system administration

Resources:

10. Security​

Key Resources:

Hands-On Practice​

Interactive Learning Platforms​

Project Ideas​

  1. Build a CI/CD pipeline from scratch
  2. Deploy a microservices application on Kubernetes
  3. Implement monitoring and alerting for a web application
  4. Create Infrastructure as Code for a three-tier application
  5. Build a disaster recovery solution

Study Plans by Experience Level​

Entry Level (0-2 years)​

  1. Master Linux fundamentals
  2. Learn Docker and basic Kubernetes
  3. Understand one cloud platform (AWS recommended)
  4. Basic CI/CD with Jenkins or GitHub Actions
  5. Python scripting

Mid Level (2-5 years)​

  1. Deep dive into Kubernetes
  2. Master Infrastructure as Code (Terraform)
  3. Multi-cloud experience
  4. Advanced monitoring and observability
  5. System design fundamentals

Senior Level (5+ years)​

  1. Complex system design
  2. Platform engineering concepts
  3. Cost optimization strategies
  4. Security best practices
  5. Leadership and architectural decisions

Additional Study Resources​

Comprehensive Question Banks​

Books for Deep Learning​

  • 📚 "Site Reliability Engineering" - Google's SRE practices
  • 📚 "The Site Reliability Workbook" - Practical SRE implementation
  • 📚 "Accelerate" - DevOps metrics and practices
  • 📚 "The DevOps Handbook" - Implementation guide

Remember: Focus on understanding concepts deeply rather than memorizing answers. Interviewers value practical experience and problem-solving skills over rote knowledge.