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In production systems mostly when working in microservices architecture, it is soon realized that monitoring each service individually is often not enough to troubleshoot complex issues. It becomes a necessity to have a full picture of the whole call stack through the entire application with detailed information on service topologies, network latencies and individual request durations. This is usually where distributed tracing comes to the rescue. In this post, the concept of distributed tracing will be introduced in microservices architecture.
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At Banzai Cloud we develop a container management platform that provisions and orchestrates hundreds of Kubernetes clusters across six different cloud providers or hybrid clouds every day. Pipeline makes it easy for users to run applications on Kubernetes, but under the hood there is an insanely complex system, so it’s mission critical for us to have realtime information about what’s happening inside the platform and have access to historical data to investigate incidents our customers may have had.
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Observability is a key feature of the Banzai Cloud Pipeline platform - we put significant effort into monitoring and centralized log collection - and, recently, into tracing. Instrumentation Instrumentation is the process of monitoring/measuring software performance, writing logs and trace information and, more generally speaking, of collecting information that helps us to diagnose errors, run software with maximum availability, to understand how the software operates and, more importantly, how it impacts users and businesses.
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