Dryad vs. K3s Lightweight Kubernetes

Dryad is well suited for situations where you are lacking data and or on the lookout for more interesting datasets to work with. It is also easy to read about how the authors collected the data and even provides a link to email them in case you need more information.

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K3s Lightweight Kubernetes is well suited for local development. K3s Lightweight Kubernetes is not well suited when you need backward support. In the case that you want to test an application that is still using deprecated APIs or CRDs which are supported on popular managed Cloud Kubernetes Distributions, because K3s Lightweight Kubernetes is trying to be a lightweight application and dropping early support for APIs/CRDs marked for deprication K3s Lightweight Kubernetes will not be a good solution. If you are trying to test Kubernetes etc, functionality, K3s Lightweight Kubernetes is not a good case since it's using Dqlite or SQLite.

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• Data curation
• Easy to use website
• Data in any format

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• Virtual clusters
• IoT devices
• Local development
• Raspberry Pi

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• More incentives for people to contribute data
• More promotion of the platform so people know about it
• Expand data categories

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• Option to deploy a self managed k3s in the cloud
• Support to deploy it with kubeadm
• Integration with prometheus & grafana

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

The website isn't as clean as that for Dryad and there seems to be less support for the end-user. However, it appears that they also have a large number of data repositories and have backing from many well-known universities. Ultimately, it comes down to personal preference and likability.

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We have mostly used kind, minikube, and Docker Desktop Kubernetes for local development. Only kind has lower resource requirements, but K3s Lightweight Kubernetes seems to be even lighter. It is a big benefit to be able to deploy a K3s Lightweight Kubernetes cluster in seconds locally in our workstation, there is no cost, and it makes it easy to redeploy from scratch no matter how many times we want. The removal of deprecated APIs or CRDs also makes it more secure since it reduces unnecessarily exposed attack vectors.

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• 35% time saved when it comes to cleaning
• Obviate the need for purchasing data
• Do not need to hire people to collect data

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• Engineers have been able to run more microservices locally with K3s Lightweight Kubernetes instead of Minikube, which is more resources hungry

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info