// DEVOPS session
Leveraging LLMs and machine learning models to instantly catch regressions, optimize test suites, and accelerate deployment workflows.
Speaker C
Senior DevOps Engineer
Traditional continuous integration pipelines often suffer from long build times, flaky automated tests, and manual code review bottlenecks. This workshop introduces AI-driven automation designed to transform modern deployment lifecycles.
What we will cover:
Intelligent Test Impact Analysis: Using ML models to predict modified code paths and execute only the relevant subset of tests.
Automated Regression Diagnostics: Parsing build logs dynamically to identify root causes of failures before human review.
Self-Healing Deployment Scripts: Implementing runtime rollback logic and proactive cluster health monitoring.
Ideal for DevOps engineers and tech leads aiming to cut build pipeline times by up to 40% while maintaining strict quality gates.
// From the community
Moments from this event at Codes For Tomorrow.
