DevOps Pro Syllabus

Infinity’s Curriculum Philosophy

Tomorrow’s DevOps Professional Needs to Know More.
Tomorrow’s DevOps Professional Builds Intelligent Platforms.

A professional who:

  • Understands software delivery from code to production
  • Aligns technology with business requirements
  • Automates development and infrastructure workflows
  • Builds scalable cloud-native platforms
  • Designs CI/CD and GitOps pipelines
  • Orchestrates containerized environments
  • Operates reliable production systems
  • Leverages AI to enhance automation and operations
  • And so much more.

Because:

Tomorrow’s DevOps professional needs to know more.

  • More automation.
  • More infrastructure.
  • More reliability.
  • More scalability.
  • More intelligence.

And that’s exactly what this track builds.

Our goal is to develop DevOps professionals who bridge development, infrastructure, and operations in modern software organizations. As software systems become more distributed and complex, DevOps professionals enable teams to build, deploy, and maintain reliable software throughout the development lifecycle.

Our distinguishing hallmark is a hands-on, delivery-focused approach that combines cloud infrastructure, automation, production practices, and AI-powered workflows. Participants develop the ability to build efficient delivery pipelines, manage scalable environments, and leverage AI tools to improve software delivery and operations.

About The Training

Modern software delivery depends on complex ecosystems of applications, infrastructure, automation, and cloud services. DevOps professionals bridge development and operations, connecting engineering workflows with the systems required to deliver software efficiently, operate reliably, and scale platforms effectively.

The DevOps Pro program provides hands-on experience across the technologies and practices that power modern engineering organizations. Participants develop expertise in cloud platforms, CI/CD automation, container orchestration, monitoring, and production operations while exploring how AI is transforming automation, operational workflows, and software delivery practices.

Through a combination of engineering principles and real-world practices, participants develop the ability to design and optimize delivery pipelines, manage complex cloud environments, and support reliable software platforms at scale.

Foundations of DevOps Engineering

The Foundations stage establishes the software engineering, operating systems, and automation skills required of every DevOps professional. Participants build the technical capabilities needed to support modern software delivery and infrastructure workflows.

Goals & High-Level Skill Set

Software Engineering Foundations

  • Linux administration
  • Shell and Bash scripting
  • Python scripting
  • Programming fundamentals
  • Software Development Lifecycle (SDLC)
  • Git and version control workflows
  • Code management practices
  • Testing methodologies
  • Integration testing
  • Debugging techniques
  • Technical communication

Build & Automation Foundations

  • Build automation
  • Package management
  • Dependency management
  • Artifact repositories
  • Virtual machines
  • Service virtualization
  • Database fundamentals
  • Agile development practices

AI Foundations for DevOps

  • Large Language Model (LLM) fundamentals
  • Prompt engineering
  • AI tools and applications

Cloud Infrastructure & Platform Engineering

Modern software platforms depend on scalable infrastructure, automation, and containerized environments. This stage focuses on the principles and practices required to build, deploy, and manage cloud-native platforms.

Goals & High-Level Skill Set

Cloud & Infrastructure

  • Cloud computing fundamentals
  • Cloud platforms and services
  • Solutions architecture
  • Infrastructure as Code
  • Configuration management
  • Environment management
  • Network fundamentals
  • Load balancing
  • Storage concepts
Containers & Orchestration
  • Container management (Docker)
  • Container orchestration (Kubernetes)
  • Microservices architectures
  • Service deployment
  • Staging environments
  • Production environments

CI/CD & GitOps

  •  
  • CI/CD pipelines
  • GitOps workflows
  • Release management
  • Deployment automation

Production Engineering & AI-Enhanced Operations

Reliable software requires effective monitoring, security, troubleshooting, and continuous improvement. This stage focuses on operating production systems and applying automation and AI to modern DevOps workflows.

Goals & High-Level Skill Set

Reliability & Operations

  • Monitoring and observability
  • System reliability
  • Incident management
  • Production troubleshooting
  • Performance analysis
  • Operational workflows
  • Production best practices

Security & Data Infrastructure

  • DevSecOps principles
  • Infrastructure security
  • Security automation
  • Message queue fundamentals
  • Distributed data infrastructure

AI-Enhanced DevOps

  • AI-assisted operational workflows
  • AI agents and multi-agent architectures
  • Agentic DevOps
  • AI system design and integration
  • Model Context Protocol (MCP)
  • AI-powered automation
  • Intelligent platform operations
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