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Real Time Network Monitoring: Topology, NetFlow, SNMP
Interface counters tell you a port is busy. Bytes in, bytes out, errors, drops. That’s enough to know a link is saturated, but not enough to know which conversations are saturating it, which devices are involved, or how a problem propagates across your network. For that you’ve traditionally needed dedicated network performance monitoring tools, usually expensive, usually a separate console from the rest of your monitoring.
Why you should use Language Server Protocol (LSP) with Claude Code
Agentic coding tools like Claude Code can write, refactor, and debug across an entire codebase, but by default they read code as plain text, the way grep does. The Language Server Protocol (LSP) changes that: it’s the same code-intelligence layer an IDE uses, and wiring it into an agent lets it read code by meaning instead of by string match. The bigger the codebase, the more a wrong guess about a symbol costs, and the more that structural view pays off.
CloudZero Dimension Studio: A drag-and-drop UI at the foundation of AI ROI
The core of ROI is visibility. If you can clearly see … 1. What it costs to produce the thing you make, and 2. How much money it makes you … then calculating ROI is easy. But with AI, as with the cloud before it, getting that visibility is extremely challenging. Why? Because the cost data associated with each is inherently chaotic.
Shipped: Your Explorer setup, remembered
CloudZero Explorer now tracks your query history and lets you save up to 12 configurations and 10 favorite dimensions, so your most-used cost analyses are one click away.
How to Replace the SharePoint Preservation Hold Library (2026)
The Preservation Hold Library silently inflates SharePoint storage. Replace it with Squirrel Recycle Bin Capture for compliant retention in customer-owned Azure.
The software supply chain threat landscape - 2026 and beyond
AI is accelerating both sides of the supply chain problem. Developers ship faster using it. Attackers use it to find vulnerabilities, create malicious packages, and automate social engineering.
What is an AI software factory?
Ask a software engineer what they do and the answer, for years, has been some version of "I write code." That assumption is unwinding fast. AI agents can now write code, review pull requests, run tests, and ship to production, and they're taking on a fast-growing share of that work. As agents absorb more of the execution, the human role shifts.
The New Software Creator: Why AI Changes the Governance Problem, Not Just the Speed Problem
The conversation about AI and software development has mostly been about velocity. Developers write code faster. Pull requests ship sooner. Backlogs shrink. That part is real, and it matters. But there's a bigger shift happening underneath it, and most engineering leaders I talk to are only just starting to feel its weight. AI hasn't just made developers faster. It has fundamentally expanded who can create and ship software. That changes things in ways that velocity metrics don't capture.
Cut your environment setup time in half with Chunk sidecar snapshots
When you’re building with AI, you can get a lot done in 30 seconds. Waiting minutes for CI feedback on your latest change can feel like an eternity. Chunk sidecars are designed to give you feedback fast, running your full test suite against the same Linux environment as CI, directly inside the agentic loop. Traditional CI pipelines can take five or ten minutes to catch a basic lint error or failing unit test.