Blogs

Developer insights and practical how-to articles from our experts to inspire and empower your search experience.

Filters

Build a RAG agent with Elasticsearch and GitHub Copilot SDK

Wire Elasticsearch into the GitHub Copilot SDK as a RAG tool in five lines of C#, grounding your agent in your own logs, docs and data instead of model training data.

Greg Crist

Multilingual image search with Jina CLIP v2 and Elasticsearch

Build a multilingual image search system using Jina CLIP v2 and Elasticsearch. Query your image collection in 89 languages with no translation pipeline, and use Matryoshka Representations to cut index size by 75%

Jeffrey Rengifo

One API call per operation: how Elastic Cloud Hosted makes fleet-scale deployment management practical

Elastic Cloud Hosted adds five targeted APIs for upgrade, tier scaling, user settings, tags and snapshot repository linking, each replacing a multi-step deployment plan edit with a single focused call.

Omer Kushmaro

How we doubled vector search throughput on Elasticsearch Serverless

How we brought Elasticsearch's native SIMD scoring engine to serverless, and why serverless is where vector search innovation happens next.

Chris Hegarty

How Elasticsearch cuts time-series storage by 34% with synthetic _id and bloom filters

Learn how synthetic _id uses bloom filters to cut time-series storage by 34% while maintaining full API compatibility.

Tanguy Leroux

Small model, big benchmarks: how Jina-VLM beat the competition at 2.4B and what ICLR told us is coming next

Jina-VLM is a 2.4B open multilingual VLM leading VQA benchmarks across 29 languages. Plus: five days of ICLR 2026 takeaways on RLVR, sparse embeddings and retrieval.

Andreas Koukounas

Cutting Elasticsearch DiskBBQ query quantization time by 5x

See how asymmetric quantization cuts DiskBBQ query quantization overhead from about 20% to 4% with little recall impact.

Benjamin Trent

Cutting agent costs with pre-computed context

Pre-computing context as Knowledge Indicators reduces LLM agent token costs by up to 75% and improves answer accuracy from 60% to 92%. This post covers the extraction, retrieval and feedback loop that make it work, tested against the BrowseComp-Plus benchmark.

Joe McElroy

Kibana dashboards as code: GitOps, drift detection and Terraform for Kibana dashboards in Elastic 9.4

Elastic 9.4 ships a typed Dashboards API and a native Terraform resource that bring drift detection, PR-reviewable diffs and git-based rollback to Kibana dashboards for the first time.

AI Chat in Kibana now natively renders dashboards

The Elastic AI Chat in Kibana now builds dashboards from natural language, keeping your visuals and analysis in one thread and letting you save them as reusable Kibana objects.

Kibana cuts dashboard load time by up to 25% - here's the polling strategy behind it

Find out how Kibana uses continuous polling and browser-side HTTP/2 detection to cut dashboard load times by up to 25%, with automatic fallback on HTTP/1.

Drew Tate

Describe it, don't draw it: AI-native Kibana dashboards via MCP and ES|QL

From prompt to dashboard. Learn how to build Kibana dashboards with natural language, using example-mcp-dashbuilder: an open source MCP application that writes ES|QL queries, creates interactive charts and exports fully functional dashboards directly to Kibana.