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An SRE agent for production

AI has changed how software gets built. It hasn't changed how software gets run. Most of the AI money in software has gone into the IDE: code generation, copilots, developer assistants, faster pull requests. That work matters. But writing software is one slice of the lifecycle. The harder problem, and the more expensive one, is running that software in production. Production is where systems fail in ways nobody predicted. Incidents don't stay inside one service.

Stop switching tools to find answers: Grafana Assistant now works across 30+ data sources

When you're the on-call engineer and something breaks, you can quickly find yourself deep in a series of tools you don't regularly use—switching tabs, copying query results, and manually stitching together a picture of what's happening and why. People are increasingly turning to AI to get around this, but the results can be a mixed bag.

AI is Exposing Observability's Dirty Secret

The 3 pillars of observability are breaking. For years, dev teams relied on Logs, Metrics, and Traces to know when something went wrong. But now? AI agents are writing, deploying, and changing code in real-time. When an AI hallucination pushes a bug to production, standard monitoring sees nothing wrong.To survive the AI era, we need a 4th Pillar of Observability. Watch to find out what it is and why the old way of monitoring just became obsolete.

Why colocation is becoming the foundation of sovereign AI

The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value. In line with this shift, organisations are looking beyond where AI is trained to the specifics of where it is actually used.

Why the U.S. Locked Down Fable and Mythos: AI, National Security, and the Workforce Squeeze

The U.S. just barred foreign nationals from accessing two advanced AI models — Fable and Mythos — citing national security. Around the same time, the Five Eyes intelligence alliance warned that AI-enabled cyberattacks are "months, not years" away. In Season 5 of ShipTalk, host Adam and co-host Martin dig into whether that warning is already overdue — and what it means for the people actually defending software.

What is AI cost observability? A guide to tracking LLM and AI spend

AI cost observability is the practice of measuring, attributing, and analyzing AI workload costs at the request, model, and workflow level in real time. It connects cloud infrastructure spend, inference and token costs, and business attribution (cost per feature, team, customer, or product) so engineering, finance, and product teams can see where AI spend goes and whether it creates value.

Enterprises are making their biggest AI bets blind

AI cost observability is the practice of measuring, attributing, and analyzing AI workload costs at the request, model, and workflow level in real time. It connects cloud infrastructure spend, inference and token costs, and business attribution (cost per feature, team, customer, or product) so engineering, finance, and product teams can see where AI spend goes and whether it creates value. On July 14, IBM had its worst trading day since 1987.

Quantum Computing Security: Why Enterprises Need to Prepare Now

Most security teams assume their encryption will hold. That assumption has an expiry date. A 2025 ISACA poll of more than 2,600 professionals found that 62% expect quantum computers to break current encryption, yet only 5% of their organizations have a defined plan to respond. That distance between worry and action is the real exposure. Machines able to crack widely used encryption are no longer science fiction, and the data you guard today could be unlocked the moment they arrive. Here is what the shift means for your business, how much runway you actually have, and where a sensible response begins.

Top 5 Network Diagramming Tools for 2026: Ultimate Guide for IT Teams

Network diagramming is the backbone of successful IT infrastructure planning and troubleshooting. The right diagramming software saves organizations time and prevents costly errors, especially as systems grow in complexity and scale. Below, discover the five best tools for network diagramming in 2026, evaluated through rigorous criteria and supported by industry data, so you can confidently select the ideal platform for your needs.

Why the Netherlands Is a Strategic Hosting Location for EU-Focused Businesses

Selecting the optimal physical server location is one of the most critical infrastructure decisions for an expanding enterprise. For digital businesses serving European users, the Netherlands has firmly established itself as the digital gateway to the continent. Situated at the very core of Europe's telecommunication crossroads, Dutch infrastructure offers unprecedented network connectivity, stringent legal data protections, and low-latency throughput.