Install the CLI

bash -c "$(curl -sS"

You must have Docker installed to run Cortex locally or to create a cluster on AWS.

Deploy an example

# clone the Cortex repository
git clone -b 0.18
# navigate to the TensorFlow iris classification example
cd cortex/examples/tensorflow/iris-classifier
# deploy the model
cortex deploy
# view the status of the api
cortex get --watch
# stream logs from the api
cortex logs iris-classifier
# get the api's endpoint
cortex get iris-classifier
# classify a sample
curl -X POST -H "Content-Type: application/json" \
-d '{ "sepal_length": 5.2, "sepal_width": 3.6, "petal_length": 1.4, "petal_width": 0.3 }' \
<API endpoint>
# delete the api
cortex delete iris-classifier

Running at scale on AWS

Run the command below to create a cluster with basic configuration, or see cluster configuration to learn how you can customize your cluster with cluster.yaml.

See EC2 instances for an overview of several EC2 instance types. To use GPU nodes, you may need to subscribe to the EKS-optimized AMI with GPU Support and file an AWS support ticket to increase the limit for your desired instance type.

# create a Cortex cluster on your AWS account
cortex cluster up
# set the default CLI environment (optional)
cortex env default aws

You can now run the same commands shown above to deploy the iris classifier to AWS (if you didn't set the default CLI environment, add --env aws to the cortex commands).

Next steps

  • Try the tutorial to learn more about how to use Cortex.

  • Deploy one of our examples.

  • See our exporting docs for how to export your model to use in an API.

  • See uninstall if you'd like to spin down your cluster.