Application Performance Monitoring (APM), tracing, and observability are fundamental software development and system management approaches. Each of these three concepts uniquely ensures that your applications operate, efficiently, smoothly, and reliably. Your organisation will more than likely already adopt one of these approaches, or even two, potentially all three.

Do you find yourself lying awake late at night, worried that your greatest observability fears will materialize as one of the most horrific specters of Kubernetes-driven chaos reaches up through your mattress to consume your very soul?

Are you one of the many companies harnessing the power of Heroku to build, deliver and scale your applications seamlessly? If so, you're likely aware of the need for robust observability to ensure your Heroku environment runs smoothly. Let’s delve into the world of Heroku monitoring and explore how Sumo Logic, a leading observability platform, can provide invaluable insights into your Heroku infrastructure and application logs.

You probably know that we have a generous free plan that allows you to send 20 million events per month. This is enough for many of our customers. In fact, some have developed neat techniques to keep themselves underneath the event limit. I’m going to share one way here—hopefully no one at Honeycomb notices!

Large Language Models (LLMs) are all the rage in software development, and for good reason: they provide crucial opportunities to positively enhance our software. At Honeycomb, we saw an opportunity in the form of Query Assistant, a feature that can help engineers ask questions of their systems in plain English.

From an IT perspective, technologists generally agree that the ability to monitor and have visibility into the IT stack across every one of their applications is essential with the now-permanent remote and hybrid work models. It also stems from the fact that digital transformation and IT growth has accelerated by seven years since the pandemic in 2020, analysts say.

Simply put: Observability is the ability to measure the internal states of a system by examining its outputs. A system is considered “observable” if the current state can be estimated by only using information from outputs, namely sensor data. More than just a buzzword, the term “observability” originated decades ago with control theory (which is about describing and understanding self-regulating systems).