Sidecar Resource Requests PPS
Spec #
This is a top-level attribute of the pipeline spec.
{
"pipeline": {...},
"transform": {...},
"sidecarResourceRequests": {
"cpu": number,
"memory": string,
"gpu": {
"type": string,
"number": int
}
"disk": string,
},
...
}
Attributes #
Attribute | Description |
---|---|
cpu |
The minimum number of CPU cores that the storage container will reserve. |
memory |
The minimum amount of memory that the storage container will reserve. This can be specified in bytes, or with a unit such as “Mi” or “Gi”. |
gpu |
An optional field that specifies the number and type of GPUs that the storage container will reserve. |
type |
The type of GPU to use, such as “nvidia” or “amd”. |
number |
The number of GPUs that the storage container will reserve. |
disk |
The minimum amount of disk space that the storage container will reserve. This can be specified in bytes, or with a unit such as “Mi” or “Gi”. |
Behavior #
The sidecarResourceRequests
field in a HPE Machine Learning Data Management Pipeline Spec is used to specify the resource requests for the storage container that runs alongside the user container.
In a HPE Machine Learning Data Management Pipeline, the storage container is used to perform additional tasks alongside the user pipeline container, such as logging, monitoring, or handling external dependencies. By specifying resource requests for this sidecar container, you can ensure that the storage container has enough resources reserved as to not impact the performance of the user container.