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README.md

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<br>
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Cortex deploys your machine learning models to your cloud infrastructure. You define your deployment with simple declarative configuration, Cortex containerizes your models, deploys them as scalable JSON APIs, and manages their lifecycle in production.
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Cortex deploys your machine learning models to your cloud infrastructure. You define your deployment with simple declarative configuration, Cortex containerizes your models, deploys them as autoscaling JSON APIs, and manages their lifecycle in production.
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Cortex is actively maintained by Cortex Labs. We're a venture-backed team of infrastructure engineers and [we're hiring](https://angel.co/cortex-labs-inc/jobs).
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- **Machine learning deployments as code:** Cortex deployments are defined using declarative configuration.
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- **Autoscaling:** Cortex can automatically scale APIs to handle production workloads.
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- **Multi framework support:** Cortex supports TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, and more.
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- **CPU / GPU support:** Cortex can run inference on CPU or GPU infrastructure.
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- **Scalability:** Cortex can scale APIs to handle production workloads.
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- **Rolling updates:** Cortex updates deployed APIs without any downtime.
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- **Cloud native:** Cortex can be deployed on any AWS account in minutes.

manager/info.sh

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@@ -26,8 +26,7 @@ function get_apis_endpoint() {
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kubectl -n=$CORTEX_NAMESPACE get service nginx-controller-apis -o json | tr -d '[:space:]' | sed 's/.*{\"hostname\":\"\(.*\)\".*/\1/'
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}
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echo
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER | grep -v "saved kubeconfig as" || true
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operator_endpoint=$(get_operator_endpoint)
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apis_endpoint=$(get_apis_endpoint)

manager/install_cortex.sh

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if ! aws s3api head-bucket --bucket $CORTEX_BUCKET --output json 2>/dev/null; then
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if aws s3 ls "s3://$CORTEX_BUCKET" --output json 2>&1 | grep -q 'NoSuchBucket'; then
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echo -e "\n✓ Creating an S3 bucket: $CORTEX_BUCKET"
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echo "✓ Creating an S3 bucket: $CORTEX_BUCKET"
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aws s3api create-bucket --bucket $CORTEX_BUCKET \
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--region $CORTEX_REGION \
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--create-bucket-configuration LocationConstraint=$CORTEX_REGION \
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>/dev/null
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else
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echo -e "\nA bucket named \"${CORTEX_BUCKET}\" already exists, but you do not have access to it"
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echo "A bucket named \"${CORTEX_BUCKET}\" already exists, but you do not have access to it"
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exit 1
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fi
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else
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echo -e "\n✓ Using an existing S3 bucket: $CORTEX_BUCKET"
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echo "✓ Using an existing S3 bucket: $CORTEX_BUCKET"
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fi
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}
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function setup_cloudwatch_logs() {
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if ! aws logs list-tags-log-group --log-group-name $CORTEX_LOG_GROUP --region $CORTEX_REGION --output json 2>&1 | grep -q "\"tags\":"; then
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echo -e "\n✓ Creating a CloudWatch log group: $CORTEX_LOG_GROUP"
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echo "✓ Creating a CloudWatch log group: $CORTEX_LOG_GROUP"
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aws logs create-log-group --log-group-name $CORTEX_LOG_GROUP --region $CORTEX_REGION
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else
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echo -e "\n✓ Using an existing CloudWatch log group: $CORTEX_LOG_GROUP"
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echo "✓ Using an existing CloudWatch log group: $CORTEX_LOG_GROUP"
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fi
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}
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break
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done
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echo -e "\n\n✓ Cortex is ready!"
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echo -e "\n✓ Cortex is ready!"
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if command -v cortex >/dev/null; then
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echo -e "\nPlease run \`cortex configure\` to make sure your CLI is configured correctly"
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fi
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}
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echo
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER | grep -v "saved kubeconfig as" || true
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echo -e "\nInstalling Cortex ..."
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manager/uninstall_cortex.sh

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set -e
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echo
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER | grep -v "saved kubeconfig as" || true
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echo -e "\nUninstalling Cortex ..."
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manager/uninstall_operator.sh

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# Note: if namespace is changed, the old namespace will not be deleted
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echo
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER
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eksctl utils write-kubeconfig --name=$CORTEX_CLUSTER | grep -v "saved kubeconfig as" || true
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echo -e "\nUninstalling the Cortex operator ..."
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