Hands-on DevOps & AI Training
An organization wanted to speed up delivery and standardize practices in teams, including effective use of AI tools (e.g. GitHub Copilot), without compromising security and quality. We conducted training and working sessions with real tasks and measured the effect.
Project Goals
Unify DevOps practices (CI/CD, observability, security).
Improve productivity with AI assistance in code/tests.
Define measurable KPIs (cycle time, PR throughput, quality).
Safe rules for using AI (guardrails).
Our Approach
Assessed current maturity and defined target standards and KPIs.
Conducted practical training (hands-on) with real scenarios from the project.
Introduced rules for using AI tools and templates for code review.
Set up measurement (e.g. task completion time, time-to-merge, PR quality) and retrospectives.
Solution
- Practical workshops and internal templates/guidelines.
- Playbook for using GitHub Copilot and AI tools.
- Set of best practices for CI/CD and quality.
- Metrics and process for continuous improvement.
Results
- Clearer standards and easier onboarding of new people.
- Faster delivery on routine tasks and better focus on complex ones.
- Safer and controlled use of AI via rules and measurement.
FAQ
Do AI tools degrade quality?
Is it suitable for non-DevOps teams?
How do you measure impact?
Contact
Do you have a question or want to discuss a project? Write to us.