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Component Stats

With any production application, visibility into your servers' resource usage is incredibly important. They help to identify any possible bottlenecks and are a good indicator of what to scale and when to scale it. Service resource usage statistics are provided in your Nanobox dashboard.

Monitored Server Resources

To provide visibility into the health of your app, Nanobox collects RAM, CPU, Swap, & Disk usage from all components and nodes.

CPU

The CPU statistic indicates how much of the available CPU a component/node is using. CPU provides compute time, speed, and responsiveness. The higher the CPU usage, the more likely your service is to become slow or completely unresponsive. In multi-instance components, this is an average of CPU usage across all nodes in the cluster.

RAM

The RAM statistic indicates how much of the allotted RAM a component/node is using. The higher the RAM usage, the more likely your service is to become unresponsive. In multi-instance components, this is an average of RAM usage across all nodes in the cluster.

Swap

The Swap statistics indicates how much of the allotted swap space is used. Swap acts as a disk overflow when the system needs more memory and RAM is full. In multi-instance components, this is an average of swap usage across all nodes in the cluster.

Disk

The Disk statistic represents how much of your component's/node's allotted disk space is being used. If you run out of disk space, the component/node will not function properly. In multi-instance components, this is an average of Disk usage across all nodes in the cluster.

Summary View

Your Nanobox dashboard provides live stats as well as a summary of hourly historical stats.

Component Resource Usage Summary

Detailed View

Click on the "Stats" button under a component/node to view detailed historical hourly averages. In multi-component servers (bunkouses), you'll also see a summary of what each component is using of the available resources.

Expanded Component Resource Usage

Note: Historical averages are provided in hourly blocks. In some cases, a brief period of high resource usage may be lost in the hourly average.

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