Are you overwhelmed by logs, metrics and traces? Are you unsure which type of data offers the most bang for your buck in terms of operational efficiency and system understanding? Is the deluge of data preventing you from seeing the forest for the trees? If you've ever felt lost in the forest of observability, know that you are not alone.

To navigate the observability journey, you need to shift the paradigm to outcome-first. Our journey will begin by questioning everything we thought we knew about the three mainstays of observability: Logs, metrics and traces. Why do we need them? What purpose do they serve? And most importantly, do they always provide ROI in every use case?

With a clear focus on the desired outcomes, we will explore which observability data can truly satisfy those outcome-focused needs. We will delve into which data is best for debugging and which can give you a clear picture of system state.

We'll also talk about the trade-offs between different types of data. For example, logs can be very detailed, but they can also be overwhelming. Metrics can be more concise, but they may not provide enough detail to troubleshoot problems. Traces can provide a complete picture of a request as it travels through a system, but can also be difficult to collect and analyze.

By the end of this talk, you'll have a better understanding of the different types of observability data and you'll be able to choose the right data type for your specific needs.