AURA in practice: real-world use cases for production AI agent infrastructure
How platform and SRE teams are using Mezmo's open-core agent framework — with any LLM, any tools, any observability backend.
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The latest News and Information on Log Management, Log Analytics and related technologies.
Architecting Log Management for Privacy and Scale without the Headache
As companies grow, they inevitably hit a wall: observability data explodes while privacy requirements become stricter. For years, engineers have faced a painful tradeoff—either ship petabytes of sensitive data to a central cloud (incurring egress costs and compliance risks) or manage a complex self-hosted stack that is painful to scale.
Claude Code is running bash commands on your infrastructure. Here's how to watch it.
I’ve been staring at Claude Code telemetry for the past few weeks, and I keep noticing the same thing: most teams drop it into their environment, say “it’s amazing,” and have absolutely no idea what it’s actually doing at the system level. That’s fine for a personal dev tool. It’s not fine when you’ve rolled it out to 50 engineers.
The AI-Driven Security Pipeline: Bindplane at RSAC 2026 Conference
RSAC 2026 Conference is right around the corner, and we're unveiling new security capabilities at Booth N-5285. Book a 15-minute slot if you want an in-person walkthrough!
Take the next steps for observability with autonomous IT platforms and Elastic
TL;DR: Autonomous IT platforms combine observability data and AI to automatically detect, diagnose, and resolve issues—shifting operations from reactive monitoring to predictive, self-healing systems.
OTEL Collector: Customizable YAML Configuration
This video shows you how custom YAML configuration works with the Sumo Logic OpenTelemetry collector.
Monitor schema health with engine.schema_fields: Structure, Drift, and Volatility
If you’ve worked with an observability pipeline, you’ve probably experienced schema problems: a field disappears, a type shifts from string to number, or a new label quietly appears. The causes are everywhere. Different teams adopt different naming conventions. A dependency upgrade changes the shape of a library’s log output. Over time, these small, reasonable decisions compound into schema sprawl: dashboards break, alerts misfire, and teams scramble to find out what happened.
From Data Chaos to Results: The New Data Strategy for the Agentic Era
The world is generating data at a pace that defies the human ability to draw insights and comprehend. By 2028, we’ll reach almost 400 zettabytes of global data—with over 55% of it coming from machines talking to machines. For enterprises, this isn’t just a storage problem; it’s an existential challenge.
Powering enterprise AI at scale: The Elastic and NVIDIA cuVS integration
Seamlessly vectorize high-volume data and accelerate your time to production with the new gold standard for GPU-accelerated vector search.
Choosing a JavaScript logging library: The 2026 definitive guide
With AI writing more and more of our code, properly monitoring and debugging that code has become an increasingly critical part of the development workflow that can't be ignored. Luckily, we have more time than ever to implement the right tools to do so. Implementing a production-ready logging solution is easy to do, and provides you and your LLM Agents with a wealth of debugging information from your app, across users and environments.