DevOps Engineer Learning Paths

This repository is a comprehensive educational resource covering the full spectrum of DevOps practices, including continuous integration and delivery, containerization, orchestration, configuration management, and infrastructure as code. It provides structured content that walks through automating the build, test, and deployment lifecycle using multi-stage pipelines with Jenkins and Azure DevOps. The material covers declarative server configuration and state management through automated Ansible playbooks, enabling consistent system environments across machines. It also addresses container lifecycle management with Docker for packaging and deploying applications, alongside Kubernetes for orchestrating containerized workloads with service discovery, scaling, and centralized configuration. Infrastructure provisioning is handled through Terraform, with declarative configuration files and state management for managing cloud resources across AWS, Azure, and Google Cloud. The content is organized as a master-class course format, providing a guided path through these interconnected DevOps domains.

This project is a comprehensive educational curriculum designed to build proficiency across modern infrastructure, cloud-native technologies, and systems administration. It functions as a reference library and interview preparation resource, offering a structured collection of conceptual questions, practical coding challenges, and hands-on scenarios that cover the full spectrum of software delivery and operational workflows. The repository distinguishes itself through a modular, domain-specific structure that links instructional problem statements with verified implementation examples. By employing a standardized documentation schema, it provides a predictable learning path for mastering complex technical concepts, ranging from infrastructure-as-code patterns and container orchestration to cloud platform administration and security best practices. The content spans a wide array of technical domains, including automated configuration management, distributed system monitoring, database operations, and version control. It provides deep dives into specific tooling for cloud provisioning, container networking, and service deployment, ensuring that learners can validate their technical skills through isolated, practical exercises. All instructional materials are organized into a unified taxonomy of markdown-based documents, allowing users to navigate and study specific technical topics at their own pace.

Developer Roadmap is a community-driven platform that provides structured, graph-based learning paths for software engineering. It serves as a comprehensive knowledge repository where technical domains are organized into visual sequences to guide professional skill acquisition and career growth. The project distinguishes itself through a collaborative ecosystem that enables users to contribute roadmaps, curate industry best practices, and maintain professional profiles. It integrates diagnostic assessment frameworks to evaluate technical proficiency, helping developers identify knowledge gaps and prepare for professional interviews through targeted learning sequences. Beyond its core mapping capabilities, the platform offers practical project ideas and interactive tutoring to reinforce engineering concepts. It provides a centralized space for the community to share resources, track progressive skill development, and navigate complex technical landscapes.

This project is a centralized library of community-contributed, declarative configuration files designed for automating the deployment of cloud infrastructure and services. It serves as a repository of machine-readable templates that define the desired state of cloud environments, enabling consistent and repeatable resource provisioning. The collection provides pre-configured scripts that streamline the setup of virtual machines, databases, and networking components. By utilizing these templates, users can standardize the deployment of cloud services and automate the creation of development, testing, and production environments. These templates leverage infrastructure-as-code practices to define resource topologies, ensuring that cloud environments are configured through structured schemas. The repository supports the automation of complex cloud environments by providing verified configurations that reduce manual setup time and configuration errors.

This project is an interactive programming curriculum and educational system designed to teach computer science and software engineering. It provides a structured set of courses and professional roadmaps focused on backend engineering, DevOps, and systems fundamentals. The platform is distinguished by an AI-powered coding tutor that provides Socratic guidance and contextual hints to help students find solutions independently. It features a browser-based code sandbox using WebAssembly to eliminate local environment setup, alongside automated test-based grading and spaced-repetition logic to reinforce difficult concepts. The curriculum covers a broad range of technical domains, including programming languages such as Go, Python, and TypeScript, as well as relational database design, container orchestration with Kubernetes, and cloud operations. It also includes professional development resources for technical interview preparation and portfolio construction. Learning engagement is managed through gamified incentives like experience points and leaderboards, while progress is tracked via sequenced learning paths and AI-generated coding challenges.

DevOps-Roadmap is a comprehensive educational repository and knowledge base designed to guide technical professionals through the complexities of modern software engineering. It functions as a structured curriculum and reference library, covering the full spectrum of skills required to master system architecture, infrastructure management, and cloud operations. The project distinguishes itself by bridging the gap between high-level architectural design and the practical realities of engineering leadership. It provides curated insights into distributed systems, data consistency, and scalable design patterns, while simultaneously offering frameworks for managing high-performing teams, navigating corporate dynamics, and fostering psychological safety within technical organizations. Beyond core architecture, the repository encompasses a broad capability surface that includes professional development, productivity optimization, and the integration of emerging technologies. It offers guidance on implementing AI-driven workflows, managing large-scale machine learning lifecycles, and applying evidence-based metrics to track team performance and development health. The repository serves as a centralized resource for engineers at all career stages, providing access to industry-standard principles, technical interview preparation materials, and strategic coaching frameworks.

Kubernetes The Hard Way is an educational curriculum designed to teach the fundamental architecture and operational requirements of container orchestration platforms. It provides a structured, hands-on learning path that guides users through the manual bootstrapping of a multi-node cluster from scratch, intentionally avoiding automated installers to ensure a deep understanding of how individual control plane and worker node components interact. The project distinguishes itself by requiring the manual configuration of every layer of the infrastructure, including the generation of cryptographic identities for mutual authentication and the establishment of encrypted communication channels between distributed components. Participants gain practical experience in managing distributed key-value consensus, configuring network-overlay routing for pod communication, and handling the lifecycle of system services through manual configuration files. This guide covers the entire provisioning process, from setting up compute resources to implementing security protocols and managing binary-based service deployments. By building the system piece by piece, users develop the operational knowledge necessary to troubleshoot complex failures in production environments. The tutorial requires four virtual or physical machines and provides a comprehensive walkthrough of the steps needed to establish a functional cluster environment.