We've just rolled out another new feature: a 'Stats Overview' area where you can view a summary of the stats for all your monitors at a glance. There have been several requests for this feature from customers who want to view the most important stats for their websites in one place. Here are the details...

HiveMQ is an open source MQTT-compliant broker for enterprise-scale IoT environments that lets you reliably and securely transfer data between connected devices and downstream applications and services. With HiveMQ, you can provision horizontally scalable broker clusters in order to achieve maximum message throughput and prevent single points of failure.

Tracing is a widely adopted solution to provide performance insights into distributed applications. It is a valuable resource for developers to view the service call graph and track service latency at a granular level. It’s also a handy tool for on-call engineers to drill down and debug a problematic service during an outage. There are a number of open source distributed tracing frameworks out in the wild, including Jaeger, Zipkin, and OpenTelemetry.

If you follow our very own @HLENKE, you might have seen his recent tweet. Availability and responsiveness are key topics for every SaaS platform. They also happen to be multi-level, complex topics that often span different technology stacks and can be tackled with a variety of approaches. Hannes' tweet actually gives us the perfect segue into a blog post about how our engineering team currently monitors Checkly.

Information Technology (IT), like many other industries, is tapping into the latest advancements in Machine Learning (ML) and Artificial Intelligence (AI) to solve a decades-old problem in the IT management world. History can teach us many things, and by diving into years of accumulated IT data, we can find meaningful insights and use them to guide the future.

Practicing observability isn’t just about tools. It also means improving how you work together and how you share lessons across the team. Learning from each other helps everyone on your team become better engineers that can create amazing experiences with code, or that make code work at incredible scale (or both!). Writing software and operating it in production is—and must be—a team sport.