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rguske.github.io | ||
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arveknudsen.com
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| | | | | In my previous blog post I showed how to use the Kops tool to create a production ready Kubernetes cluster on Amazon Web Services (AWS). In this follow-up post I will show how to install Elasticsearch and its graphical counterpart Kibana in the cluster, in order to be able to collect and store logs from your cluster and search/read them. We will also install Fluentd as this component is responsible for transmitting the standard Kubernetes logs to Elasticsearch. This is generally known as the ELK stack, which stands for Elasticsearch, Logstash (precursor to Fluentd) and Kibana. | |
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mherman.org
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| | | | | This tutorial looks at how to handle logging in Kubernetes with Elasticsearch, Kibana, and Fluentd. | |
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juliaferraioli.com
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| | | | | In the last few entries on creating a containerized Minecraft server, we created the container, launched the server, moved data to a volume, created regular backups of our world, took a look at customizing the server's properties, and updated changes to the container. Right now, our setup is pretty solid! So, let's get to that fun and impractical thing I mentioned that we'd be doing with Kubernetes. Lego® representation of a Minecraft mooshroom in a mushroom biome | |
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foo.zone
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| | | [AI summary] The text describes a comprehensive setup of a Kubernetes cluster (k3s) with various services and tools. It includes a private Docker registry, multiple applications like Anki Sync Server, Miniflux, and others, all utilizing NFS storage and UID/GID mapping for compatibility. The setup also involves relayd for traffic routing, Ingress controllers, and custom Helm charts for deployment. The author plans to expand on monitoring and observability in future posts. | ||
