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AI is moving fast. Enterprise adoption needs to move with purpose. Over the past year, one thing has become clear: Organizations are not looking for more AI hype. They are looking for a path to production — one that connects infrastructure, data, and intelligence in a way that delivers real business value. That is exactly what the Elastic AI Ecosystem is built to do. At Elastic, we believe AI is only as powerful as the data foundation behind it. Great models matter.

So your database is slow. Now what? Grafana Cloud Database Observability already gives you visibility into your SQL queries with RED metrics, individual execution samples, wait event breakdowns, table schemas, and visual explain plans. But visibility is just the starting point. You can see that a query's P99 latency spiked, but what should you do about it? You can see wait events like wait/synch/mutex/innodb firing, but what does that actually mean?

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NiCE and TazamaTech Announce Strategic Partnership.

An open-source foundation for resilient infrastructure: on-prem, cloud, and hybrid. IT downtime costs organizations an average of $9,000 per minute, or more than $1 million per hour. That’s real money lost when websites crash, transactions fail, or internal systems go offline. For many organizations, avoiding those losses starts with choosing the right server operating system (OS). Why? The OS sets the foundation for how stable, secure, and cost-efficient your infrastructure will be.

A few weeks ago we had a bug with Session Replay. Replays were failing in some browsers once more than 1,000 video segments loaded. We had no idea how often it happened or who was hitting it, and because the failure didn’t always produce an error, we had no way to find affected users to reproduce it. Before, we could’ve answered this with spans or logs, but it’s clunky — spans are often sampled, so you can miss outliers; logs are less structured and tend to change over time.

For most of JMS's lifetime, writing a simple producer required creating a ConnectionFactory, creating a Connection, starting it, creating a Session, creating a MessageProducer, creating a Message, calling send(), and then closing the producer, session, and connection with the close calls safely wrapped in finally blocks to prevent resource leaks. Every developer knew the pattern. Every developer wrote it slightly differently. Every code review had the same comments about resource management.

This article is a high-level overview of the Coralogix CLI. For a deeper look at how it works in practice, read the full technical deep dive here. Agent-driven investigation sounds simple: read the alert, query the data, return the cause. In reality, most agents either overload their context window with raw logs or guess at queries and return incorrect results.