DevOps Maturity Assessment
Where does your team stand? Use this 5-phase maturity model to benchmark your current DevOps practices and build a roadmap to the next level.
Initial
Ad-hoc and manual
Deployments are manual and inconsistent. No standardised processes, limited documentation, and firefighting is the norm. Infrastructure changes are done by hand through the console.
Characteristics
- Manual deployments via SSH or console
- No CI/CD pipeline
- Minimal or no monitoring
- No Infrastructure as Code
- Knowledge lives in people's heads
How to Advance
- Set up a basic CI/CD pipeline (GitHub Actions or GitLab CI)
- Introduce version control for all code and configuration
- Add basic uptime monitoring (e.g., UptimeRobot, CloudWatch)
Repeatable
Consistent basics
Core processes are documented and repeatable. A basic CI/CD pipeline exists, and infrastructure is partially codified. The team follows some standards but lacks automation.
Characteristics
- Basic CI/CD pipeline in place
- Some Infrastructure as Code (Terraform or CloudFormation)
- Basic monitoring and alerting
- Documented deployment process
- Manual testing before releases
How to Advance
- Automate testing in the CI pipeline
- Codify all infrastructure with Terraform
- Implement structured logging
Defined
Standardised and measured
Processes are standardised across teams. Full CI/CD pipelines with automated testing. Infrastructure is fully codified. Metrics are collected but not yet used for decision-making.
Characteristics
- Full CI/CD with automated tests
- All infrastructure in Terraform/IaC
- Centralised logging and monitoring
- Environment parity (staging mirrors production)
- Deployment frequency: weekly or more
How to Advance
- Define SLOs and SLIs for core services
- Implement distributed tracing
- Introduce automated security scanning
Managed
Proactive and data-driven
The team uses metrics and SLOs to guide decisions. Incident management is mature with blameless post-mortems. Self-service platforms empower developers. Deployments happen multiple times per day.
Characteristics
- SLOs and error budgets drive priorities
- Blameless post-incident reviews
- Self-service developer platform
- Automated canary or blue/green deployments
- Deployment frequency: daily or more
How to Advance
- Implement chaos engineering practices
- Build internal developer experience tooling
- Automate capacity planning
Optimised
Continuous improvement
DevOps practices are deeply embedded in the engineering culture. Continuous improvement is automatic. The team experiments with new tools and practices, and reliability is a competitive advantage.
Characteristics
- Chaos engineering in production
- Fully automated compliance and governance
- Cost optimisation is continuous and automated
- Team contributes to open-source DevOps tooling
- Deployment frequency: on-demand, multiple times per day
How to Advance
- Share learnings through conference talks and blog posts
- Mentor other teams in the organisation
- Explore cutting-edge: eBPF, AI-driven operations, platform engineering
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