Benchmark-driven optimizations — How we pushed scalability to the next level in Elasticsearch 8

Elasticsearch 8 has introduced significant benchmark-driven optimizations to enhance scalability and performance, especially for high shard count use cases. Elastic has focused on managing increasing data volumes and higher shard counts while keeping resource usage in check. They have developed specific benchmarks to track improvements in indexing throughput and snapshot performance, utilizing nightly benchmarks to detect both regressions and advancements. By pivoting from bare metal to cloud-based environments for macro-benchmarking, Elastic has achieved notable enhancements, including almost doubling indexing throughput and significantly reducing latency in field capabilities API. Additionally, snapshot performance improvements have been realized, such as a 97% reduction in task time through decreased garbage collection activity, which allows for a larger default snapshot pool size in Elasticsearch 8.6.0. The rigorous benchmarking process ensures that any performance changes, whether positive or negative, are investigated to maintain the reliability and efficiency of Elasticsearch, providing an improved experience for Elastic Cloud customers.

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