1. Background and Prerequisites Compared with Ext4, Btrfs is a younger file system with more features to play with — snapshots, subvolumes, checksum self-verification, software RAID, and even transparent compression. That said, if you do not have the operations capability behind you, it is best not to use Btrfs. This article records the process of pulling a Btrfs disk out of a Synology DSM system and reading its data.

Clusters that run for a long time often face various kinds of resource exhaustion. On top of that, when disk space runs low, Kubelet will proactively clean up images on its own, adding another source of uncertainty. This article provides some command snippets for cleanup work. 1. Cleaning Up Basic Kubernetes Objects Clean up Pods in Evicted state 1 sudo kubectl get pods --all-namespaces -o wide | grep Evicted | awk '{print $1,$2}' | sudo xargs -L1 kubectl delete pod -n Clean up Pods in Error state 1 sudo kubectl get pods --all-namespaces -o wide | grep Error | awk '{print $1,$2}' | sudo xargs -L1 kubectl delete pod -n Clean up Pods in Completed state 1 sudo kubectl get pods --all-namespaces -o wide | grep Completed | awk '{print $1,$2}' | sudo xargs -L1 kubectl delete pod -n Clean up unused PVs 1 sudo kubectl describe -A pvc | grep -E "^Name:.

1. How Logstash Works Logstash is a component for data transport and processing. Through combinations of plugins, Logstash can handle a wide variety of log collection scenarios: logstash->elasticsearch filebeat->logstash->elasticsearch filebeat->kafka->logstash->elasticsearch filebeat->redis->logstash->elasticsearch 2. Basic Logstash Configuration Here is the format of a Logstash configuration: 1 2 3 4 5 6 7

1. Error message When pulling an image, you will occasionally run into the following error: 1 2 3 4 5 6 7 8 docker pull node:10.16-alpine 10.16-alpine: Pulling from library/node e7c96db7181b: Already exists 50958466d97a: Pulling fs layer 56174ae7ed1d: Pulling fs layer 284842a36c0d: Pulling fs layer error pulling image configuration: Get https://production.

Judging from the survey data, more people lean toward choosing small clusters. Below is a comparison list from the perspective of node count and node configuration. Below is a comparison of choosing a few large clusters versus many small clusters: Feature A few large clusters Many small clusters Resource utilization High Low Node management overhead Low High Resource scaling range Large Small Resource scheduling range Large Small Efficiency of inter-application communication High Low Cluster operations difficulty High Low Cluster version diversity Low High Blast radius Large Small Below is a comparison of choosing a few high-spec nodes versus many low-spec nodes: