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title = "Kubeflow on AWS Features"
weight = 200
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## Reasons to use Kubeflow on Amazon Web Services (AWS)

Running Kubeflow on Amazon EKS brings the following optional and configurable features:

* You can manage your Amazon EKS cluster provisioning with **[eksctl](https://github.com/weaveworks/eksctl)** and easily choose between multiple compute and GPU worker node configurations.
* You can manage ingress traffic with the **[AWS ALB Ingress Controller](https://github.com/kubernetes-sigs/aws-alb-ingress-controller)**.
* You can leverage the **[Amazon FSx CSI driver](https://github.com/kubernetes-sigs/aws-fsx-csi-driver)** to manage Lustre file systems which are optimized for compute-intensive workloads, such as high-performance computing and machine learning. Amazon FSx can scale to hundreds of GBps of throughput and millions of IOPS.
* Centralized and unified Kubernetes cluster logs in **[Amazon CloudWatch](https://aws.amazon.com/cloudwatch/)**, which helps with debugging and troubleshooting.
* You can enable TLS and Authentication with **[AWS Certificate Manager](https://aws.amazon.com/certificate-manager/)** and **[AWS Cognito](https://aws.amazon.com/cognito/)**.
* You can enable **[Private Access](https://docs.aws.amazon.com/eks/latest/userguide/cluster-endpoint.html)** for your Kubernetes cluster's API server endpoint.
* Your Kubeflow on AWS deployment automatically detects GPU worker nodes and installs the **[NVIDIA Device Plugin](https://github.com/NVIDIA/k8s-device-plugin)**.
