Operations | Monitoring | ITSM | DevOps | Cloud

upsun

Agent security starts with where the agent runs, not how it behaves

Aug 4, 2026 By Upsun In Upsun
When engineering teams evaluate AI agents, the first questions are usually about capability. Which model performs best? How much faster can it write code? What's the return on investment? Security, if it enters the conversation at all, tends to come later. Patrick Dawkins, Principal Software Engineer at Upsun, thinks that's backward. Over the past year, he's been building the infrastructure that enables AI agents to operate safely within engineering teams.
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cloudzero

Railway Mania, the birth of the S&P 500, and the lesson for the AI era

Aug 4, 2026 By Brady Lenahan In CloudZero
In 1846, Britain poured roughly 7% of its national income into railways, proportionally about three times what the U.S. spends on AI infrastructure today. The technology delivered everything it promised, and a generation of investors still lost their shirts. What sorted the winners from the wreckage wasn't conviction about the technology; it was whether ROI was measured or asserted. The man who fixed that problem gave his name to the S&P 500.
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How SigNoz MCP Helped MSI Find 20 Unnecessary Operations

Aug 4, 2026 By SigNoz - Open Source Observability Platform In SigNoz
Taylor Mattison explains how SigNoz MCP helped surface wasted work inside MSI's sales-order workflow. Warning checks were firing on user actions that had nothing to do with any warning they could raise. By comparing telemetry across the workflow, Taylor could point to unnecessary operations that were wasting API calls, database time, and server capacity. This clip is part of our MSI customer story on using SigNoz MCP with Claude to debug slow sales orders across the stack.
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influxdata

Where Historians Fall Short for Physical AI

Aug 4, 2026 By Ryan Nelson In InfluxData
Summary Physical AI—machines and industrial systems that sense conditions, reason, and act in the real world—needs two things from operational data: detailed history for training, and real-time telemetry for inference. Traditional data historians weren’t built for either at the speed Physical AI requires. Four gaps result: limited real-time access, compression that strips model-relevant signal, IT/OT fragmentation, and site-by-site architectures.
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Building an AI Observability Agent: Lessons from the Trenches - Stripe at O11yCon 2026

Aug 4, 2026 By Honeycomb In Honeycomb
Stripe shares lessons from building an incident investigation agent, from context-window blowups to why the final 5% still needs a human. In this O11yCon 2026 talk, they dig into what it takes to go from 'it works' to 'it works reliably,' including how pointing agents at like Honeycomb's speeds up on-call investigations.
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harness

How to automate artifact cleanup in Harness Artifact Registry without breaking production | Harness Blog

Aug 4, 2026 By Shibam Dhar In Harness
AI is changing artifact management in two ways at once. Every AI-generated pull request, dependency update, and automated build creates more container images, packages, and Helm charts than ever before. Registries are growing faster than engineering teams can manage them, driving up storage costs and leaving thousands of stale artifacts behind. At the same time, the cost of deleting the wrong artifact has never been higher.
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Running LLM Workloads in Production: An Operations Playbook for Teams That Did Not Sign Up for This

Running LLM Workloads in Production: An Operations Playbook for Teams That Did Not Sign Up for This

Aug 4, 2026 By OpsMatters In OpsMatters
Somewhere in the past two years, AI quietly became an operations problem. The proof of concept your product team shipped - a support-ticket summarizer, a natural-language search box, a code-review assistant - graduated into a production dependency, and now it pages you. The failure modes are unfamiliar: latency distributions with tails measured in tens of seconds, upstream providers that throttle without warning, costs that scale with user enthusiasm rather than infrastructure size, and outputs that can be wrong in ways a health check will never catch.
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Why Responsible Technology Use Matters

Why Responsible Technology Use Matters

Aug 4, 2026 By OpsMatters In OpsMatters
Technology plays an integral role in our lives today. Technology is applied in communications, education, business, shopping, and various other tasks we undertake daily. The emergence of new forms of technology such as Artificial Intelligence, Cloud Computing, and IoT has made life more comfortable, but at the same time, they present challenges including privacy concerns, cyberattacks, and the spread of misinformation, among others.
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honeycomb

Spend More Time Talking to Humans

Aug 3, 2026 By Douglas Soo In Honeycomb
A few months ago, I noticed something happening. I would spend all day working with LLMs—prompting them, reviewing their work, and correcting them—and when I wasn’t working on my own code, I was reviewing LLM-generated code. By the end of the day, I was exhausted. This was a very unusual thing for me: I’ve been a software developer at startups for 30 years, and while sometimes I might have gotten stressed out, I had never been exhausted by the actual act of writing code.
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