Search Performance

Find the real cause of slow or unstable Elasticsearch and OpenSearch workloads

SAB Consulting investigates query latency, indexing behaviour, mappings, shards, resource use and workload design to separate application symptoms from platform root causes.

The problem with search performance

Search latency can come from query design, mappings, shard topology, aggregations, indexing pressure, cache behaviour, hardware, concurrency or application usage. Increasing cluster size may hide the problem without solving it.

What we assess

  • Slow queries and search profiles
  • Query and aggregation patterns
  • Mappings and field types
  • Shard count, size and allocation
  • Routing and index design
  • Refresh and merge behaviour
  • Indexing throughput
  • Heap, CPU, disk and cache pressure
  • Thread pools and queues
  • Application access patterns
  • Relevance and pagination constraints
  • Workload isolation

What you receive

  • Performance baseline
  • Root-cause findings
  • Prioritized query, mapping and architecture changes
  • Capacity and shard recommendations
  • Validation plan
  • Implementation roadmap

Frequently asked questions

Does the audit cover OpenSearch as well as Elasticsearch?+

Yes. The scope can cover either platform and account for version-specific behaviour.

Will the audit include application queries?+

It should. Search performance is often affected by the interaction between application logic and the cluster, not only by infrastructure.

Start with a focused assessment

Share the platform, cost or reliability problem you are trying to solve. SAB Consulting will help define the right assessment, the evidence required and the practical next step.