Amazon Elastic Kubernetes Service (EKS) vs. Rafay

It is well suited when you want to have a Kubernetes cluster in AWS Cloud and want to avoid all the management overhead of maintaining your own cluster in terms of the control plane. EKS seems to be lacking in features when compared with AKS and GKE. Backups, service mesh, and monitoring have a lot of room for improvements.

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Rafay is well suited for managing K8 deployments in on-prem deployments as well as AWS. Their support for GKE seems a bit limited.

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• Upgrade the kubernetes clusters to the latest version with a single click
• Auto scaling policies to automatically scale the nodes
• Detailed logs and events on the cluster within the EKS clusters portal, cloudwatch logs and metrics

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• AWSIAM integration with Kubernetes RBAC could be better.
• Enabling some add-ons like service mesh, and monitoring will be nice instead of having to install them yourself after the creation of the cluster.
• EKS bootstrap time could be faster ...

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• Seamless Single Sign-On Integration
• Use of a jumpstation to bootstrap a new EKS cluster deployment
• Some information in the UI does not auto populate
• UI can be enhanced a bit

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Cluster maintanence is reduced, easier to deploy resources, great observability insights

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So far our experience with using Rafay's platform has been very positive.

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I have dealt with a lot of support organizations and am really glad to say that Rafay goes above and beyond expectations when it comes to supporting our teams.

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It feels like AWS is behind the EKS race, the only advantage I'm able to see right now is the support of IPv6, however, trying to promote AWS alternatives that are different from the market and more like a vendor locking solutions like ECS/Fargate have kept AWS behind and focusing on the wrong things. EKS needs to really improve its integration with the Kubernetes ecosystem and have an enterprise solution for monitoring, backups, and service mesh.

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No, we are very satisfied with the contract terms and pricing model and hope it does not change in the future.

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• Good performance of platform without hiccups
• Less number of people required to manage cluster
• Easier to deploy new microservices

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