Open CPU and memory live chartsįrom the main menu, select View | Tool Windows | Profiler. Sometimes it is enough to figure out the cause, and when it is not enough, it can give a clue for the further investigation. It's also possible to find these values manually by inspecting the cgroup interface files, although some manual calculations are required to determine CPU usage as a percentage.IntelliJ IDEA provides a way to monitor live performance statistics for a running process.Īs opposed to viewing static figures, live data may help you to visualize resource consumption, identify resource-related bottlenecks, and understand how certain events affect the program performance.įor example, in the picture below, we can see how a memory leak looks like in the Heap Memory chart. The metrics server provides a convenient method for inspecting the CPU and memory resources of your Kubernetes pods and nodes. You can find more information on these files in the Linux kernel docs. Convert the usage_usec value to nanoseconds by multiplying it by 1000, at which point it can be used in the same calculations returned by the age file. Note the usage_usec value is measured in milliseconds, unlike the value returned by the age file, which is in nanoseconds. As with value returned by the cgroup v1 age file, this value must be converted into a CPU usage percentage to be useful. This prints a file with a value called usage_usec. Print the current cpu usage with the command: cat /sys/fs/cgroup/cpu.stat On systems with cgroups v2, print the current memory usage with the command: cat /sys/fs/cgroup/memory.current If the directories /sys/fs/cgroup/memory or /sys/fs/cgroup/cpu don't exist, you're likely working on a system with cgroups v2. This post on Stack Exchange provides more details, and this Python code provides a useful practical example. The CPU time (in nanoseconds) obtained by this groupĬonverting this value into a more usable measurement like CPU usage percentage requires some calculation. Note the value returned by age is not immediately useful as it returns: Print the current cpu usage with the command: cat /sys/fs/cgroup/cpu/age Print the current memory usage with the command: cat /sys/fs/cgroup/memory/age_in_bytes If the metrics service isn't available, it's still possible to determine the memory usage of a single pod by entering an interactive session and printing the contents of cgroup interface files.Įnter an interactive session with the following command, replacing podname with the name of the pod you wish to inspect: kubectl exec -it podname - sh In this case, you can install the metrics server with the instructions on GitHub. The following error indicates that the metrics server is not installed: error: Metrics API not available Node resource usage is available with the command: kubectl top node Although the metrics server isn't built into Kubernetes, most clusters either bundle it or provide an easy solution for enabling it.Īfter the metrics service is installed, pod resources are displayed with the command: kubectl top pod The metrics server provides Kubernetes clusters with a lightweight and highly scalable solution for collecting CPU and memory resources. In this post, I show you how to view the CPU and memory usage of pods in Kubernetes. But how do you track resource usage of pods spread across a Kubernetes cluster? Tracking the resource usage of local processes is relatively easy in Linux with the top or htop command.
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