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Logs are very useful for understanding what happens within the cluster, from debugging to monitoring activities. Sometimes, however, the infrastructure where the applications run does not have native tools that offer exhaustive logs. For example, if the container, pod, or node stopped working or were deleted, we would also lose our logs. Therefore, it is advisable to store the logs separately, inside or outside the cluster, to understand the source of the problem or to reuse them in future analysis. This is called cluster-level-logging. Kubernetes does not natively have this paradigm, so sometimes you have to rely on external software. Here we will use ElasticSearch&Kibana. Kibana is an open source data visualization dashboard for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data.
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