DevOps and Software Engineering Fundamentals
Domain 1: DevOps and Software Engineering Fundamentals
This domain tests whether you understand DevOps as a sociotechnical operating model, not a toolchain. Expect questions on CALMS, value streams, feedback, shift-left, and the DORA metrics.
Core rules
- DevOps is a culture and set of practices that shorten the feedback loop between idea and customer value by combining cross-functional teams, automation, and measurement.
- CALMS: Culture, Automation, Lean, Measurement, Sharing. Automation without culture change tends to reproduce the same bottlenecks.
- A value stream maps every step from commit to production; the goal is to remove queue time, handoffs, and approval delays, not just speed up coding.
- Shift-left means moving quality, security, and operability checks earlier and making them automatic. It does not mean eliminating production testing or operations ownership.
- DORA's four keys: deployment frequency, lead time for changes, change failure rate, time to restore service. Throughput metrics pair with stability metrics; optimizing one alone is a trap.
Worked example
A team deploys once a month; 25% of releases require a hotfix, and restoration takes two days. Deployment frequency is low, lead time is high, change failure rate is high, restore time is high. The correct first move is not "buy a CI tool." It is to map the value stream, find the largest queue (for example, a manual change-approval board), and introduce automated testing and smaller batches. Smaller batches reduce failure size and make restore faster.
Traps
- Treating continuous delivery as continuous deployment. Delivery means every change is releasable; deployment to production may still be a business decision.
- Calling a "DevOps team" the answer. That recreates a silo.
- Gaming DORA metrics by redefining "deployment" or excluding failures.
- Assuming DevOps requires public cloud or Kubernetes.