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How Mindbody improved query latency and optimized costs using Amazon Aurora PostgreSQL Optimized Reads
- Mindbody, a technology platform for fitness and wellness businesses, faced scaling and performance challenges due to data growth.
- They adopted Amazon Aurora PostgreSQL Optimized Reads to improve query latency and reduce costs.
- The root cause analysis revealed issues with query performance, CPU utilization, and I/O costs.
- Mindbody transitioned to Aurora Optimized Reads by upgrading the database cluster and creating a proof-of-concept environment.
- Performance improvements included reduced CPU and IOPS usage, leading to better query response times.
- Cost benefits were observed with a 23% reduction in Aurora costs and increased price predictability.
- Aurora Optimized Reads enabled Mindbody to meet performance SLAs efficiently and reduce operational costs.
- By leveraging Optimized Reads, Mindbody improved query performance and cost efficiency in managing large datasets.
- The team successfully transitioned to Aurora PostgreSQL Optimized Reads, enhancing their platform's reliability.
- Users can access the Optimized Reads feature through the Amazon RDS console for better query performance.
- Key contributors include Sandeep Koppula, Rahul Gupta from Mindbody, and Mukesh Agrawal from AWS.
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