The Elastic Team - Elastic Community Newsletter

Hello from the Elastic DevRel team! In this newsletter, you’ll find information on upcoming Elastic meetups and events in your region, catch up on product updates and content, and stay up-to-date with everything Elastic-related. In this edition, we cover the 8.17 release of Elasticsearch and the Elastic Stack as well as the General Availability of Elastic Cloud Serverless on AWS.

Elasticsearch and the Elastic Stack 8.17 are now available. Check out the release notes.

The fastest way to spin up Elasticsearch and Kibana 8.17 is with start-local. Run curl -fsSL https://elastic.co/start-local | sh in your shell and you’re good to go.

Logsdb

With the general availability of the Elasticsearch specialized logsdb index mode, Elastic reduces the storage footprint of log data in Elasticsearch by up to 65%. This allows you to store more observability and security data without exceeding your budget while keeping all data accessible and searchable.

Logsdb index mode enables index sorting and advanced compression techniques like ZSTD, delta encoding, and run-length encoding. With Elastic Cloud Serverless or the enterprise level license, you will get even more compression with synthetic _source. Refer to the subscription page for Elastic Cloud and Elastic Stack / self-managed for the breakdown of available features and their associated subscription tiers.

To activate this mode, you need to set index.mode to logsdb:

PUT _index_template/my-index-template

{

  "index_patterns": ["logs-*"],

  "data_stream": { },

  "template": {

     "settings": {

        "index.mode": "logsdb" 

     }

  },

  "priority": 101 

}

Elastic Rerank model

Reranking models provide a semantic boost to any search experience without requiring a change in the schema of your data. 8.17 provides a semantic boost for full-text search with a highly performant and efficient semantic reranking model. The technical preview of Elastic Rerank model — in addition to the ability to integrate with third-party models for semantic reranking — makes it much easier to get started with relevance tuning.

The Elastic Rerank model is in technical preview. You can use it by creating an inference endpoint and then use it in your _search query. You can read more details about the performance and efficiency of this new model on Elasticsearch labs.

Full-text search for ES|QL

The technical preview of new MATCH and query string (QSTR) functions in ES|QL makes log searches easier and more intuitive. MATCH delivers full-text search functionality in ES|QL using a Lucene match query, while QTSR aids in more advanced filtering of log data by enabling Lucene query string queries.

Some examples:

FROM books

| WHERE MATCH(author, "Faulkner")

| KEEP book_no, author

| SORT book_no

| LIMIT 5

FROM books

| WHERE QSTR("author: Faulkner")

| KEEP book_no, author

| SORT book_no

| LIMIT 5

Elastic Cloud Serverless is GA

No nodes, no shards, no versions: Elasticsearch Serverless is GA on AWS after two years of development including almost a year of technical preview. Available on cloud.elastic.co — you can start a free trial today. Here are some of the best resources to get you up and running with it:

• The official release blog post: Running on a blob store like S3 doesn't mean it has to be slow.
• A completely rearchitected, cloud-native Elasticsearch, based on blob storage, separating storage and compute and indexing from search.
• A new cloud backend, based on K8s, with a global control plane and regional components, ability to scale both within a K8s cluster and across K8s clusters and autoscaling across all dimensions — Elasticsearch, Kibana, Fleet, K8s nodes, K8s clusters.
• The differences in comparison to self-managed or hosted Elasticsearch: This is also the reason for "do less with serverless" — you don't have to do all the housekeeping, configuration, and scaling anymore.
• Roadmap: What is already available and what's coming next; including Azure and GCP support.
• If you want to see a deep dive into architecture and integrations on Elasticsearch Labs: To know how writes really work with S3. Or queries. Or autoscaling. Or …
• Finally, pricing (per solution): If you have looked at the cost during the preview phase, take another look since we have managed to reduce prices considerably.

OpenELM: Deploy and test the new Apple Models and build a RAG system using Elastic with Gustavo Llermaly.

Monitoring-as-code: Carly Richmond discusses how monitoring-as-code helps unite monitoring and E2E testing efforts in this piece for ;login: magazine.

Re-ranking: Explore depth in a 'retrieve-and-rerank' pipeline and select an optimal re-ranking depth for your model and dataset with Thanos Papaoikonomou, Thomas Veasey and Quentin Herreros.

Elastic AI Assistant: Tommy Bumford covers streamlining threat intelligence reporting with Elastic AI Assistant.

BBQ: Chris Hegarty explains how we optimized vector comparisons in Better Binary Quantization (BBQ) using hardware accelerated SIMD (Single Instruction Multiple Data) instructions.

Observability: Navigate challenges in an observability maturity journey with David Hope.

Vega: Add filter capabilities to Vega Sankey visualizations in Kibana with Tim Bosman and Miloš Mandić.

Check out these videos:

• Learn how to analyze data using Python, Elasticsearch and Kibana with Jessica Garson.
• Implement Elasticsearch Vector Search and kNN with Justin Castilla.
• Jessica Garson explores translating datasets Using Python, LangChain & Vector Database.
• Master RAG with Playground - quickstart by Joe McElroy.

Featured blogs from the community:

• Mert Oz explores key optimizations for Elasticsearch performance.
• Failing at an Elasticsearch 'full' phrase match by Doug Turnbull.
• Nick Hehr of VIAM explores using sensor data with Webhooks and Elastic Cloud.

Americas:

Virtual Meetup: Elastic Machine Learning from Zero to Real Insights in 2 Weeks — January 8

Seattle: Seattle JS - Elastic Observability and Open Telemetry — January 8

Meetup in Lancaster: Monthly Community Meetup — January 15

Meetup in New York: How Elastic Stack Shielded Clients from the SIGRed DNS Apocalypse — January 16

Meetup in Dallas: Monthly User Group Meetup — January 21

Europe, Middle East, and Africa:

Meetup in Madrid: Elastic Meetup at eDreams Odigeo — January 15

Meetup in Amsterdam: AI-Free Zone: Delivering Full-Text Search That Works— January 22

Grenoble: SnowCamp — January 22-25

Asia-Pacific:

Virtual Meetup: Elastic Virtual Meetup - APJ — January 16

ElasticON Tour:

Elastic's free, one-day conference series is coming to you. Join us to learn what's hot at Elastic right now, watch talks or demos, and visit the ask-me-anything booth. We have a community track for which you can submit your talks!

Paris: ElasticON community track — January 20

Paris: ElasticON — January 21

London: ElasticON — February 6

Singapore: ElasticON — March 4

Sydney: ElasticON — March 6

Join your local Elastic User Group chapter for the latest news on upcoming events! You can also find us on Meetup.com.

If you’re interested in presenting at a meetup, send an email to meetups@elastic.co