Andreas Grabner currently works with Dynatrace & has 20+ years of experience as a software developer, tester and architect and is an advocate for high-performing cloud scale applications. He is a regular contributor to the DevOps community, a frequent speaker at technology conferences and regularly publishes articles on blog.dynatrace.com.
In his spare time he is hitting the salsa dance-floors of the world.
Since 2015 we at Dynatrace experienced 3 waves of transformation bringing us from DevOps (Speed), via NoOps (Stability) to what we call AI-Supported Autonomous Cloud Enablement (Scale).
While DevOps and our approach to NoOps resulted in 1h Commit to Production and a 93% reduction of end user impacting production issues we had a hard time scaling speed and keeping our quality promise as we went through a 10x growth in size of engineering over the past 5 years.
We forced ourselves to leverage and enhance our deterministic AI engine by integrating it into every phase of our software development life-cycle and providing it as a Self-Service option to our teams. Our engineers get immediate feedback before even committing code. Our SREs use it to enforce SLI/SLO based quality gates between stages. The AI evaluates our canary deployments and supports operations by triggering auto-remediation tasks to bring the system back to a healthy state in case of production issues.
Join this talk and learn more about how you can make AI improve the quality and speed of your delivery, how it can help you automate and elevate quality evaluation and how through fast feedback loops, you can have a positive impact on the next line of code your developers are writing!