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The latest News and Information on Observabilty for complex systems and related technologies.

Can Observability Reduce Your Tech Debt? | Live Laugh Logs Ep. 5 with Wilco Burggraaf

Your telemetry data can reduce engineering complexity AND make your software more sustainable - find out how in this episode! Welcome to Episode 5 of Live Laugh Logs, the podcast from the Coralogix Developer Relations team. This week, Annie is joined by Wilco Burggraaf, Principal Lead at HighTech Innovators and host of the Sustainable IT Action Netherlands meetup.

Evaluate AI models for observability: o11y-bench joins Fireworks' Specialized Intelligence Index and reaches v1.1

When evaluating AI models for observability, generating a plausible query or explanation isn't enough. Teams need to know whether an agent's conclusions are supported by telemetry, whether its changes to dashboards actually work, and whether it can deliver reliable results consistently. This is why we built o11y-bench, Grafana Labs' open benchmark for evaluating AI models on observability and SRE tasks. And today, we're excited to share two updates.

Ship SecOps changes like software: Modernizing the SOC without breaking what works

Cribl gives security teams control over their data: what they collect, where to send it and how much to keep. The rest of the SecOps stack hasn’t kept pace. Detections, parsers and configurations spread across SIEMs, pipelines and data lakes still change by hand, so every cost cut, migration or new source turns into weeks of manual validation, and plenty of planned changes never happen at all. SecOps as Code closes that gap: every change ships like software, with testing, version control and rollback across the entire infrastructure.

LLM inference on Kubernetes and observability

Running an LLM on Kubernetes is rarely just a Deployment with vLLM in it anymore. A whole layer of frameworks and operators has grown up for it: KServe, NVIDIA Dynamo, Ray Serve, Kthena, llm-d. Each one adds its own custom resource that describes a model deployment, with routing, autoscaling and the split of a model across pods built in, and each one turns that resource into ordinary Kubernetes objects in its own way.

Agent Observability FAQ: Understand the value of monitoring, evaluating, and improving your AI agents

Agents have quickly become part of the tech landscape as organizations embrace AI across their businesses. But embracing agents also means embracing the monitoring best practices that have long been part of engineers' workflows: tracking performance, catching errors, and responding to incidents But it doesn't stop there. Agents also introduce new challenges.

Cribl Detect: A new way to SIEM

Cribl Detect helps security teams use an open, platform-first architecture for SIEM workflows, including compliance, detection, investigation, and response. This video explains how Cribl Detect combines telemetry pipelines, real-time detection, structured search, federated investigations, long-term retention, and open integrations.

Operationalizing Microsoft 365 Copilot: Compliance, security, and scale

Unmonitored AI is a massive organizational blind spot. Join Cribl's Field CISO, Ed Bailey, and Senior Product Manager, Daniel Pan to learn Cribl can help you affordably collect and store Microsoft 365 Copilot prompts and responses and share that data across your IT and Security teams to meet compliance requirements and gain real AI observability. We'll cover how to scale collection with less effort and build the AI-ready data architecture that solves today's challenges and sets you up for what's next.

Community Stories: Coroot at the Stanford University Libraries

Coroot was designed to solve the problem of time-consuming root cause analysis. It handles the full observability journey - from collecting telemetry automatically with zero code setup (thanks, eBPF!) to simplifying the role of SREs and DevOps everywhere with instant root cause analysis powered by AI. We also strongly believe that simple observability should be an innovation everyone can afford to benefit from: which is why our software is open source!

Introducing AI Observability: Trace Every AI Agent Request from Prompt to Pod

TL;DR Logz.io AI Observability provides end-to-end tracing for AI agents and LLM applications. Built on OpenTelemetry, it lets you trace every request from prompt to backend service, visualize multi-step agent execution, isolate root causes across models and infrastructure, and track token usage per step, all alongside your existing logs, metrics, and traces.