Amazon Elastic Kubernetes Service (EKS) vs. Google Cloud Run

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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Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

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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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• Auto scaling is the best one
• provide direct VPC connectivity and rigid network
• Cloud SQL and Pub/Sub services
• Handling latency issues

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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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• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

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We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

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

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The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.

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Not seen any major issues when we run applications its good

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Initially we felt slow but slowly it picked up and easy to manage

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I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

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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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AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.

Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.

Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.

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Not part of purchase.

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It has good auto scale feature and reliable also

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We have very good support when needed

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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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• Built in support for auto scaling helps reduce operational overhead
• Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
• Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

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