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cloudzero

The AI-nigma: FinOps Is Maturing - So Why Is Cloud Efficiency Falling?

Feb 12, 2026 By Larry Advey In CloudZero
Q: What do you call it when FinOps maturity surges but cloud efficiency plummets? A: An AI-nigma. I don’t claim to be a comedian. But I do claim to be Fred FinOps, so the paradoxical findings from CloudZero’s new report titled FinOps in the AI Era: A Critical Recalibration, created in partnership with B2B SaaS benchmarking firm Benchmarkit, had me scratching my head. The good news: These numbers tell a story of cloud cost maturity and control. But then there’s the bad news.
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cloudzero

Sustainable AI Investment: A Systems Thinking Approach

Feb 12, 2026 By Adam Tankanow In CloudZero
According to our new report, FinOps in the AI Era: A Critical Recalibration, 40% of companies now spend $10M or more annually on AI. Most can’t tell you if it’s working. That’s not a budgeting problem. It’s a systems problem. And Donella Meadows wrote the playbook for understanding it.
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xMatters

Turning Data Into Decisions with the xMatters Incident AI Agent

Feb 12, 2026 By Jon Skog In xMatters
When an incident hits, the gap between awareness and action can make all the difference. Responders know the pain: endless tool-switching, chasing updates, and fragmented data. It’s not a lack of capability that slows response; it’s the lack of context and connection. That’s why we built the xMatters Incident AI Agent, a purpose-built, conversational assistant that brings intelligence and automation directly into the heart of incident response.
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coralogix

Troubleshooting & RCA with Olly

Feb 12, 2026 By Lily Waldorf In Coralogix
If troubleshooting still feels harder than it should, check on these two numbers: how many dashboards you have, and how many alerts fire every day. For most teams, it’s hundreds of dashboards and thousands of alerts, a sign of maturity, coverage, and good intentions. On the other hand, we also see that when something actually breaks, that coverage rarely turns into clarity fast enough.
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speedscale

Silent Failures: Why AI Code Breaks in Production

Feb 11, 2026 By Ken Ahrens In Speedscale
You ship a small “safe” change on Friday. The diff is tiny, the tests are green, and the AI assistant was confident. An hour after deploy, your on-call channel lights up. A downstream service is rejecting responses that look fine in code review. Now you’re rolling back and rewriting a fix that should have been obvious if you had real traffic in the loop. This isn’t a hypothetical.
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Investigate Issues in Slack: Grafana Cloud Slack App with AI

Feb 11, 2026 By Grafana In Grafana
The Grafana Cloud app for Slack brings observability and incident response closer to where you and your teams already collaborate Ask questions about system health, alerts, on-call schedules, and Grafana Cloud features; manage incidents and alerts; and collaborate with full context.
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coralogix

Agent vs Assistant: The key distinction between Olly and the competition

Feb 11, 2026 By Chris Cooney In Coralogix
The market is saturated with agents and assistants, making it difficult to tell them apart. However, the difference between these two approaches is significant. They offer radically distinct levels of impact, reflecting major differences in both their technical complexity and the quality of their inferences. Let’s figure out the distinction.
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sentry

Sentry acquires XcodeBuildMCP

Feb 11, 2026 By Cameron Cooke In Sentry
Today we're announcing that Sentry has acquired XcodeBuildMCP, an open source MCP server that gives AI agents the ability to build, test, and debug native iOS and macOS apps. XcodeBuildMCP has become a go-to tool for agentic Apple-platform development, with more than 4,000 GitHub stars and an active community. It unlocks the full developer loop: build, run, debug, interact, and verify, allowing users to stay in their preferred agentic development environment.
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logicmonitor

A Step-by-Step Look at how Agentic, Autonomous ITOps Resolves Incidents

Feb 11, 2026 By Margo Poda In LogicMonitor
Agentic, autonomous ITOps improves incident response by carrying context from detection through resolution, reducing noise, delay, and manual coordination. Most IT incidents don’t fail due to missing data. Monitoring systems generate more than enough signals. The problem is that understanding those signals—and deciding what to do with them—happens in fragments. Engineers move between dashboards, logs, tickets, and chat threads, stitching together context by hand.
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What Agentic AI Is Really Made Of (Most People Miss This)

Feb 11, 2026 By Elastic In Elastic
Agentic AI isn’t just an LLM. Without the right context, it gives generic answers. This is the component that makes its decisions actually useful. Additional Resources: About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.
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