From Apache to Solr to Elasticsearch: The Evolution of Zendesk's Search Experience
Zendesk manages terabytes of customer data in the form of support ticket comments, user data, knowledge base content, etc. In Zendesk's previous search architecture based on Apache Solr 3.6 (pre-cloud), manual sharding, operational overhead, difficulty of schema updates, and lack of near-real time indexing was limiting scalability, performance and development velocity. This talk will provide insights into the reasons Zendesk migrated from Apache Solr to Elasticsearch, the journey, and the lessons learned while building their new search and indexing architecture.
Stefan currently is the lead engineer for the search backend at Zendesk. He loves to tinker on scalable, data driven products, and for over 15 has been had the opportunity to do just that for several Bay Area software startups. He holds a degree in Machine Learning from the University of Bonn, and presently lives with his wife and daughter in Raleigh, North Carolina.