On August 31st, we presented the integration between Akamas and Dynatrace during the Performance Clinic webinar. This time we went a little more in-depth regarding the technical part, and there was also a demo.
Today’s application development and release cycles are measured in days, and not in months. Configuration options of the tech stack continue to increase in scope and complexity, with dependencies that have become unpredictable. Without automation, Performance engineers and developers can no longer ensure that applications perform as planned, and costs are minimized.
Autonomous Performance Optimization, the novel approach that Akamas proposes, automates the performance optimization process with minimal intervention and oversight from human experts. It uses AI and machine learning techniques to automatically and continuously optimize the technology stack, delivering unprecedented application performance, deployment agility, and cost savings.
In this episode of the Performance Clinic series, Stefano Doni (Akamas) joined Andreas Grabner (Dynatrace) to explain how does Autonomous Performance Optimization work. After that, he explained the practical steps needed to automate optimizations of your enterprise, cloud, or database systems leveraging observability data from Dynatrace.