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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

The Current State of Content Negotiation for AI Agents (Feb 2026)

The web was built for humans, but now the agents are taking over. Humans look at a web page and see content rendered by their browser. AI agents see 180,000 tokens of nav bars, footers, and div soup — burning through their context window on junk that makes them slower and stupider. The web needs to evolve, and we as developers are driving the shift. AI agents like Claude Code, Cursor, Codex, and Gemini are how we interact with documentation, CLIs, and products today.

Use AI to turn any JSON API into a dashboard in minutes with the Infinity data source plugin and Grafana Assistant

The internet is full of fascinating data just waiting to be visualized and queried. And with the latest update to Grafana Cloud, you can start doing it in minutes. Through public APIs, you can access information about global earthquake activity, weather forecasts, music catalogs, and millions of other datasets. And then there's all the data that sits inside company APIs, partner services, and internal platforms that power everyday products and operations.

Bindplane Blueprints for Elasticsearch: Production-Ready NGINX Log Pipelines for Kibana

We've just released new and easy-to-use Bindplane blueprints designed specifically for Elasticsearch as a destination. These blueprints empower teams to quickly transform raw events such as those from NGINX access and error logs into clean, structured, and ECS-compliant data optimized for high-performance visualization in Kibana.

Signal-Driven Error Monitoring: Detecting and Debugging Reactive Failures in Angular

Angular's Signal-based reactivity model represents one of the biggest paradigm shifts the framework has seen since Ivy. By replacing the asynchronous push-pull model of RxJS with synchronous, localized updates, Signals make state management both simpler and faster. But this new simplicity hides a subtle danger: when something breaks inside your reactive graph, it often does so silently. A computed value might stop updating. An effect might fire indefinitely.

Make use of guardrail metrics and stop babysitting your releases

Modern CI/CD pipelines have automated the hard work of building, testing, and deploying our code. But for many teams, that’s where the automation stops. The most critical part of a release, turning a new feature on for real users, is still a stressful, manual process. An engineer cautiously ramps up traffic to 5%, then 10%. The whole team stares at dashboards, trying to see if anything breaks. If something does, they scramble to manually roll back.

How to write annotations in Kubernetes with JSON for Datadog Autodiscovery | Datadog Tips & Tricks

Pod annotations in Kubernetes with invalid JSON syntax can prevent Datadog Autodiscovery from detecting integrations, resulting in missing metrics and gaps in monitoring. Watch this video for a step-by-step process to write annotations: Note: This video focuses on Datadog Autodiscovery v2 syntax.