Case Study: Zendesk achieves scalable, easy-to-manage search with Elastic (Elasticsearch)

Zendesk - Customer Case Study

Zendesk faced rapidly exploding search scale — from millions to over a billion tickets and tens of millions of user records — while running a complex, heavily sharded Solr + MySQL architecture that required dozens of clusters, pods and lots of operational work. This made it hard to roll out search features, support new products, and manage configuration and automation at scale.

Zendesk migrated to Elasticsearch and built a centralized search service with partitioned indexes, aliases, incremental indexers and a robust indexing pipeline, plus monitoring via Datadog and Kibana. The new architecture simplified operations, made feature and schema rollout easier, and delivered the scalability and visibility needed to handle their 2015 scale (≈1.1B tickets, ~17M queries/day) with higher indexing throughput and reduced operational complexity.

Zendesk

Stefan Will

Lead Engineer