Category: Inside Elastic
Articles tagged Inside Elastic
How cross-project search (CPS) works in Elasticsearch Serverless
Elastic Cloud Serverless cross-project search (CPS) treats index expressions as cross-project by default. This post explains how TransportSearchAction scopes projects, resolves index expressions, skips projects with no matches, and validates index resolution against allow_no_indices and ignore_unavailable.
Stop guessing which query is burning your cluster: Query activity in Kibana
Pinpoint long-running Elasticsearch searches from Kibana: live tasks, origin context, and cancel when the cluster allows without living in low-level APIs.
Preconditioning Vectors: Making Elasticsearch VectorDB Better Binary Quantization work for every vector
Modern quantization techniques can hurt recall when using older models or embeddings that aren’t normally distributed. Learn how preconditioning fixes these vectors through random orthogonal projection, making BBQ more effective and recovering recall.
How we built Elasticsearch simdvec to make vector search one of the fastest in the world
How we built Elasticsearch simdvec, the hand-tuned SIMD kernel library behind every vector search query in Elasticsearch.
Announcing read-only permissions for Kibana dashboards
Introducing read-only dashboards in Kibana, giving dashboard creators granular sharing controls to keep results accurate and protected from unwanted changes.
Building effective database retrieval tools for context engineering
Best practices for writing database retrieval tools for context engineering. Learn how to design and evaluate agent tools for interacting with Elasticsearch data.
Build task-aware agents with an expanded model catalog on Elastic Inference Service (EIS)
Elastic Inference Service (EIS) expands its managed model catalog, enabling teams to build production-ready agents with flexible model choice across retrieval, generation, and reasoning, without managing GPUs or infrastructure.
Does MCP make search obsolete? Not even close
Explore why search engines and indexed search remain the foundation for scalable, accurate, enterprise-grade AI, even in the age of MCP, federated search, and large context windows.
Adaptive early termination for HNSW in Elasticsearch
Introducing a new adaptive early termination strategy for HNSW in Elasticsearch.
Speed up vector ingestion using Base64-encoded strings
Introducing Base64-encoded strings to speed up vector ingestion in Elasticsearch.
Building automation with Elastic Workflows
A practical introduction to workflow automation in Elastic. Learn what workflows look like, how they work, and how to build one.
Skip MLOps: Managed cloud inference for self-managed Elasticsearch with EIS via Cloud Connect
Introducing Elastic Inference Service (EIS) via Cloud Connect, which provides a hybrid architecture for self-managed Elasticsearch users and removes MLOps and CPU hardware barriers for semantic search and RAG.