Cambi infrastrutturali in Uber: dai limiti raggiunti con #elasticsearch a contributori di #opensearch

https://www.uber.com/en-IT/blog/evolution-of-ubers-search-platform/

The Evolution of Uber’s Search Platform

Search is a foundational pillar of Uber’s user experience, directly influencing key aspects of our core business. Whether you’re looking for a meal on Uber Eats or requesting a ride, search is what connects you with the right options—quickly, accurately, and at scale. Uber Eats users are faced with a staggering choice: over one million restaurants globally, and typically more than a thousand dishes or restaurants per user session. Helping Uber Eats users navigate this vast space—based on preferences like cuisine, price, delivery time, dietary needs, or past behavior—is a deeply complex problem.

Uber Blog

16 billion credentials: No new leak, lots of old data

A report of an alleged data leak of 16 billion access data is currently doing the rounds. However, much of it is old.

https://www.heise.de/en/news/16-billion-credentials-No-new-leak-lots-of-old-data-10453869.html?wt_mc=sm.red.ho.mastodon.mastodon.md_beitraege.md_beitraege&utm_source=mastodon

#Elasticsearch #IT #Security #news

16 billion credentials: No new leak, lots of old data

A report of an alleged data leak of 16 billion access data is currently doing the rounds. However, much of it is old.

heise online

16 Milliarden Zugangsdaten: Kein neuer Leak, viele alte Daten

Eine Meldung eines angeblichen Datenlecks von 16 Milliarden Zugangsdaten macht derzeit die Runde. Vieles davon ist jedoch alt.

https://www.heise.de/news/16-Milliarden-Zugangsdaten-Kein-neuer-Leak-viele-alte-Daten-10453723.html?wt_mc=sm.red.ho.mastodon.mastodon.md_beitraege.md_beitraege&utm_source=mastodon

#Elasticsearch #IT #Security #news

16 Milliarden Zugangsdaten: Kein neuer Leak, viele alte Daten

Eine Meldung eines angeblichen Datenlecks von 16 Milliarden Zugangsdaten macht derzeit die Runde. Vieles davon ist jedoch alt.

heise online
Elasticsearch adds vector search to its ecosystem, allowing hybrid queries without new infrastructure. #Elasticsearch https://zilliz.com/blog/top-5-open-source-vector-search-engines
Top 5 Open Source Vector Databases in 2025 - Zilliz blog

Walk through the most popular open-source vector databases available today, compare their strengths and limitations, and provide practical insights to help you make an informed decision.

Ryan Smith on Using #ElasticSearch to complement your #headless multisite #WordPress application @decoupleddays August 13-14 2025 @citycollegeny #ccny Watch this space: 2025.decoupleddays.com

ElasticSearch users that interact with it with Perl - apparently Elastic have abandoned the Perl lib (Search::Elasticsearch) with the recently released version 9.0.

If you'd like to use it in the future, might be worth letting them know, especially if you have a support contract.

https://www.elastic.co/guide/en/elasticsearch/client/perl-api/current/index.html

#Elastic #Perl #ElasticSearch

MCP and #mastra with a dash of #elasticsearch. quick and dirty twitter thread from our SF meetup 🧵
Just created my first index in ElasticSearch! It's fascinating how we can index, store, and search documents so efficiently. On to the next step in the workflow! 🔧
#LLMZoomcamp #ElasticSearch #DataTalksClub

Log management in large Kubernetes environments poses challenges with thousands of pods generating vast data volumes, increasing CPU, RAM, and disk costs. Aliaksandr will discuss strategies using #Elasticsearch, #Grafana #loki and #VictoriaLogs to cut infrastructure costs by 10x or more.
This talk is essential for anyone building or running large-scale #Kubernetes clusters.

https://hubs.li/Q03rRvjC0

#Observability #DevOps #OpenSource #Logging

How to Efficiently Manage Logs in Large-Scale Kubernetes Clusters DevConf.CZ 2025

Large Kubernetes clusters can generate significant volumes of logs, especially when housing thousands of running pods. This may demand substantial CPU, RAM, disk IO, and disk space for storing and querying large log volumes. In this talk, we will look into different strategies of storing those logs in ElasticSearch, Grafana Loki and VictoriaLogs and examine how we can save 10x or more on infrastructure costs. This talk presents real-world examples of efficient log management in large-scale Kubernetes clusters. It includes setup demonstrations, numerical data, and graphical representations from reproducible benchmarks.