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Elasticsearch Performance Tuning

Implementation and Support Services for Elasticsearch

Continuously enhancing search is critical to its performance. But the day-to-day maintenance may also take away your internal team’s focus on business goals. 

Search Technologies provides a tuning service engagement for boosting search relevancy and the overall search experience within your Elasticsearch application. This includes system evaluation, sample query testing and adjustments, and a quantitative methodology for improvements.


An Elastic partner, we provide expert services and software tools for Elasticsearch performance tuning. 


  • We have over 200 search and analytics experts who are experienced with Elasticsearch and a broad range of search engines.
  • Using search engine scoring techniques and adjusting the out-of-the-box relevancy algorithms in Elasticsearch can greatly improve search results.
  • Performance tuning also solves many challenges around Elasticsearch, including content processing, indexing, speed, memory tuning, scalability, user behavior analytics, search interface enhancements, performance benchmarking, etc.


  • Content processing: often, when the data being indexed is not optimized for relevancy, content processing prior to indexing can significantly improve the results through data cleansing, normalization, and enrichment. Search Technologies' Aspire is designed specifically for handling structured and unstructured data processing. 
  • Connectors for Elasticsearch: we have an existing range of connectors that work seamlessly with leading search engines and common data repositories. In addition, we can build custom connectors to meet your specific requirements.


Depending on your needs, a typical services engagement may include:


elasticsearch performance tuning

  • A comprehensive assessment of your current Elasticsearch application
  • Gather basic statistics on the documents (number of documents, average size, number of fields, tokens per document, tokens per field, etc.)
  • Gather basic query set statistics (number of tokens per query, types of operators used, etc.)
  • Use sample queries for relevancy tuning - typically a set of 20-30 queries gathered from query logs or via in-person interviews
  • Code configuration, integration, testing, and deployment
  • Performance tuning based on the sample queries
  • Demonstration and reporting on expected improvements
  • A statement of work detailing project’s scope and deliverables 


Our Global Managed Services and Support team provides system monitoring, software maintenance, and support services for your Elasticsearch application as needed. We work with each customer to build a support package that fits their specific needs. Learn more about our managed services here.

Contact us to learn more about our services details and pricing.

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