Openmetrics-exporter, or OME, is an Observability-as-Code framework that reduces the toil of finding-and-combining useful metrics from layers and hundreds of components involved in modern cloud-native systems. Every source, component, or metric is just a simple configuration file because the only “code” you should focus on is for your customers.
It leverages plugin architecture to support data sources. It relies heavily on data frame processing to combine metrics from various metrics sources before they are all converted into Openmetrics format, ready to be piped out by a Prometheus. Traditionally, such correlation and post-processing have been the responsibility of additional Data Pipelines, but with OME, it’s as simple as writing a configuration file. At its core, OME uses Hashicorp Configuration Language (HCL) to build a DSL that can allow declarative input to build metric Pipelines.
The talk is mainly about what you can solve using OME. But it also takes a concise journey of “behind-the-scenes” The need to build Openmetrics-exporter, picking a configuration language that was easily editable by humans, creating a DSL around it, and, more importantly, leveraging Golang for Data Science needs.
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