Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

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.

Since I started using Claude Code more frequently, I kept noticing a “worktree” checkbox popping up whenever I started a session in a Git repository. I had no idea what it meant, so I did what any curious developer would do and started digging. What I found was a Git feature I somehow never came across before: git worktrees.

Turn inventory data into actionable insights, build dashboards tailored to your needs, and expand visibility across Apple and ChromeOS devices.

Europe is in the middle of one of its most severe heat events on record, and the effects go well beyond public health. As temperatures across France, Spain, the UK, and Germany push into record territory, the strain on power grids, cooling systems, and physical infrastructure is becoming impossible to ignore. For data center operators, maintaining uptime in this environment demands the real-time visibility that modern Data Center Infrastructure Management (DCIM) software can provide.

Telegraf Enterprise is now generally available. It combines Telegraf Controller, a centralized management console for Telegraf, with official support from InfluxData. Open source Telegraf remains unchanged. Telegraf Controller is free to start with built-in limits, while a Telegraf Enterprise license unlocks higher-scale limits, audit logging, LDAP/OIDC integration, and commercial support. Telegraf has become the standard for collecting telemetry across cloud, edge, and physical infrastructure.

If your team bIf your team builds with Python or.NET, your packages have likely lived separately from your code, stored in a registry with distinct login, permissions, and billing. Starting today, they don’t have to. Bitbucket Packages now supports the Python Package Index (PyPI) and NuGet, integrating Python and.NET package management into the platform where your team writes code, reviews pull requests, and runs pipelines.

When we introduced native Pipelines authentication for Bitbucket Packages, we made it easier to publish artifacts from CI/CD without relying on personal credentials. Now we’re extending that integration further: package artifacts published through the Pipelines integration can display a Source Pipeline, making it easy to trace an artifact back to the pipeline run that created it.

In November 2025, we introduced new triggers and workflows to Bitbucket Pipelines to help teams manage and scale complex CI/CD workflows. We later extended that foundation with additional event-based triggers for pipeline, deployment, and pull request events. We’re now extending that model with a new package-artifact-created trigger.