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The latest News and Information on Log Management, Log Analytics and related technologies.

Elasticsearch 9.4 powers the next phase of the Elastic AI Ecosystem: Dell AI Data Platform with NVIDIA

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.

The cost of knowledge

In the world of observability, “cardinality” has become a heavy word. It is a ghost used to justify skyrocketing bills or degraded query performance. When cardinality rises, the advice is almost always the same: reduce it. Drop your labels, or reduce the dimensions. It is usually framed as “optimization.” Every label you add to a metric is a dimension of knowledge. Each one gives you a way to slice, compare, and explain the chaos of production.

Ep 41: The cost of not thinking: Who's responsible when AI agents get it wrong?

In this episode of Masters of Data, we get into the messier side of AI adoption, tackling questions like who actually owns the output when AI gets it wrong, and whether chasing efficiency is making us forget what it means to be human in the first place. We discuss tech CEOs proudly announcing they no longer think for themselves and debate whether AI is quietly eroding our critical thinking skills. We make the case that purpose-built, narrow AI is genuinely exciting, but that no efficiency gain is worth losing the human touch that makes work, connection, and creativity meaningful.

Observability vs Monitoring: What's the Real Difference in 2026?

Understand the real difference between observability and monitoring — and why modern IT teams in 2026 need both. Monitoring tells you something is broken; observability explains why. See real examples, faster troubleshooting workflows, and how Motadata ObserveOps unifies both in one platform. Don’t forget to like, share, and subscribe for more IT insights.

Introducing the Coralogix CLI: Headless Observability for Every Agent

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.

Federated Search | From Silos to Insight | Unified Datasets in AWS S3 with Ingest Processor

Are storage costs and data silos slowing down your investigations? In this video, we dive into the Unified Dataset Experience to show you how to search data where it lives. Learn how to use the Splunk Ingest Processor to route high volume logs directly to AWS S3 while maintaining instant visibility via Federated Search. No more re-hydrating data, just fast cost-effective insights.

How the Coralogix CLI Adds Production Intelligence to Any Agent for Any Use Case

The new interface into production telemetry is a tool call, made from whichever agent runtime the operator happens to be using at that moment. A finance lead in Claude Code, a product manager in Cursor, an engineer in Codex. Three different jobs, three different agents, three different reasoning loops. The thing they have in common is the data layer underneath.