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A 200 GB disk, and df -h said only 54 GB was left — 72% used. Most days that is survivable. But this machine also runs a small Kubernetes cluster, and the moment an image pull or a build needs a few GB of scratch space, “three-quarters full” stops being a comfortable place to be. This is the write-up of two things: where the space actually went, and — the more important half — how I convinced myself that deleting it did not break anything that was running. ...

A small app of mine had been running quietly for months. Then one day, it showed: 15 restarts. The only log it produced was two lines: 1 2 3 4 Error: timed out Caused by: timed out The strange part: every other pod in the same cluster had restarted exactly 6 times. Same node, same moment — why did only this one crash 9 extra times? The answer turned out to be two problems stacked on top of each other. One was cluster-wide: all pods were being killed together. The other was app-level: only my app turned a brief dependency hiccup into a crash loop. ...

Quest Set up a strongswan vpn client on an Ubuntu 24.04 PC using network management GUI. The strongswan server only accept EAP-TLS authentication. Process bash command history 1 2 3 4 5 6 7 8 9 10 11 12 13 14 # install packages sudo apt update && sudo apt install libcharon-extra-plugins network-manager-strongswan strongswan-nm mkdir sw-vpn cd sw-vpn # download client certifacte and private key scp server_vpn:cmd-cmd-pc.tar.gz . # fix MTU issue vim custom.sh sudo cp custom.sh /etc/NetworkManager/dispatcher.d/01-vpn-mtu sudo chmod +x /etc/NetworkManager/dispatcher.d/01-vpn-mtu rm cmd-cmd-pc.tar.gz ls -alh /etc/NetworkManager/dispatcher.d/01-vpn-mtu cat /tmp/vpn_mtu_debug.log mtu fixer The custom.sh file ...

what’s kafka Kafka is a distributed streaming platform. Think of it as a high-throughput, fault-tolerant message queue on steroids. It’s designed for handling real-time data feeds. Concepts Topic: A category or feed name to which records are published. Partition: A topic is divided into partitions, which are ordered, immutable sequences of records. Partitions enable parallelism and scalability. Producer: An application that publishes records to a Kafka topic. Consumer: An application that subscribes to one or more topics and processes the records. ...