Many engineering teams rely on ElasticSearch for search and analytics, but as data volumes grow, so do the challenges of scale, cost, and performance. At Mezmo, we faced this reality head-on, recognizing the need for a more efficient and scalable solution to support our multi-cluster, multi-petabyte telemetry data backend. After extensive evaluation, we made the leap to Quickwit, an open-source, cloud-native search engine for logs.

Watch this webinar to hear how we navigated the transition, the key decision-making frameworks we used, and the architectural challenges we overcame. Whether you're exploring alternatives to ElasticSearch or preparing for your own backend transformation, this session will provide practical insights from a real-world migration.