Using AI / ML to Supercharge Continuous Delivery With Harness and PagerDuty

Harness provides Continuous Delivery as-a-Service, leveraging AI and machine learning to automate deployment and health checks, thereby addressing the complexities often overlooked in manual deployment processes. By using unsupervised machine learning algorithms, such as Hidden Markov Models and KMeans Clustering, Harness can instantly detect anomalies and regressions in application performance and quality from APM and log data, a task that would typically take human engineers hours to accomplish. This automation not only facilitates rapid deployment but also ensures a safety net for rollbacks if new issues are identified. The integration with tools like PagerDuty allows for pre-deployment incident checks, preventing deployments in unstable environments. Steve Burton, a DevOps Evangelist at Harness, emphasizes the platform's ability to enable organizations to deploy quickly without compromising system integrity, drawing on his extensive experience in the field.