Hitachi

JP1 Version 12 JP1/Performance Management - Remote Monitor for Virtual Machine Description, User's Guide and Reference


1.7.4 Monitoring the memory resource

This subsection explains how to monitor the memory resource of a Docker container.

Organization of this subsection

(1) Overview

Multiple Docker containers share the physical server's memory resource. In a Docker container, processes run within the range of the memory resource that has been allocated to the Docker container.

You can understand used amounts of the memory resource that is being used by each Docker container.

The following PI_VMI record a used to monitor the memory resource. For details about records, see 5. Records. The PI_HMI record this indicate the memory resource of the physical server are not supported.

  1. PI_VMI record

    This record is used to monitor the amount of memory resources allocated to each Docker container.

The following figure shows the range of performance data collected in the PI_VMI record.

Figure 1‒71: Correspondence between records and data collection ranges

[Figure]

(2) Monitoring examples

This subsection explains the factors that cause insufficient memory resource of Docker containers and how to solve such problems.

The following figure shows the items monitored here and the flow of actions to take.

Figure 1‒72:  Monitored items and flow of actions

[Figure]

(a) Example of monitoring the total memory usage rate of a Docker container

You can monitor the memory usage rates of Docker containers in the Used % field of the PI_VMI record. If this value is large, the memory resources of the Docker container are considered insufficient.

The figure below shows a monitoring example.

Figure 1‒73: Example of monitoring the memory usage rate

[Figure]

Monitoring template report to be checked

VM Memory Trend

In this example, as the value of Used % for container1 has increased, insufficient memory resource of the Docker container may occur.

In this case, check the processes that are running in the Docker container. If the problem still cannot be solved, consider changing the Docker container's memory resource, changing the physical server that runs the Docker container, or taking other appropriate action.