DevOps is the set of practices and tooling that turns “code that works on my machine” into software that runs reliably in production—with fast feedback, safe change, and predictable operations.
If you already build backend services and understand Docker/CI, you’re close: DevOps is largely about extending your engineering rigor to delivery + infrastructure + runtime. The payoff is leverage: you can ship more often, break less, and debug faster because the system is designed for change.
DevOps is not “ops work.” It’s engineering the path to production and the platform it runs on.
Think of DevOps as four connected layers:
Compute, storage, and networking primitives (VPC/VNet, subnets, routing, IAM, load balancers, DNS). Most production issues trace back to permissions, networking, or capacity.
Containers are the package; Kubernetes is the runtime control plane: scheduling, service discovery, rollout strategies, and resilience patterns.
You define infrastructure the way you define software: versioned, reviewed, reproducible. This is how teams avoid “click-ops drift.”
Pipelines evolve from “build/test” into policy + automation: security scanning, promotion across environments, progressive delivery, and rollback.
Cross-cutting practices: observability (logs/metrics/traces), security (least privilege, secrets), and reliability (SLOs, incident response).
Which description best matches the DevOps “center of gravity” in a modern team?
The key idea is engineering the delivery and runtime system so changes are repeatable, safe, and diagnosable. It’s common to assume DevOps is either “ops does deployments” or “just performance work,” but those miss the broader system of automation, policy, and runtime design. Avoiding vendor lock-in can matter, but treating it as the primary goal often leads to unnecessary complexity.