ML-based automated issue management, defect classification and bug triaging.
Building a distributed and scalable ML-enabled backend on top of Apache Ignite, Ray Serve, Scikit-learn and PyTorch.
Local development with Apache Ignite made simpler on Arch Linux.
Peter Gagarinov shares his experience with integrating Apache Ignite with external machine frameworks.
Peter shares his Apache Ignite experience. He will show how one can minimize the number of blocks in a complex, scalable backend for an ML-based, automated issue-management system (Alliedium), as you stay within the Java ecosystem and the microservice paradigm.
Making development of distributed and scalable Jira Cloud app backends easier with Apache Ignite and Atlassian Connect Spring Boot.