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At Banzai Cloud we are passionate about observability, and we expend a great amount of effort to make sure we always know what’s happening inside our Kubernetes clusters. All clusters provisioned with Pipeline - our multi- and hybrid-cloud container management platform - are provided with, and rely upon, each of the three pillars of observability: federated monitoring, centralized log collection and traces. In order to automate log collection on Kubernetes, we opensourced a logging-operator built on the Fluent ecosystem.

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Logs (one of the three pillars of observability besides metrics and traces) are an indispensable part of any distributed application. Whether we run these applications on Kubernetes or not, logs are one of the best ways to diagnose and verify an application state. One of the key features of our Kubernetes platform, Pipeline, is to provide out-of-the-box metrics, trace support and log collection. This post highlights some of the behind the scenes automation we’ve constructed in order to achieve this.

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