DASA’s DevOps Competence Model reflects the vision that the role of the IT engineer will become more generic as DevOps teams develop. Anyone of the crew can roughly do the job of another. The key to working in this environment is to recognize that there is a skills and knowledge set that needs to be present in every DevOps team. The distribution of these skills and knowledge may be different per team. However, each team will need to ensure that there is enough of each skill and knowledge area to ensure the service is delivered as required by the customers of the service.
12 Skills and knowledge Areas required for DevOps
The DASA DevOps Competence Model identifies 8 knowledge areas and 4 skills areas that are relevant in DevOps. Every professional operating in a DevOps team requires all 12 competencies in varying degree.
Why DevOps Skills Matter
- Courage: Evangelism, coaching, self-confidence, proactivity, reflection, trust, open discussions, experimentation, fail fast, courage to change.
- Teambuilding: Understand the other’s point of view, collaboration, mutual accountability, common purpose, ability to integrally support the service/product.
- DevOps Leadership: Facilitating teams to high performance, humility, transparency, Service lifecycle mindset, Stakeholder management.
- Continuous improvement: Today we do our work better than yesterday, kaizen mindset, quality at the source, first time right, knowledge-sharing, ability to adapt.
The role of the IT engineer will become more generic as DevOps teams develop and IT people become more multi-skilled. The key to working in this environment is to recognize that a skills and knowledge set is needed on these teams.Niels Loader, Principal Consultant Quint
- Business Value Optimization: Use of the IT service in real life, including direct feedback loop of user comments to team, service level management, definition of done, business activity/performance monitoring, business case management.
- Business Analysis: Functional requirements, non-functional requirements, longer term development of business process (based on translation of market developments), data analysis, and refinement.
- Architecture & Design: Ensuring fit between developments and current situation, overall service design, patterns & styles.
- Programming: Software engineering mastery, everything as code, data management.
- Continuous Delivery: Automated testing, deployment and release management, configuration management, version control, cloud, containerization, feature-driven delivery.
- Test Specification: Design of test cases, test concepts.
- Infrastructure Engineering: Technical monitoring, performance management (e.g load balancing etc.), capacity and availability management, reliability engineering, cloud, containerization.
- Security, Risk & Compliance: Security, service continuity planning.