Operations | Monitoring | ITSM | DevOps | Cloud

Humanized AI Text for Stronger DevOps and Operations Content

Humanized AI Text for Stronger DevOps and Operations Content

Feb 28, 2026 By OpsMatters In OpsMatters
You create content for operations teams, DevOps engineers, SREs, and IT decision-makers. Topics include monitoring, incident management, cloud infrastructure, ITSM processes, and observability tools. AI generates initial drafts quickly. The results frequently come across as mechanical. Sentences follow predictable patterns. Technical explanations lose nuance. Readers in this field expect precise, practical language from experienced practitioners. They detect generated text easily. Engagement drops when content feels detached from real-world ops challenges.
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fabrix

How Fabrix.ai Agents Ensure Data Privacy & Security

Feb 27, 2026 By Shailesh Manjrekar In Fabrix
As Agentic AI moves into enterprise environments, IT and security leaders face a critical challenge on how to leverage advanced LLMs without exposing sensitive data, intellectual property, or proprietary configurations to the cloud. You cannot build a self-driving, autonomous IT infrastructure if your security team blocks the deployment, and that’s exactly why the Fabrix.ai platform features an Enterprise-Grade LLM Integration architecture anchored by our built-in Data Security layer.
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canonical

Canonical and Ubuntu RISC-V: a 2025 retro and looking forward to 2026

Feb 27, 2026 By Canonical In Canonical
2025 was the year that RISC-V readiness gave way to RISC-V adoption. It’s been quite a journey. What began years ago as early architectural exploration and enablement has matured into real silicon, systems, and deployments. In particular, RVA23 provides a stable and predictable baseline we can align on with our wider ecosystem of partners. At Canonical, we’re committed to making RISC-V a viable option for anyone who wishes to adopt it.
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logicmonitor

Why Evidence-Backed RCA in Edwin AI Starts With Logs

Feb 27, 2026 By Margo Poda In LogicMonitor
A step-by-step look at how Edwin AI uses native LogicMonitor logs, topology, and context to turn root cause analysis from alert-driven inference into evidence-backed investigation. Most root cause analysis today starts with alerts and ends with explanations that sound reasonable but can’t be verified. An alert is fed into a language model, and the output looks like an answer. It often isn’t.
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grafana

The rise of agentic AI in production: Can observability systems run themselves?

Feb 27, 2026 By Grafana Labs Team In Grafana
Sometimes the biggest shifts in technology aren’t about collecting more data — they’re about who (or what) gets to act on it. In this episode of “Grafana’s Big Tent” podcast, host Tom Wilkie, Grafana Labs CTO, is joined by Spiros Xanthos, Founder & CEO of Resolve AI, Manoj Acharya, VP of Engineering for Observability at Grafana Labs, and Cyril Tovena, Principal Engineer on the Grafana Assistant team, to discuss agentic AI in observability.
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From RCA to Autonomous Ops: The Future of AI in Observability | Big Tent S3E7

Feb 27, 2026 By Grafana In Grafana
SREs are famously skeptical of AI — so how do you convince them to trust agents in production? In this episode of Grafana’s Big Tent, Tom Wilkie talks with Spiros Xanthos (Resolve AI), Manoj Acharya (Grafana Labs), and Cyril Tovena (Grafana Assistant team) about agent-first observability. They unpack knowledge graphs, LLM reasoning, autonomous debugging, pricing models, and the “Claude Code moment” for observability. Is autonomous production ops closer than we think?
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