Operations | Monitoring | ITSM | DevOps | Cloud

For many teams, Budgets is the first page they open in the morning, and it should tell them where they stand at a glance. That’s easier now, with a redesigned Budgets page and a way to set a budget without leaving the app.

Before agents were part of the picture, GitKraken Desktop had one job: make Git make sense. Visualize the commit graph, show branches and remotes clearly, and let a developer feel confident hitting merge. That job has not changed. What changed in GitKraken Desktop 12 is what sits on top of it.

Recently, Google released a couple new Gemini models. They were Gemini 3.6 Flash, 3.5 Flash Lite, and 3.5 Flash Cyber. Many people on the internet roasted Gemini Flash and Flash Lite for their less-than-frontier performance. This makes sense when you consider that OpenAI and Anthropic have been sparring back and forth for first place for quite a while but Gemini almost never gets that first place position. After all, this is Google we are talking about.

Enterprise IT work rarely stays inside one tool anymore, does it? A service request may start in an ITSM platform, require approval in a collaboration tool, trigger an identity change, update a system of record, and notify an employee when the work is complete. Likewise, an infrastructure incident may begin with a monitoring alert, require diagnostic checks, involve cloud or network systems, and end with validation, documentation, and escalation if remediation fails.

Reduce downtime and build a more resilient network with our practical tips for improving network availability. By Serena Toh and Matt Madawi Table of Contents Network availability is more than a technical metric (though it is an important one). The availability of your network is the difference between applications that keep serving customers and applications that stall when a link, device, data center, or provider fails.

Dynatrace gives engineering teams deep, real-time visibility into every service they run. That visibility is the foundation of every effective reliability practice, and it's exactly the foundation Gremlin is built to extend. Once you can see how your distributed systems behave today, the next step is knowing how they'll behave under failure tomorrow—and to do it before those failures happen.

An incident is open and the evidence is scattered. The application logs point to a connection timeout; the load balancer shows nothing unusual, and the container that produced the original error was replaced eighteen minutes ago. Three engineers are logged into three separate hosts running the same search, and the log line that would explain it has already rotated away. That is the moment most teams start shopping for a log file analysis platform.

An AI sandbox is an isolated environment where code from an AI coding agent runs without direct access to your machine or your production systems. If the agent runs a destructive command or a mistaken script, the damage stays contained inside the sandbox. Developers use AI sandboxing to let agents execute code freely while keeping the host and its credentials out of reach.

Terraform gives you two ways to express the same infrastructure. You can declare resources directly, or you can wrap them in a module and call that module with inputs. Both produce identical cloud objects. The choice is not about capability, it is about where you want the complexity to live and who you want to be responsible for it. Most teams get this decision wrong in one of two directions.