In-memory volumes (services)

This page describes how to configure a dedicated in-memory volume you can use for file reads and writes.

This feature differs from the built-in in-memory filesystem provided by Cloud Run, which does not limit the memory consumed by in-memory file writes. Using in-memory volumes, you can limit the amount of memory that can be consumed.

Behavior

After you configure an in-memory volume for your Cloud Run service, an empty volume is created for every Cloud Run instance that is started, and exists as long as that instance is running. When the instance stops running, the data in the volume is permanently deleted.

If you specify a limit for an in-memory volume and then exceed that limit when writing to the volume, you will get an out of memory error, which you can handle, and the instance will keep running. If you don't specify a volume size limit and then exceed the instance memory limit when writing to the volume, the instance will crash.

Volume ownership differs by execution environment and deployment type

When you mount a volume, the identity owning the files and directories differs depending on the workload's execution environment and on whether the deployment consists of one or multiple containers.

In the first generation execution environment where you are deploying a single container, the volume is owned by the identity used for the container. In all other cases, the volume is owned by root. This includes:

First generation execution environment where you are deploying multiple containers
The second generation environment

Use cases

Use cases for an in-memory volume include allocating scratch space or checkpointing a long computation to prevent crashes.

Configure an in-memory volume

Any configuration change leads to the creation of a new revision. Subsequent revisions will also automatically get this configuration setting unless you make explicit updates to change it.

If you specify a memory size limit for the volume, the memory is allocated from the memory used by all of the individual containers in the instance that access this volume. If you specify an in-memory volume size that is larger than the sum total of all memory used by the containers in the instance, the volume defaults to the sum total used by the containers.

If you don't specify a memory size limit for a volume, you can potentially exceed the instance memory limit and crash the instance.

If you use the in-memory volume as a shared volume in a multicontainer deployment without specifying an in-memory size limit, half of the total available instance memory is allocated for the shared volume. For example, emptyDir volume size = [Memory (Container A) + Memory (Container B) + Memory (Container N)]/2.

Console

Go to Cloud Run
Click on the service you want to configure.
Click the YAML tab.
Configure the volumeMounts and volumes attributes as shown:
```
apiVersion: serving.knative.dev/v1
  kind: Service
  metadata:
  annotations:
    run.googleapis.com/launch-stage: BETA
    name: SERVICE
  spec:
    template:
      metadata:
      spec:
        containers:
        - image: IMAGE_URL
          volumeMounts:
          - mountPath: PATH
            name: VOLUME_NAME
        volumes:
        - name: VOLUME_NAME
          emptyDir:
            sizeLimit: SIZE_LIMIT
            medium: Memory
```
replace
- SERVICE with the name of your Cloud Run service.
- IMAGE_URL with a reference to the container image, for example, us-docker.pkg.dev/cloudrun/container/hello:latest. If you use Artifact Registry, the repository REPO_NAME must already be created. The URL has the shape REGION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG
- PATH with the relative path to the volume, for example, /cache.
- VOLUME_NAME with the name you want to use for the in-memory volume.
- SIZE_LIMIT with the memory limit you want to assign to the volume, in MiB or GiB (specified as Mi or Gi), for example, 500Mi. This limit must be less than the total memory specified for your containers.
Click Save and Deploy new Revision.

YAML

You can download and view existing service configurations using the gcloud run services describe --format export command, which yields cleaned results in YAML format. You can then modify the fields described below and upload the modified YAML using the gcloud run services replace command. Make sure you only modify fields as documented.

To view and download the configuration:

gcloud run services describe SERVICE --format export > service.yaml

Configure the volumeMounts and volumes attributes as shown:
```
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
 annotations:
  run.googleapis.com/launch-stage: BETA
  name: SERVICE
spec:
  template:
    metadata:
    spec:
      containers:
      - image: IMAGE_URL
        volumeMounts:
        - mountPath: PATH
          name: VOLUME_NAME
      volumes:
      - name: VOLUME_NAME
        emptyDir:
          sizeLimit: SIZE_LIMIT
          medium: Memory
```
Replace:
- SERVICE with the name of your Cloud Run service.
- IMAGE_URL with a reference to the container image, for example, us-docker.pkg.dev/cloudrun/container/hello:latest. If you use Artifact Registry, the repository REPO_NAME must already be created. The URL has the shape REGION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG
- PATH with the relative path to the volume, for example, /cache.
- VOLUME_NAME with the name you want to use for the in-memory volume.
- SIZE_LIMIT with the memory limit you want to assign to the volume, in MiB or GiB (specified as Mi or Gi), for example, 500Mi. This limit must be less than the total memory specified for your containers.
Replace the service with its new configuration using the following command:
```
gcloud run services replace service.yaml
```