Google Distributed Cloud connected uses quotas and system limits to maintain fair resource
allocation, prevent service overloads, and help you manage resource use.

Quotas and system limits are similar but differ in the following ways:

- *Quotas* have default values, but you can typically request adjustments.
- *System limits* are fixed values that can't be changed.

Google Cloud uses quotas to help maintain fairness and reduce
spikes in resource use and availability. A quota restricts how much of a
Google Cloud resource your Google Cloud project can use. Quotas
apply to a range of resource types, including hardware, software, and network
components. For example, quotas can restrict the number of API calls to a
service, the number of load balancers used concurrently by your project, or the
number of projects that you can create. Quotas protect the community of
Google Cloud users by preventing the overloading of services. Quotas also
help you to manage your own Google Cloud resources.

The Cloud Quotas system does the following:

- Monitors your consumption of Google Cloud products and services
- Restricts your consumption of those resources
- Provides a way to [request changes to the quota value](https://docs.cloud.google.com/docs/quotas/help/request_increase) and [automate quota adjustments](https://docs.cloud.google.com/docs/quotas/quota-adjuster)

In most cases, when you attempt to consume more of a resource than its quota
allows, the system blocks access to the resource, and the task that
you're trying to perform fails.

Quotas generally apply at the Google Cloud project
level. Your use of a resource in one project doesn't affect
your available quota in another project. Within a Google Cloud project, quotas
are shared across all applications and IP addresses.


For more information, see the
[Cloud Quotas overview](https://docs.cloud.google.com/docs/quotas/overview).


There are also *system limits* on Distributed Cloud connected resources.
System limits can't be changed.

Your use of Google Distributed Cloud connected is governed by the following
types of quotas:

- **Rate quotas** determine how quickly you can call the
  Distributed Cloud Edge Container API as well as create and access
  Distributed Cloud connected resources.

- **Resource quotas** determine the total amount of
  Distributed Cloud resources that you can create within
  your Google Cloud project.

For more information about working with quotas, including steps for increasing
them and for setting up monitoring and alerting on quota metrics, see
the [Cloud Quotas documentation](https://docs.cloud.google.com/docs/quotas/overview).

## Rate quotas

The following table lists the rate quotas for
Distributed Cloud connected.

| Quota | Default limit | Description |
|---|---|---|
| **API requests** | 1200 per minute | All requests to the Distributed Cloud Edge Container API across all Google Cloud regions |
| **API requests** | 600 per minute | All requests to the Distributed Cloud Edge Container API for a specific Google Cloud region |

## Resource quotas

The following table lists the resource quotas for
Distributed Cloud connected.

| Quota | Default limit | Description |
|---|---|---|
| **Clusters** | 20 per Google Cloud project per Google Cloud region | Number of Distributed Cloud connected clusters per Google Cloud project in a Google Cloud region |
| **Networks** | 100 per Distributed Cloud connected zone | Number of Distributed Cloud networks per Distributed Cloud connected zone |
| **Subnetworks** | 138 per Distributed Cloud connected zone | Number of Distributed Cloud subnetworks configured per Distributed Cloud connected zone |
| **Routes** | 50,000 per Distributed Cloud network | Number of routes that can be advertised to a Distributed Cloud network |

## Virtual machine scaling limits

Scaling limits for virtual machines using VM Runtime on GDC are dictated
by the hardware configurations of your deployment, specifically the available
capacity on G1 or G2 hardware.

### Maximum VM scaling

The maximum number of concurrent VMs you can run depends on the CPU, memory, and storage
resources provided by your hardware configuration.

### Resource usage

To scale up VM deployments, ensure that the cluster has enough CPU, memory, and
storage resources for both VMs and control plane components of your
Distributed Cloud connected hardware deployment.