Docker vs. Google Cloud IoT

You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.

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I consider myself very techy and found Google Cloud IoT platform very challenging to manage. The lack of tutorials and discussions to understand how each section works is very challenging. I specifically made a connection after several hours to Google Nest to third-party integration, Home Assistant. Shortly after Google Cloud upgraded to a new version breaking the connection. This was extremely frustrating. No service should take several hours to figure out, in my opinion, if it does, the platform is doing a poor job of making it easy. I'm personally very discouraged any time I ever have to use this platform. It's very hard to find answers.

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• Packaging of application to limit the space occupied
• Ease of running the application
• Provide multiple ways to handle the application issues and integration of different components like pipeline, ansible, terraform etc

• Integration with different brands of microcontrollers including the one currently used by Espresiff.
• The platform is very robust and secure.

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• Docker hub image retention policy can be relaxed
• Docker hub policies can be more developer friendly
• Docker CLI help section can be improved
• Image and container storage (local) management can be optimized

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• Not beginner friendly.
• Needs more tutorials and walk throughs on how to get started.
• Very complicated and unless you know what you are doing you will be lost.
• Lack of material found on how to do each section / services.

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I have been using Docker for more than 3 years and it really simplifies the modern application development and deployment. I like the ability of Docker to improve efficiency, portability and scalability for developers and operations teams. Another reason for giving this rating is because Docker integrates CI/CD pipelines very well

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Haven't seen any outages, fatal/unrecoverable errors in my usage so far. Enough said.

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Docker Desktop. The CPU high usage is a known issue. Needs fixing. Otherwise, it is great overall. Would not use anything else still.

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The reason why we are still using Docker right now is due to that is the best among its peers and suits our needs the best. However, the trend we foresee for the future might indicate Amazon lambda could potentially fit our needs to code enviornmentless in the near future.

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Although comparisons are hateful, even more so when we are talking about leading brands where the quality of their services are indisputable, the general environment of Google was more familiar to me since I use, for example, Google Firebase on a daily basis, where part of the concepts are similar, without Without a doubt, AWS services are excellent, but it was easier for me to go through the functions of Google Cloud IoT.

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It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.

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• Reduces the number of virtual machine which impacted our quarterly billing
• Using docker with proxy we run multiple application on same port on same host.
• impact on billing is we have to provide docker training to the people who are working on it.

• The amount of hours to get things integrated is negative.
• The amount of hours researching how to get devices integrated is negative.
• Overall the amount of time and effort getting things working has been a negative experience.

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