Operations | Monitoring | ITSM | DevOps | Cloud

Buy vs Build in the Age of AI (Part 2)

In Part 1, we explored how AI has dramatically reduced the cost of building monitoring tooling. That much is clear. You can scaffold uptime checks quickly, generate alert logic in minutes, and set-up dashboards faster than most teams used to schedule the kickoff meeting. So the barriers to entry have fallen. But there’s a quieter question that rarely gets asked in the excitement of building. Have you ever calculated what it would actually cost to replace your monitoring provider?

How to choose a secure private cloud provider for your enterprise

Enterprise private cloud procurement tends to generate impressive security documentation. SOC 2 reports, penetration test summaries, ISO 27001 certificates, detailed descriptions of network segmentation and encryption standards. What it doesn't always generate is clarity on the question that actually matters: does this infrastructure make it possible to operate securely at the level your organization requires, given your specific workloads, your regulatory context, and your threat model?

MCP vs. CLI for AI-native development

Summary: The CLI vs. MCP question is really a question about where you are in the development loop. CLIs fit the inner loop: fast, local, zero overhead. MCP servers fit the outer loop: external systems, shared infrastructure, structured access. Most teams need both. AI has put a new kind of scrutiny on developer tooling. When a developer works alongside an AI coding assistant, the tools that assistant can reach, and how it reaches them, directly affect the quality and speed of the work.

What is Ambient AI in Healthcare? Revolutionizing Clinical Care, Efficiency, and Outcomes

You probably use ambient AI every day without even knowing it. When your Apple Watch is telling you to stand up after sitting too long, your CGM recommends you eat a snack, or even when your smart home lights dim around the time you go to bed, every night…that’s ambient AI. Among other things, ambient AI is there to help you stay healthy, tracking what you do in the background and making decisions based on your previous actions and preferences.

Global Industrial Leader Coordinates Severity 1 Incidents with Clarity and Speed

“The first 15 minutes of a Sev-1 incident often determine the next 15 hours.” For a multi-billion dollar global industrial leader, managing Severity 1 incidents across a complex, distributed infrastructure is a high-stakes operation. When systems go down, the impact is felt instantly across production lines and global logistics.

Resolve's Agents of IT podcast - S2Ep5 - Ari's Hot Takes #itautomation #claude #aiautomation #ai

In this episode of Agents of IT, Ari Stowe and Ian Coppock unpack the recent Claude outage and what it reveals about our growing dependence on AI at work. From developers suddenly returning to Stack Overflow to the infrastructure challenges behind AI scaling, the conversation explores what happens when AI becomes critical enterprise infrastructure. They also discuss how organizations should prepare for AI outages, why “stampede adoption” is the new reality of AI releases, and what resilient, multi-agent architectures could look like going forward.

Static and Dynamic Tagging in N-central and N-sight

Static and Dynamic Tagging in N-central and N-sight In this demonstration, N-able Head Nerd Jason Murphy shows how tag management helps teams organize devices, prioritize support, and streamline day-to-day operations across customer environments. You will see how static and dynamic tags are used to identify VIP devices, track onboarding status, reflect SLA tiers, and create rule-based views that stay accurate as environments change.

Shadow AI and the Coming Workplace Reckoning (w/ Kay Firth-Butterfield)

In this episode of The DEX Show, we’re joined by Kay Firth-Butterfield, the world’s first Chief AI Ethics Officer and former Head of AI at the World Economic Forum. From human rights law and human trafficking to Davos and large language models, Kay traces her remarkable journey into AI governance. We explore shadow AI, workplace “hallucinations,” AI companions, and the hidden risks leaders are underestimating. Kay shares why organizations need cross-functional AI governance, stronger guardrails, and far better training — and why the future of work may depend as much on the humanities as technology.