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As a feature to evolve the Observability of K8s, we will introduce the logging function that we are currently considering with the technical leader of the K8s community. If this function is introduced, even if many user operations are issued at the same time, it is possible to easily extract how a specific user operation was processed from the huge log of each component of K8s, and the time required for troubleshooting will be greatly reduced. With this presentation, audience will know how to significantly reduce the time required for troubleshooting of K8s itself. The presentation will also help revitalize the K8s Logging community and improve the Observability ecosystem. In K8s environment, Log investigation is one of troublesome things for users. Users use their knowledge, experience, and analysis tools to investigate, but it often takes time to identify the cause. The main reason is that K8s component log is independent structure. In K8s, many components work together just by performing one operation (kubectl apply, etc.) by the operator, so the log of one operation is distributed and output to multiple log files. Therefore, if an operation fails, it is necessary to extract and analyze the relevant parts from those distributed log files in order to analyze the cause.
