Case Study: SEEK achieves scalable, real-time log search across billions of logs with Elastic

SEEK - Customer Case Study

SEEK, a global leader in employment and education marketplaces with 100 million job seeker profiles and over 375 million monthly site visits, faced a growing operational and security challenge: logs were scattered across multiple sources and large flat files, searches were slow and manual, retention was limited, and teams needed a way to search and correlate data to support proactive security, continuous delivery and better end‑user experience.

SEEK ran an Elasticsearch POC and built a distributed, cloud‑hosted cluster with collectors (nxLog, syslog, rivers), Kibana clients, Curator-driven hot‑warm‑cold retention, Shield/AD access controls, Marvel/Watcher monitoring and automated alerts. The production system indexes ~5,000 docs/sec, supports billions of searchable documents with a one‑year retention, and delivers real‑time visualisation and cross‑source correlation—speeding incident investigations (infected devices, fraud, scraping), improving deployment and customer‑response monitoring, and centralising log management.

SEEK

Christopher Phan

IT Security Analyst