Imagine that you’re receiving a support ticket that your application is not working fine. You read the attached stacktrace and now it’s time to solve the mystery - what did the user do that led to throwing of this exception? Is it possible to find all the logs from all the applications that correspond to this user’s business operation?
What if the user is complaining that the strategy is slow? How can you decide which concrete operation is the culprit? Is there any way to visualize the latency?
Let’s answer these questions by taking a deep dive into application observability utilizing distributed tracing, metrics, and correlated logs via Spring Cloud Sleuth, Tanzu Observabilty, OpenZipkin, OpenTelemetry, and more!
Lecture took place on Thursday, 23rd June 2022 at 16:00 in area 2
Sebastian Gębski - chief Solutions Architect at Amazon Web Services. ex-CTO, ex-VP of Engineering. He has co-built online platforms since 2001: across all kinds of organizations - starting with startups and ending with global financial groups, on 3 continents. He was designing solutions for improvement factories up to 300 people and leading engineering organizations up to 70 people. Hyper-active blogger (No Kill Switch), co-host of CTO Morning Coffee, and a serial reader. Fan of deliberate strategy plan (e.g. Semantic Spatial Maps), System's Theory, and applicable application of DSLs.
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