In our continuous journey to support teams grappling with the complexities of Kubernetes environments, we’re thrilled to announce the launch of Honeycomb for Kubernetes, a dedicated solution designed to bridge the growing divide between infrastructure/platform teams and application developers. This is available to all plans (including Free!) at no additional cost.

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).

Logz.io is always growing and evolving based on customer usage and feedback. We add new features and quality of life improvements all the time. Here’s the round up of what we released in 2023 Q3.

As systems increasingly shift towards distributed architectures to deliver application services, the roles of monitoring and observability have never been more crucial. Monitoring delivers the situational awareness you need to detect issues, while observability goes a step further, offering the analytical depth to understand the root cause of those issues. Understanding the nuanced differences between monitoring and observability is crucial for anyone responsible for system health and performance.

Over the last year or so, the unavoidable topic of overwhelming cost has emerged as the number one issue among today’s observability practitioners. Whether it is in conversations among end users, feedback from customers and prospects, industry chatter or the coverage of experts including Gartner, the issue of massive telemetry data volumes driving unsustainable observability budgets prevails.