Observability is made up of metrics, logs, and traces. These pillars help us understand the behavior of applications under normal execution, which further accelerates identifying anomalies in case of application failure or deviation from normal execution. Logging is not about tracing each and every operation, it is about sensible, consistent, and machine-readable log messages that expose the application behavior.

We often say that Honeycomb helps you find a needle in your haystack. But how exactly is that done? This post walks you through when and how to visualize your data with heatmaps, creating a log scale to surface data you might otherwise miss, and using BubbleUp to quickly discover the patterns behind why certain data points are different.

Share When it comes to serverless applications, their distributed nature of exponential scalability and use of potentially thousands of resources automatically begs the need for observability. Using the mass data output of an application to understand and optimize the internal states is a game-changing strategy, but only if used well. Dashbird Atlas takes serverless observability to a new level, reducing excessive noise through simple visualization of your application.