K3s Lightweight Kubernetes vs. Watson IoT Platform

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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For large companies with large-scale manufacturing, electronics management, and infrastructures that require lots of maintenance, IBM Watson IoT is a must-have. It greatly increases performance, decreases downtime, and is an all-around great management dashboard. This is best for infrastructures that have a larger infrastructures of IoT devices in an enterprise/manufacturing setting, otherwise IBM Watson may not bring many benefits to your team.

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

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• The asset information is available in both static and dynamic format (from thermal images, to OEM data, to time series data). The ability to ingest all the information using a single platform has great value.
• Another benefit is a seamless integration with Maximo. This has been a challenge with other 3rd party systems available.
• The experience of IBM Maximo systems updates is positive.

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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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• Some of the tutorials could use a little more improvement - While there is a considerable amount of documentation, most of the good documentation for Watson IoT we found to be from third-parties.
• Administration and billing tools could use a bit more improvement - The UI is a bit clunky and poorly-designed here.
• Be prepared to work with IBM support to get this going - Their turn-around support for inquiries can be lengthy, and setup time may also be quite lengthy because of this.

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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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Predix has recently launched their Asset Performance management Unified system. I am keen to see how it stacks up against Watson.

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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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• Positive - This tool greatly increases most company's manufacturing and production efficiency, and the use-cases are extensive. It was a great way of decreasing down-time for us.
• Negative - Took lots of work and energy to get up and running, we had to rely on IBM support and tutorials many times during this process.
• Positive - Quite cheap, most of the tiers of pricing cost very little, and it's possible to use Watson IoT for a few months for free to see if it is beneficial for your company.

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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