DevOps: development–operations approach with AI, Docker and Kubernetes

Course overview

Description generated based on course syllabus and open data.

DevOps is a culture and set of practices that unifies development and operations to deliver small, reliable, and repeatable changes. Combined with AIOps, it strengthens observability and automated anomaly detection.

What DevOps is and how it unifies development and operations

DevOps removes silos across teams, automates the software lifecycle, standardizes infrastructure, and enables transparent flow of changes from code to production.

Core DevOps practices: CI/CD, IaC, containerization, monitoring

• CI/CD: automated build, test, and deploy.
• IaC: Terraform/Ansible for reproducible infrastructure.
• Containerization and orchestration: Docker, Kubernetes.
• Observability: logging, metrics, tracing, AIOps.
• Security in the pipeline: DevSecOps checks and policies.

Who DevOps fits / who it does not

Fits

• Beginners with confident PC use seeking a systematic approach.
• IT newcomers aiming to structure knowledge via practice.
• Practicing engineers (developers, QA, admins) moving to automation.
• Teams and organizations standardizing delivery processes.

Does not fit

• Those avoiding teamwork and process changes.
• When not ready to work with infrastructure, networks, and security.

Problem → outcome in DevOps

• Manual deploys and failures → automated CI/CD pipelines with rollback.
• Unstable environments → IaC provides consistent stages and reproducibility.
• Slow releases → small increments and standardized pipelines.
• Hard incident root cause → monitoring + tracing + AIOps alerts.
• Excess costs → containerization, auto‑scaling, resource optimization.

DevOps compared to alternatives

DevOps vs classic siloed development/operations

• DevOps: shared responsibility, single change pipeline, fast feedback.
• Silo: communication gaps, manual steps, long release cycles.

DevOps vs SRE (Site Reliability Engineering)

• DevOps: culture, practices, process automation.
• SRE: engineering reliability via SLO/SLA/error budgets.
• Together: DevOps processes plus SRE metrics and operational goals.

DevOps vs classic SysAdmin/NoOps

• DevOps: infrastructure as code, pipelines, policy‑as‑code.
• SysAdmin: mostly manual operations and ad‑hoc scripts.
• NoOps: maximal automation; DevOps is the pathway to it.

DevOps + AIOps curriculum outline

• Git, GitFlow; CI/CD pipelines (build, test, deploy).
• Docker images and registries; Kubernetes, Helm, rollout/rollback.
• Terraform/Ansible: IaC, modules, policies, secrets.
• Monitoring and logging: Prometheus, Grafana, Loki, tracing.
• AIOps: anomaly detection, event correlation, incident forecasting.
• Security: container scanners, secret management, access policies.

Expected outcomes of DevOps learning

• A working CI/CD setup for a service with tests and continuous deploy.
• Infrastructure as Code for cloud or on‑prem with managed states.
• Containerized app on Kubernetes with autoscaling and health‑checks.
• Dashboards and alerts plus basic incident response playbooks.
• A practical repository with pipelines and documentation.