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AI Can Write Your Infrastructure Code. Can It Govern and Heal What It Builds?
AI can write your Terraform in seconds. Learn what it takes to govern configuration drift and heal AI-generated infrastructure builds.
Create Custom Visualizations | Introducing Grafana Pages | New from Grafana AI
Grafana Pages is now in public preview in Grafana Cloud. Tell Assistant what you want it to see , and Pages builds it: a custom visualization, an app, a slide deck, or even a game. Pages are for the moments a dashboard can’t cover, like walking leadership through a launch, starting your day with a view of the services you own, or turning an incident into a story everyone can follow.
A walkthrough of a root cause analysis with ilert AI SRE
It's 3am and a complaint has made its way to you: customers can't see product reviews. Nothing has crashed, and no alert points anywhere useful. Somewhere in your stack one service is failing, and the one showing the error is probably not it. Before you can fix anything you have to find it, and that search is most of your night. Now imagine you open the laptop, type one sentence and go grab a coffee. By the time you’re back, the root cause is ready, evidence attached. Your job is to check it.
AI Can Write Infinite Code. But Can We Ship It Safely?
AI is making code generation faster than ever. But writing code is only half the battle. Neil Watkins from Burns & McDonnell explains why the next big challenge in AI-driven software development isn't generating more code. It's making sure that code can be tested, secured, and deployed safely. As AI accelerates development, businesses need to rethink how they manage risk and ship software with confidence.
Connect Agentic Pipelines to the redesigned Atlassian MCP
Agentic Pipelines now integrates with the redesigned Atlassian MCP server for Claude and Codex agents. Rovo Dev CLI agents in Agentic Pipelines currently use the original version of Atlassian MCP server and are unaffected by this update.
Shipped: Slice AI spend eight ways in AI Explorer
You can already break down cloud spend by team, product, or customer in Explorer. But AI spend has been harder to decompose. Which models is each team running? What activity is driving the cost growth you saw this month? Before AI Explorer, answering those questions meant exporting raw event data and building your own breakdowns, or waiting days for reconciled billing to land in Explorer.
Adding friction to your AI spend isn't saving money. It's costing you growth.
Enterprises are putting hard ceilings on AI spend. Accenture now centrally funds $29 a month per person for Claude and charges anything above that to a project budget code. Uber used up its 2026 AI budget in four months and restricted access. A cap stops waste and useful work at the same rate. The alternative is seeing AI cost by team, by project and by outcome, then funding what returns. Companies spent the past year telling employees to use more AI. Now a lot of them are putting a lid on it.
Fireside Chat: Alexander Embiricos (OpenAI) and Yanbing Li, CPO, Datadog
Join Datadog's Chief Product Officer Yanbing Li and OpenAI's Member of Product Staff Alexander Embiricos as they discuss emerging technologies and innovation, how they impact businesses today, and the new opportunities they create for you.
Test AI-Generated Code with Real Traffic#aiagents #devops #observability #shiftleft #softwaretesting
AI can generate code in seconds, but testing it against real production behavior is where developers get stuck. Learn how capturing and replaying actual production traffic in development helps you catch bugs before you deploy!