Operations | Monitoring | ITSM | DevOps | Cloud

If you run Huntress across a fleet of client environments, you already know the console gives you a solid view of agent health, threat detections and incident reports. What it doesn't give you is a way to put that data next to everything else you're tracking, your PSA tickets, your other security tools, the rest of your stack, so you can see the whole client picture in one place.

Microsoft Defender does a great job protecting you and your organization from online threats. It is constantly working to detect and collect security data so you don’t have to worry about falling behind on incidents and vulnerabilities. The Defender portal can also provide great insights into that data, but connecting it to the rest of your stack is difficult.

In our previous article we looked at the basics of: In this article, we are going to take a deeper dive into some of the complexities of configuration as well as some of the nuances of analysing Claude telemetry. Before we dive into the code, let us just remind ourselves that our telemetry pipeline looks like this: That is, we are emitting Claude Code telemetry to an OpenTelemetry Collector. The telemetry is then exported to an Application Insights endpoint and stored in Log Analytics tables.

API responses are often easier to understand when they are displayed visually instead of as raw JSON. While Postman is widely used for testing APIs, many developers overlook one of its most useful features which is the Postman Visualizer. While it is not as fully featured as a dedicated dashboarding platform like SquaredUp, it is a great way to quickly visualize API responses during development and debugging.

Engineering teams are shipping more AI-generated code than ever, but at what cost? Learn how to build a telemetry pipeline to monitor Claude Code usage and costs directly in SquaredUp. It is estimated that 85-90% of engineering teams are now using AI coding assistants such as Claude, Codex and Cursor. This is not just for small-scale pilot projects— around 40% of all code now being shipped is AI-generated, and in start-ups the figure is around 95%. This can result in incredible productivity gains.

MSPs operate in high-pressure, customer-first environments where understanding exactly what is happening across client environments is the difference between proactive service and constant firefighting. Yet, many still struggle to get a unified view across their customers, tools, and teams.

Prometheus is a wildly popular open source monitoring tool typically used for monitoring Kubernetes environments and containerized workloads. But how do you turn the mountains of metrics into a clear picture of health and performance? SquaredUp plugs directly into your Prometheus database to visualize and monitor your data. What sets SquaredUp apart from other Prometheus visualization options like Grafana and Perseus is just how easy it is to visualize, monitor and share Prometheus dashboards.

No matter how fast we build, we'll never integrate with every tool. There are too many, new ones appear constantly, and some are too niche to ever reach the top of our roadmap. So if the tool you care about isn't supported yet, your options have been to wait for us to get to it, or build it yourself with our Web API plugin — a powerful, flexible option, though one that asks you to map out the endpoints, authentication and paging yourself.

If you manage endpoints for a living, you'll know the problem isn't a lack of data. It's that there's too much of it, scattered across too many places. A modern IT team or MSP might be looking after thousands of devices spread across dozens of customer organizations, each generating a constant stream of alerts, patch results, antivirus events and disk warnings. NinjaOne does a great job of collecting all of that.

Data is almost always scattered across too many tools. Usually, if you want to see it all in one place, you're stuck building messy pipelines or paying for a warehouse you don't really want. SquaredUp is a window into all those tools. It lets you see what’s happening across your entire stack in real time without moving any of the data. Think of it as a universal translator that lets your tools talk to each other so you can stop the manual digging and just see the big picture.