Performance Optimization After Elasticsearch Migration for Asia’s Largest Matchmaking Platform
Client
The client is a leading matchmaking platform in Asia, serving over 35 million users globally through web and mobile apps. With massive user engagement and real-time search needs, the platform relies on Elasticsearch for matchmaking intelligence.
Project Context
After migrating from AWS to GCP, the client experienced performance issues in their Elasticsearch cluster. The in-house team lacked the depth of Elastic tuning experience needed to stabilize operations.
Challenges
Performance dropped after migration due to mismatch in underlying infrastructure
47-node cluster was not delivering expected throughput
Solution
Compared AWS and GCP setups to identify resource mismatches
Recommended optimal node configurations and performed benchmarking
Improved cluster layout and indexing patterns
Project Objectives
Identify root causes of latency and slow response post migration
Optimize hardware sizing and storage configuration
Improve query speed at scale
Solution Delivery
SquareShift performed cluster analysis and benchmarking using ES Rally, recalibrated node distribution, and helped the client achieve over 2x improvement in query latency at 90K requests/sec load.
Testimonial
Thanks to SquareShift, our user experience is now faster and more stable than ever
