Operations | Monitoring | ITSM | DevOps | Cloud

Your agent can't fix what it can't see

Agents are getting better and better at fixing bugs. They’re even getting better at testing their work, thanks to headless browsers, sandboxes, simulators, etc. But what about the bugs that only show up once you bring in different browsers, languages, extensions, internet speeds, and all the other variables that get mixed in the second you ship to prod? Or all the bugs that only show up when you account for… well, humans being humans and doing weird stuff you didn’t expect them to do?

Measure the real impact of AI coding tools on software delivery with Datadog AI Impact

Engineering teams have rapidly adopted AI coding tools, but organizations still struggle to understand their impact. Existing dashboards focus on activity, such as daily active users, acceptance rates, or lines of generated code, but these metrics don’t answer a more important question: Are teams actually shipping more, faster, and with fewer issues?

How Online Plant Identification Tools Work

Online plant identification tools work in a simple way: a user uploads a photo of a plant, the tool analyzes visible features such as leaves, stems, flowers, shape, color, and growth pattern, then compares those features with a plant database. After that, it shows the most common name and, in many cases, adds basic care recommendations.

Observability Expanding Beyond Infrastructure and Into AI Systems

Observability revolves essentially around understanding infrastructure health. This means that operations teams monitor applications, netwo0rks, database and cloud environments using familiar signals. They use logs, metrics, latency, uptime measurements, and traces. If systems remain available and the performance stays within expected thresholds, the teams have enough visibility to understand whether applications are functioning properly.

Inside the Grafana AI Team Weekly: Guards for AI Observability (May 5, 2026)

This is an excerpt from a real AI team weekly meeting where we talk about the stuff we build and occasionally also demo them! In this one, Principal Software Engineer Sven Großmann shows a new feature he's working on for AI Observability, called "guards". We're showing parts of our team meetings to build in public in some small way and give you a sneak preview of what's to come. But not all features we show may make it to production! You've been warned. :)

AI Agent Orchestration in IT Operations: The Complete Developer's Guide

If you've spent any time in IT operations, you know the drill - alerts firing at 2 a.m., cascading failures, runbooks nobody follows correctly, and a team stretched too thin. That's the environment where AI agent development starts making real sense. Not as a buzzword, but as an actual engineering answer to an operational problem that's been compounding for years. From our team's point of view, orchestrating multiple AI agents in IT isn't just automation. It's about building systems that coordinate and act the way a competent ops team would - minus the fatigue.

Top Business Process Automation Trends Shaping 2026 Workflows

Businesses in Australia are operating in a very different environment than they were even five years ago. Service-based companies are handling higher client expectations, tighter compliance requirements, growing admin loads and increasingly complex operations - often without expanding their teams at the same pace.

Your Company Has 10x More Developers Than You Think

The low-code promise failed for 15 years. AI builders delivered in 15 months. Here's what actually changed, why the engineer in me resisted it, and what it means for every CTO. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.