How do you optimize Jaeger performance and reduce resource consumption in a cloud-native environment?
Jaeger is a popular open-source tool for distributed tracing, which helps you monitor and troubleshoot complex microservices-based applications. However, Jaeger can also consume a lot of resources, such as memory, CPU, and network bandwidth, especially in a cloud-native environment where services are dynamic and ephemeral. How can you optimize Jaeger performance and reduce resource consumption without compromising its functionality and usability? Here are some tips and best practices to help you achieve that.
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