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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.

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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 Will

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.

Sameera Mahajani

Sameera is the Sr. Search Engineer at Zendesk Inc. She mainly works on Zendesk search platform, matrics, data analysis, relevancy, etc. Before joining Zendesk, she worked at Turner Broadcasting where she spent 2 years working on the search platform for CNN, TBS, TNT, cartoon network, etc. Outside work, Sameera loves classical music, plays the Violin and is a daring baker.