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Copy file name to clipboardExpand all lines: docs/clusters/aws/install.md
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## Prerequisites
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1.[Docker](https://docs.docker.com/install)
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1.[Docker](https://docs.docker.com/install) must be installed and running on your machine (to verify, check that running `docker ps` does not return an error)
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1. Subscribe to the [EKS-optimized AMI with GPU Support](https://aws.amazon.com/marketplace/pp/B07GRHFXGM) (for GPU clusters)
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1. An IAM user with `AdministratorAccess` and programmatic access (see [security](security.md) if you'd like to use less privileged credentials after spinning up your cluster)
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1. You may need to [request a limit increase](https://console.aws.amazon.com/servicequotas/home?#!/services/ec2/quotas) for your desired instance type
Copy file name to clipboardExpand all lines: docs/clusters/gcp/install.md
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# Install
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## Spin up Cortex on your GCP account
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## Prerequisites
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Make sure [Docker](https://docs.docker.com/install) is running on your machine.
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1.[Docker](https://docs.docker.com/install) must be installed and running on your machine (to verify, check that running `docker ps` does not return an error)
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1. You may need to [request a quota increase](https://cloud.google.com/compute/quotas) for your desired instance type and/or GPU type
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1. Export the `GOOGLE_APPLICATION_CREDENTIALS` environment variable, containing the path to your GCP credentials file (e.g. `export GOOGLE_APPLICATION_CREDENTIALS=~/.config/gcloud/myproject-8a41417a968a.json`)
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1. If you haven't done so already, enable the Kubernetes Engine API in your GCP project ([here](https://console.developers.google.com/apis/api/container.googleapis.com/overview))
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If you're using GPUs, make sure your GPU quota is sufficient (see [here](https://cloud.google.com/compute/quotas)).
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