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<br> <img src='https://cortex-public.s3.us-west-2.amazonaws.com/logo.png' height='32'> <br>

Note: This project is no longer actively maintained by its original authors.

Production infrastructure for machine learning at scale

Deploy, manage, and scale machine learning models in production.

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Serverless workloads

Realtime - respond to requests in real-time and autoscale based on in-flight request volumes.

Async - process requests asynchronously and autoscale based on request queue length.

Batch - run distributed and fault-tolerant batch processing jobs on-demand.

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Automated cluster management

Autoscaling - elastically scale clusters with CPU and GPU instances.

Spot instances - run workloads on spot instances with automated on-demand backups.

Environments - create multiple clusters with different configurations.

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CI/CD and observability integrations

Provisioning - provision clusters with declarative configuration or a Terraform provider.

Metrics - send metrics to any monitoring tool or use pre-built Grafana dashboards.

Logs - stream logs to any log management tool or use the pre-built CloudWatch integration.

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Built for AWS

EKS - Cortex runs on top of EKS to scale workloads reliably and cost-effectively.

VPC - deploy clusters into a VPC on your AWS account to keep your data private.

IAM - integrate with IAM for authentication and authorization workflows.