Gaining affordable, in-depth insights is always the first observability task of engineering teams. When you take a conventional, monolith-friendly monitoring architecture and try to graft it onto a distributed, cloud-native app problems arise - you can no longer have both.Centralized architectures, where raw data is being trucked all the way to the observability provider before being digested for insights (such as metrics), have started to weigh heavy on their teams - usually by way of immense burdening costs. Suddenly to get the desired logs, metrics and traces, teams had loads more data to collect, since a monolithic single app now gave way to a complex array of microservices. A new breed of observability architectures are out there and it’s time we all get acquainted. These architectures collect and digest raw data in a distributed manner, where the data actually lies. They break the link between the data volume monitored and the volume of data being sent, handled, and stored to support in-depth monitoring insights - reducing costs, network usage and irrelevant data collection. We’ll delve into a real life implementation of such an approach, showing how it can redefine modern observability today, and allow sustainable scale in the future.
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0:00 Intro
0:22 Talk
