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Cost-effective serverless computing at scale

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Cost-effective serverless computing at scale

Cortex is a serverless platform for compute-intensive applications.

Use cases

  • Data processing - run image processing, natural language processing, and more.
  • Machine learning in production - train and serve machine learning models in production.
  • Large-scale inference - efficiently scale realtime and batch inference workloads.


  • Cluster autoscaling - configure Cortex to spin up instances when load increases and spin them down when load decreases.
  • Workload autoscaling - customize the autoscaling behavior of each workload to ensure efficient use of cluster resources.
$ cortex cluster info

region: us-east-1 instances: [c5.xlarge, g4dn.xlarge] spot_instances: true min_instances: 10 max_instances: 100


  • Any workload - define custom Python functions or containers and deploy them as realtime, async, and batch workloads.
  • Any pipeline - chain workloads seamlessly to create custom data pipelines.
$ cortex deploy apis.yaml

creating text-generator (realtime API) creating image-classifier (batch API) creating video-analyzer (async API)

all APIs are ready!


  • Structured logging - automatically stream logs from every workload to your favorite log management tool.
  • Metrics aggregation - monitor your workloads with pre-built Grafana dashboards and add your own custom dashboards.
$ cortex get

API TYPE REPLICAS text-generator realtime 32 image-classifier batch 64 video-analyzer async 16


  • Spot instance management - spend less on EC2 instances by letting Cortex manage spot instances.
  • Multi-instance type clusters - configure resources per workload to run each workload on the right hardware.
$ cortex cluster pricing

RESOURCE COST PER HOUR 1 eks cluster $0.10 2 network load balancers $0.02 each 10-100 g4dn.xlarge instances $0.53 each 10-100 c5.xlarge instances $0.17 each

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