Operations | Monitoring | ITSM | DevOps | Cloud

How Agentic AI is Reengineering Advertising Revenue Operations: Workflows to Workforce

Digital advertising is experiencing a shift similar to manufacturing's industrial revolution. AI is automating routine tasks, freeing up human teams for higher-level strategic work, moving us from manual campaign management to automated systems where humans design the strategy rather than execute every detail. This represents the biggest operational change since programmatic advertising began.

AI-Powered Monitoring with Checkly

Most monitoring tools weren't built for the AI-first world. By nature, traditional monitoring platforms force you out of your natural coding environment and trap you in clunky web interfaces, brittle configuration panels, and rigid APIs. And sadly, when monitoring providers do offer "AI features," it's usually a chatbot bolted onto their existing UI, being nothing more than a pale imitation of the AI tools you’re reading about every day on Hacker News. All this creates friction.

MCP Observability with OpenTelemetry

2025 has truly been the year of Agentic AI, with MCP (Model Context Protocol) emerging as one of its flashy and most talked-about innovations. While many products have seamlessly integrated MCP servers into their systems, these servers are increasingly being labelled as black boxes, opaque components that handle critical tasks but offer little visibility into what's happening under the hood. We prompt an agent, a tool gets invoked, and a response is generated. But what really happens in between?

Coralogix launches OpenAPI endpoints

Observability is about much more than dashboards and alerts. Extensible platforms that integrate into the user’s tech stack are fundamental parts of a great developer experience. This is why Coralogix has supported gRPC APIs for account management, data ingress & query, alert definition, dashboard creation, permissions management and more. Today, Coralogix adds a new integration, with the launch of OpenAPI endpoints for all existing functionality.

LangChain & LangGraph: The Frameworks Powering Production AI Agents

Your AI agent worked flawlessly in development, with fast responses, clean tool use, and nothing out of place. Then it hit production. A simple "What's our pricing?" query triggered six API calls, took 8 seconds, and returned the wrong answer. No errors. No stack traces. Unlike traditional systems, AI agents don't crash, they drift. They make poor decisions quietly, and your monitoring says everything's fine.

Introducing Netdata Insights

Subscribe to the channel → / @netdata Now in research preview: Netdata Insights The problem: Incident? You're jumping between dashboards, piecing together timelines. Reporting? You're copy-pasting charts and correlating trends by hand. The data’s there, but turning it into a narrative doesn’t scale. The solution: Netdata Insights. Synthesizes high-fidelity telemetry using the latest LLMs into AI-powered reports with natural-language explanations, visuals, and clear recommendations.

Netdata: The Fastest Path to Full Stack Observability. AI Powered.

Netdata is a real-time, high-performance and on-premises observability platform designed to monitor metrics and logs with unparalleled efficiency. Netdata requires zero-configuration to get started, and provides alerts, anomaly detection and AI assisted troubleshooting out of the box, providing a powerful and comprehensive infrastructure monitoring experience. Netdata is known for its distributed design. Instead of funneling all data into a few central databases like most traditional monitoring solutions, Netdata processes data at the edge, keeping it close to the source.

How we built agentic incident response

‍ AI already transforms how we detect, respond to, and resolve outages. Traditional workflows often force responders to switch between dashboards, shift through logs, and coordinate across fragmented channels under stress. This reactive, manual approach leads to slower resolution, higher operational costs, and burnout, especially as IT systems grow more complex. ‍ At ilert, we are not just discussing the future of incident management – we are actively building it.

Is AI About to Create Its Own Language? Here's What You Need to Know!

This panel brings together experts Josh Mesout (Civo), Nobel Chowdary Mandepudi (Arm), Jimil Patel (Intuit), Numa Dhamani (iVerify), and James Gress (Accenture) to discuss the cutting edge of AI and machine learning. They explore when AI might develop its own language beyond human syntax, the evolving landscape of ML frameworks such as MLIR, Mojo, and JAX, and the challenges involved in bridging the gap from AI research to production while optimizing models for deployment.