Case Study: Revinate achieves reliable, lower-cost log analytics with ChaosSearch

Scaling Work-Based Learning with a Data Lake Platform for Log Analytics

Revinate, a global leader in guest data management and intelligence for the travel industry, was struggling as its ELK stack grew more expensive and less stable. As log volume increased, the team spent too much time adding Elasticsearch nodes, reindexing data, and managing shards, while also needing to preserve Kibana familiarity and avoid a steep learning curve for users. ChaosSearch was brought in as a replacement for log analytics.

ChaosSearch implemented a data lake platform that indexes Revinate’s logs directly in its existing Amazon S3 environment, with no data movement or new agents, and allowed the team to keep using Kibana. The result was a reliable, drop-in solution that eliminated outages, removed the need to re-index or shard, and freed up engineering time to focus on product work, while also saving Revinate 30% per month compared with hosting ELK on Amazon EC2.

Revinate

Jason Standiford

Chief Technology Officer