Operations | Monitoring | ITSM | DevOps | Cloud

hyperview

Agentic AI in the Data Center: What It Really Means, and Why Security Has to Come First

Jul 24, 2026 By Jad Jebara In Hyperview
Agentic AI means a system that acts on behalf of a specific person, within that person’s exact role and access permissions — not a general term for “smart” software. In data center infrastructure, agentic AI only becomes safe to deploy once three things already exist: a complete monitoring pipeline, an analytics pipeline, and a control pipeline governed by strict role-based access control.
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How to Build a Reliable Review Gate for AI Generated 3D Assets

How to Build a Reliable Review Gate for AI Generated 3D Assets

Jul 24, 2026 By OpsMatters In OpsMatters
A creative team generates twenty 3D props in an afternoon. The files look acceptable in preview images, so they are placed directly into the shared asset library. Days later, developers discover inconsistent scale, missing textures, reversed normals and several models with unclear ownership or revision status. The generation process worked. The production process did not.
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speedscale

Imaginary Test Data. Real Token Bill.

Jul 23, 2026 By Alan Mon In Speedscale
Ask an AI for K-pop concert advice without saying the group, city, date, or budget. It may confidently send you to a BLACKPINK tribute night in Cleveland with a $400 resale ticket. The AI was plenty confident. It just had nothing real to go on. That is exactly what happens when developers test AI applications with invented traffic. The test may look reasonable. The result may even pass.
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Catch AI Agent Failures Before They Ship | Harness AI Evals

Jul 23, 2026 By Harness In Harness
AI agent quality should not depend on manual checks. But for many teams shipping AI in production, agent failures are silent. The agent doesn't crash - it just gives confidently wrong answers, and your monitoring sees nothing wrong. Without automated guardrails, plausible-sounding wrong responses, hallucinations, and quality regressions reach customers before anyone notices.
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Guardrails for shipping with AI agents, feat. Luca Rossi of Refactoring.fm

Jul 23, 2026 By CircleCI In CircleCI
Code review has always been a time sink. AI just makes the dysfunction undeniable. Luca Rossi, founder of Refactoring.fm and builder of the open source tool Tolaria, has been running one of engineering's most-read newsletters for five years, with over 170,000 subscribers. He's also been doing what a lot of engineering leaders talk about but rarely do: building a real product with AI agents to pressure-test what's actually possible today.
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selector

The Near-Term Wins in AI for NetOps Rest on the Same Foundation

Jul 23, 2026 By Dallon Robinette In Selector
Walk into a network operations center this year and the useful AI is not running the place. It is doing three specific jobs, and doing them well: cutting an alert storm down to the one incident that matters, pointing at the likely cause, and deciding what deserves a human’s attention first. That is where AI in NetOps pays for itself right now. The part worth noticing is that all three jobs lean on the same thing.
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Dynamic MCP Server Demo | Connect Claude to Enterprise Automation in Minutes

Jul 23, 2026 By Resolve In Resolve
See how the new Dynamic MCP Server in Resolve Actions Pro 8.1 lets AI assistants like Claude discover and execute approved Resolve runbooks through the Model Context Protocol (MCP). Watch enterprise automation happen in real time with secure, auditable execution.
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Teneo

Why AI Governance Is Now the Biggest Challenge for Enterprise AI

Jul 23, 2026 By Teneo In Teneo
For the past couple of years, most conversations about AI in business have centered on adoption. Which tools should organizations deploy? Where can AI improve productivity? How quickly can it deliver value? Those questions still matter, but they are no longer the most difficult ones to answer. AI is now appearing across business applications, employee workflows, development environments, and customer-facing services.
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datadog

AI gateway best practices: Model routing, reliability, and budget controls for production agents

Jul 23, 2026 By Datadog In Datadog
Organizations are increasingly using multiple models to build AI agents in order to find the best balance of performance and cost for each agentic task and LLM call. As we discovered in the 2026 State of AI Engineering report, there isn’t currently a clear winner in terms of adoption among competing models and many organizations are keeping older models in flight despite frequent new releases.
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