Case Study: Algolia achieves optimized operations at scale with VMware Tanzu Wavefront

Wavefront Enables Algolia to Optimize Operations at Scale

Algolia, a search-as-a-service provider handling 12+ billion queries per month for roughly 1,600 customers, needed to monitor a wide set of infrastructure and API metrics (CPU, RAM, I/O, indexing speed, network and inter-provider latency, queue size, crashes, etc.) as usage and scale grew. Existing monitoring tools bogged down at scale, only supported single-metric threshold alerts, and required metrics to be defined up front, leaving no historical data for ad-hoc troubleshooting.

Algolia adopted Wavefront’s SaaS metrics platform, which enables complex multi-stream metrics and alerts (moving averages, derivatives) and stores raw historical data so new, dynamic metrics can be defined and trended retroactively. The result was immediate current and historical visibility, faster debugging of obscure issues (e.g., a DNS/IPv6 problem), real-time customer-facing metrics via Algolia’s interface, greatly reduced alert noise, and the ability to automate resolutions and free up developer and ops time.

Algolia

Julien Lemoine

Co-founder & CTO