Hosts Host memory usage exceeds threshold 1 - node_memory_MemAvailable_bytes{mode!="idle"} / node_memory_MemTotal_bytes Threshold: 0.9 Host CPU usage exceeds threshold 1 - avg(irate(node_cpu_seconds_total{mode="idle"}[5m])) by (host_name) Threshold: 0.85 Host disk usage exceeds threshold 1 - avg without (fstype)(node_filesystem_free_bytes{fstype!='rootfs',mountpoint!~'/(run|var|snap).*'} / node_filesystem_size_bytes{fstype!='rootfs',mountpoint!~'/(run|var|snap).*'}) Threshold: 0.8 Windows Windows host memory usage exceeds threshold 1 - 1 * windows_os_physical_memory_free_bytes{job="windows_exporter",mode!

1. Host Service Ports 1 2 iptables -I INPUT -p tcp --dport 80 -j DROP iptables -I INPUT -p tcp -s 1.2.3.4 --dport 80 -j ACCEPT This allows only 1.2.3.4 to access port 80 on the local host. 2. Docker Service Ports For services started like docker run -d -p 80:80 shaowenchen/demo:whoami, the method above does not work; the rule has to be added to the DOCKER-USER chain.

1. Traffic Control Principles Under Linux By queuing packets, we can control how data packets are sent. This kind of control is called data shaping (shape the data), and it includes the following operations on data: Adding latency Dropping packets Reordering Duplicating, corrupting Rate control Under the qdisc-class-filter structure, controlling traffic requires three steps:

1. Background At 10:00 in the morning, a colleague asked me to run a task on the cluster, so I created a Kubernetes Job through a tool. When the tool creates a Job, it first gets all the nodes on the cluster, then binds to each node one by one to create Jobs.

1. Authentication and Authorization Problems Brought by Heterogeneous Systems Enterprise systems can be divided into the following types: Commercial software you purchase, such as JumpServer Open-source software, such as Kibana and Grafana Software developed in-house, such as an application management platform One thing worth clarifying here: authentication and authorization are two different functions: