GPU-accelerated vector indexing in Elasticsearch with NVIDIA cuVS: 138M vectors in under 10 minutes
Moving index builds to the GPU leaves the CPU free for queries, which is how vector indexing throughput went up 7x and p90 search latency fell 6x while indexing ran, with no change to recall.
One button, three places: How we rebuilt Kibana's page headers with stricter APIs
We gave Kibana's shared shell typed contracts, which is how design system governance became the default, and why the new page headers have no breadcrumbs.
Columnar storage isn't a columnar database. What Columnar mode brings to Elasticsearch
Elasticsearch has stored data in columns since 2013, but adding full columnar database capabilities required a new mode.
How we built PromQL into Elasticsearch
PromQL runs on the same Elasticsearch compute engine as ES|QL, with no plugin and no separate process to operate. Getting there meant changing how the engine evaluates time windows and builds grouping keys.
Trust, but benchmark: How we let an AI agent optimize Elasticsearch
We share how we built a harness that automatically identifies and implements optimizations in the Elasticsearch codebase.
No more allocation delays: Decoupling snapshots from shard relocation in stateless Elasticsearch
Clusters scale out under load without waiting for a snapshot to finish, because snapshots now read straight from the object store and no longer pin shards in place.
Avoiding and Correcting Hotspots: How Elasticsearch Serverless Balances Shards
Elasticsearch Serverless replaces the Elasticsearch node-weight based shard rebalancing algorithm with resource usage aware rebalancing that avoids index shard colocation, OOM events and write load hotspotting
Migrating 1,100 files to Redux Toolkit v2 without freezing the Kibana monorepo
Kibana gave Redux Toolkit v2 the default package name and pushed v1 onto an explicit alias, which inverts the usual migration order. Webpack externals, yarn resolutions and an ESLint rule keep React Redux v7 and v9 out of each other's way.
Taming PUNKs: How ES|QL queries Elasticsearch fields it was never told about
In Elasticsearch 9.5, ES|QL can query unmapped fields. It reads them from _source or returns nulls, so a query keeps working when a field drops out of the mapping and you avoid a reindex that takes hours.
ES95: Adaptive Compression for Elasticsearch Time-Series Metrics
ES95 is Elasticsearch 9.5's new adaptive time series codec that cuts @timestamp storage by 92% and floating point fields by up to 74%, with zero configuration.
How Elasticsearch's batched query phase improves search performance at scale
The batched query phase can cut search execution time in half by reducing transport overhead and better distributing reduction work across the cluster.
Why Elasticsearch is becoming a columnar database
Elasticsearch is becoming a first-class columnar database. Columnar Mode ships in 9.5, storing data once alongside the existing modes and cutting storage footprints while speeding up analytical queries.