▎Common DevOps Terms

1. CI/CD Pipeline: A set of automated processes that builds, tests, and deploys code changes from a repository to production.

2. Infrastructure as Code (IaC): Managing and provisioning infrastructure (servers, networks, databases) through machine-readable definition files (code) rather than physical hardware configuration.

3. Configuration Management: The process of maintaining consistency and control over software application configurations and their environments. Tools include Ansible, Chef, Puppet.

4. Containerization: Packaging an application and its dependencies into a self-contained unit (container) that can run reliably across different environments. Docker is the most common tool.

5. Container Orchestration: Automating the deployment, scaling, and management of containerized applications. Kubernetes is the industry standard.

6. Cloud Computing: On-demand delivery of IT resources over the internet with pay-as-you-go pricing. Major providers: AWS, Azure, GCP.

7. Virtual Machine (VM): An emulation of a computer system, allowing you to run an operating system and applications on top of another operating system.

8. API Gateway: A server that acts as a single entry point for all client requests to backend microservices, simplifying client interactions and providing security, monitoring, and traffic management.

9. Service Mesh: A dedicated infrastructure layer for making service-to-service communication safe, fast, and reliable, often used in microservices architectures. Examples: Istio, Linkerd.

10. Monitoring: The process of collecting, analyzing, and acting on data about system performance and health. Tools include Prometheus, Grafana, ELK Stack.

11. Logging: The process of recording events that occur within an application or system, crucial for debugging and auditing.

12. Alerting: The system that notifies the operations team when a critical event or threshold breach is detected in the monitoring system.

13. Scalability: The ability of a system to handle an increasing amount of work by adding resources. Horizontal (adding more servers) vs. Vertical (adding more power to existing servers).

14. Availability: The percentage of time a system is operational and accessible. Often measured in "nines" (e.g., 99.99% uptime).

15. Fault Tolerance: The ability of a system to continue operating, perhaps at a reduced level, rather than failing completely when some part of the system fails.

16. Disaster Recovery (DR): A plan and set of procedures to recover and protect a business IT infrastructure in the event of a disaster.

17. GitOps: An operational framework that codifies infrastructure and application configuration management in Git repositories, using Git as the single source of truth.

18. Testing (Unit, Integration, End-to-End): Different levels of automated testing to ensure code quality and functionality before deployment.

19. Release Engineering: The practice of managing and automating the software release process to ensure it is efficient, reliable, and repeatable.

20. Observability: The ability to understand the internal state of a system by examining its outputs (logs, metrics, traces). More comprehensive than just monitoring.