The sum of the total CPU time of all executions within the scope of the selected object. Note that the total CPU time can exceed the total duration of the execution if the average CPU load was over 100%. The effective utilization time of the CPU during the aggregated execution. Retrieve it using the following fields and aggregates: For every sample, Engine calculates the effective CPU utilization of each process during its execution. Collector sends the CPU samples to Engine every 5 minutes. Note that the maximum instantaneous load of CPU may not occur simultaneously with the moment when Collector takes a sample. For instance, a device with 12 logical processors has a maximum CPU load capacity of 1200%.Ĭontrary to memory usage samples, the system does not average CPU samples before sending them to Engine, which lets Engine know about peaks of CPU utilization. Therefore, the CPU load can be higher than 100% for devices with multiple logical processors. The system measures the CPU load as a percentage value from 0 to 100 for each logical processor that is present in the device. In the case of CPU usage, Collector takes samples of the CPU load of all running processes every 30 seconds. This is because Chrome reports the memory utilization per process before processes are aggregated in Engine. Therefore, Firefox will typically report a higher average memory usage than Chrome for similar use cases when multiple tabs are open. Chrome creates a new process for every tab that the browser opens, while Firefox uses a single process for all tabs. A single binary may spawn several identical processes in memory, resulting in a total memory consumption higher than that of the individual processes.įor instance, we can look at the behavior of two well-known web browsers: Chrome and Firefox. Note that Nexthink calculates the memory usage per process before possibly being aggregated into a single execution. The average memory usage of the underlying execution with a sampling rate of 5 minutes The average memory usage of all the underlying executions divided by their cardinality The average memory usage of the execution before being aggregated Moreover, memory issues typically arise because of a sustained high consumption of memory and not because of short-lived allocations.īased on the data collected, Nexthink has made the following fields and aggregates available to measure memory usage: Therefore, there is always some uncertainty in the values Collector offers, but it is usually negligible for well-behaved applications. Note that if a process allocates and frees memory very quickly, Collector may miss some peaks of memory consumption when taking its samples every 30 seconds. Collector calculates the average value of these samples over 5-minute intervals to eventually send to Engine. Memory usageĬollector takes samples of the amount of memory used by each running process over a period of 30 seconds. Based on these figures, assess the amount of resources given to a particular device and find out which applications are most resource-hungry. In this article, learn about the fields and aggregate values that measure the usage of memory and processing power in Nexthink. Users that perceive their devices as slow usually suffer from scarcity or misuse of two basic system resources: main memory and CPU processing power. Measuring the utilization of hardware resources within each device in your organization is key to evaluating both the efficiency of devices and the impact of resource consumption on employee experience.
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