Operations | Monitoring | ITSM | DevOps | Cloud

Agentic Operations Start with Context: Build the Right Data Foundation

Sep 8, 2026 By Splunk In Splunk
Episode 1, "Beyond the Thread: Deconstructing the Cisco Data Fabric Powered by the Splunk Platform," explores the intersection of data strategy and operational efficiency. Hosted by Splunk's Courtney Wright, the session features insights from experts Keith McClellan and Michael Sondag on the complexities organizations face in data management and operational models.
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Assisted, Augmented or Agentic? Choose Your Splunk Starting Point

Sep 8, 2026 By Splunk In Splunk
Episode two of Beyond the Thread explores how organizations can leverage a solid data foundation for AI-driven actions. Hosted by Courtney Wright and featuring experts Greg Ainsley-Malik and Sonal Pardeshi, the discussion delves into the Cisco Data Fabric, powered by the Splunk platform, and its role in transforming machine data into actionable insights. The episode highlights the journey towards agentic operations, addressing the challenges faced in moving from AI-ready data to effective implementations, and examines different adoption strategies that organizations may pursue.
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VictoriaMetrics

Two cats, two dogs, four vendors, and the model the AI couldn't find (Tech Talk Companion)

Sep 7, 2026 By Michelle Sebek In VictoriaMetrics
Tech Talks went dark for a few months, and on episode 13 I finally got to ask why. Mathias Palmersheim’s answer, delivered completely straight, was that his users were unhappy with the availability and usability of their feeders and their litter box, and he wasn’t allowed back on stream until that got fixed. The users are two dogs and two cats, and they have titles. Maisie, a Shiba Inu who came to him through a rescue, is the recently promoted chief executive pawofficer.
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cloudzero

AI cost calculator: estimate your total spend

Sep 4, 2026 By Lyne Carolyne In CloudZero
An AI cost calculator for the whole wallet adds four lanes: seats and subscriptions, API and token usage, cloud AI services, and GPU infrastructure. Average 2026 totals run $25 per employee per month at light adoption, $100 to $150 at active adoption, and $300 or more at AI-heavy companies. Getting to your number takes four lane subtotals and three corrections.
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motadata

Agent vs Agentless Monitoring and How to Decide What Goes Where

Sep 4, 2026 By Poonam Lalani In Motadata
Why does half the infrastructure end up returning no monitoring data? The standard plan is to install collection software on everything, which moves quickly across servers and stops dead at the first device running closed firmware. Storage arrays, firewalls, and switches will never accept an install, and the rollout stalls there. That plan usually gets set once for the whole environment, with a single collection model applied to hardware it was never suited for.
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Microsoft Took 8 Months to Fix This Copilot Vulnerability

Sep 4, 2026 By Harness In Harness
Microsoft finally patched a critical Copilot vulnerability nearly eight months after researchers first disclosed it — and the way the attack worked raises some unsettling questions about AI memory. The vulnerability chained together multiple flaws that could allow a malicious prompt hidden inside a webpage to be pulled into Copilot simply by asking it to summarize the page. From there, the attack could potentially access connected data from services like Gmail, Google Drive, and Google Calendar and exfiltrate that information using Copilot’s own capabilities. But the most concerning part may have been persistence.
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scout

Prompts, skills, and the AGENTS.md nobody wants to write (and how Anthropic writes theirs)

Sep 4, 2026 By Jack Rothrock In Scout
You’ve watched Claude Code compact a conversation. The context bar fills, it pauses, a summary appears, and it carries on like nothing happened. You probably assumed a housekeeping script trimmed the transcript in the background. It didn’t. The model compacted itself. When the window fills, Claude Code sends a long, specific prompt telling the model how to summarize its own conversation. Then it does, same model, same turn. The thing managing your context window is just another instruction.
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Building AI Systems That Survive an Audit: Evidence Trails, Traceability and Compliance by Design

Building AI Systems That Survive an Audit: Evidence Trails, Traceability and Compliance by Design

Sep 4, 2026 By OpsMatters In OpsMatters
A model returns an answer with a confidence score of 0.94. The team ships it. Six months later someone asks why the system produced that specific answer, and nobody can reconstruct it. For years accuracy was the only number that mattered in machine learning. Get the error rate down, ship the model, move on. In regulated domains that is no longer enough. The harder question is whether you can defend a single decision after it has been made. Most systems were never built to answer that, and by the time someone asks, the information needed is already gone.
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