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Is Amazon EKS Distribution Right For Your Enterprise? That Depends on What You’re Trying to Achieve

By Dustin Clarkson | Posted on January 21, 2021

As Kubernetes adoption continues to increase, the major cloud providers are investing heavily in providing customers with tools to easily manage containers on their platforms.

The latest entrant is Amazon EKS Distribution (or EKS-D), the company’s answer to Google Anthos and Azure Arc in the Kubernetes space. Here’s how Forbes described Amazon’s new tool:

Amazon has decided to jump the Kubernetes distribution bandwagon with Amazon EKS Distribution (EKS-D), which powers the managed EKS in the cloud. Customers can rely on the same versions of Kubernetes and its dependencies deployed by Amazon EKS, which includes the latest upstream updates and comprehensive security patching support

Amazon EKS-D comes with source code, open source tooling, binaries and container images, and the required configuration via GitHub and S3 storage locations. With EKS-D, Amazon promises extended support for Kubernetes versions after community support expires, providing updated builds of previous versions, including the latest security patches.

anthos-kubernetes-amazon-eks_illustration

While it’s definitely a smart move by Amazon to provide a tool that answers Google Anthos and Azure Arc, in our experience these offerings from the major cloud providers are just beginning to gain traction. 

Why is this the case? One reason is the fact that there are a limited number of enterprises that utilize both on premises and the cloud—or multi-clouds—at a level that warrants adopting specific tools like EKS-D. 

At least not yet.

Moving compute is easy, moving data is hard

When we’re talking about petabytes or terabytes of data, it can take hours—if not days—to move from one location to another. While it would certainly be of benefit to easily transport data for specific workloads, the math simply isn’t there yet.building-data-cloud_square-illustration

Because of this, the vast majority of enterprise data remains where it’s initially stored. A company that is already heavily invested in Amazon Web Services (AWS), for example, is unlikely to build out an on-premises datacenter just for flexibility in where workloads are conducted. Instead, it will utilize tools that best work where the data already lives.

cloud-data-analytics-app-ai-ml_square-illustrationPut another way, your choice of tools should always be based on where your data lives, not where it could live. 

None of this is to say tools like EKS-D, Anthos, or Azure Arc are unnecessary, just that they are tailored for very specific—and up until now, rare—cases that most enterprises don’t need to address. 

As always, look before you leap

New tools are always appealing on the surface, but once you dig deeper into what it takes to adopt and implement a tool, you usually reveal unexpected levels of cost and complexity. 

As with any technology, enterprises curious about Amazon EKS-D (or Google Anthos, or Azure Arc) should start with a simple question: What are we trying to achieve? Once you answer that question, it’s much easier to find the right tool.

For more information on Kubernetes, cloud adoption, and managing your enterprise data, contact one of our experts