Using Apache Ignite to boost the development of Jira Cloud apps

Building a scalable, multi-tenant backend for a Java-based, ML-driven Jira Cloud application imposes many requirements on the underlying technology stack. It is not uncommon to fulfill the requirements by combining pieces of technology—such as SQL and NoSQL databases, ORM tools, message brokers, load balancers, caching layers, ML pipelines, and web servers.

In this talk, 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. We show you how to integrate Apache Ignite with Atlassian Connect Spring Boot, and we discuss Apache Ignite features such as SQL and NoSQL queries, thin and thick clients, caching, distributed messaging and events, distributed computations, database-schema change tracking, and Kubernetes deployment.

Peter Gagarinov
Software Architect at Alliedium

Peter is a passionate open-source enthusiast who focuses on machine learning and distributed computational systems.
Peter dedicates his time to working as a consultant for various projects and as a product manager and software architect at Alliedium. Alliedium builds and offers an ML-based, automated issue-management system and provides a defect-classification and bug-triaging service for Atlassian Jira. Peter has devoted 18 years to software development, architecture, machine learning, and applied mathematical modeling for financial and electricity markets.

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