DevOps
Culture and practice that connects development (Dev) and IT operations (Ops) – for faster releases, better quality and higher stability.
DevOps is more than a buzzword – it is a cultural shift in how software is developed, tested and operated. Through collaboration between dev and ops, automation and continuous feedback, releases become faster, more reliable and safer. Organisations with mature DevOps often deploy far more frequently and recover from incidents much faster.
What is DevOps?
DevOps is a combination of culture (collaboration instead of silos), practices (CI/CD, Infrastructure as Code, monitoring) and tools (Git, Docker, Kubernetes, Terraform) that unite development and operations. The goal is faster, more reliable releases while keeping systems stable. DevOps is often described with CALMS: Culture (shared responsibility), Automation (automate what you can), Lean (small batches, fast feedback), Measurement (measure and decide on data), Sharing (share knowledge and learn from failures).
How does DevOps work?
DevOps implements a loop: Plan → Code → Build → Test → Release → Deploy → Operate → Monitor → back to Plan. Infrastructure as Code (Terraform, Ansible) makes infrastructure reproducible and versioned. Observability (logs, metrics, tracing) gives real-time insight. Blameless post-mortems after incidents support learning instead of blame.
Practical Examples
GitOps: All infra and app config lives in Git. Changes go through pull requests and are applied automatically.
Immutable infrastructure: Servers are never patched in place; new ones are built and old ones replaced.
Feature flags: New features are deployed behind flags and toggled per user or group – independent of deployment.
SRE: Google-inspired practice with error budgets, SLOs and automation to balance reliability and speed.
Typical Use Cases
Continuous delivery: Automated build, test and deploy pipelines
Infrastructure as Code: Reproducible infra with Terraform, Ansible or Pulumi
Containers: Docker and Kubernetes for consistent, scalable deployments
Monitoring: Proactive detection with Datadog, Grafana, Prometheus
Incident management: Automated alerting, runbooks and post-mortems
Advantages and Disadvantages
Advantages
- Faster releases: From weekly/monthly to daily or hourly deployments
- Reliability: Automated tests and monitoring reduce failures and recovery time
- Collaboration: Shared responsibility for the full lifecycle
- Efficiency: Automation removes manual, error-prone steps
- Feedback: Issues are found immediately, not weeks after release
Disadvantages
- Culture change: DevOps needs organisational change and can meet resistance
- Tool overload: Many DevOps tools can be overwhelming
- Learning curve: Docker, Kubernetes, Terraform and observability need expertise
- Upfront cost: Pipelines, automation and monitoring take time to build
- Not for everyone: Very small teams may find the overhead too high
Frequently Asked Questions about DevOps
What is the difference between DevOps and SRE?
How do I measure DevOps success?
Do I need DevOps?
Related Terms
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