devops-exercises open source analysis
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
Project overview
⭐ 80103 · Python · Last activity on GitHub: 2025-10-07
Why it matters for engineering teams
Devops-exercises addresses the practical challenge of preparing engineering teams for real-world DevOps and site reliability engineering (SRE) scenarios through hands-on practice. It is especially suited for production engineers, SREs, and DevOps specialists who need to strengthen their skills across a broad range of tools including Kubernetes, Terraform, Ansible, and cloud platforms like AWS and Azure. The project has a mature and reliable codebase with a strong community presence, making it a dependable open source tool for engineering teams focused on continuous learning and skill validation. However, it is not the right choice for teams seeking a turnkey production ready solution for infrastructure management, as it is primarily designed for training and interview preparation rather than direct deployment in production environments.
When to use this project
This project is a strong choice when engineering teams want a practical, self hosted option for DevOps training and skills assessment that covers a wide technology stack. Teams looking for automated infrastructure provisioning or monitoring tools should consider specialised production ready solutions instead.
Team fit and typical use cases
DevOps engineers, SREs, and platform engineers benefit most from devops-exercises by using it to simulate real-world operational challenges and improve their proficiency with tools like Docker, Prometheus, and Terraform. It is commonly used in teams managing cloud infrastructure and containerised applications, helping them prepare for production incidents and technical interviews alike.
Topics and ecosystem
Activity and freshness
Latest commit on GitHub: 2025-10-07. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.