Docker vs. Google Cloud Functions

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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Any sort of transaction or complex logic that is going to take longer than 250ms or accesses resources that are protected by permissions, secrets, etc. is a great use case for a GCF. Some sort of "helper function" associated strictly with the UI inside browser would not be a good application of a GCF. It would not be crazy to create/debug some fairly complicated logic inside the browser/IDE and when perfected package it up as a Google Cloud Function. I have done that many times.

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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 oAuth
• integration with Firebase
• integration with React Frontend

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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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• Needing a zip file is problematic (when wanting to automate deployment for example).
• Requires another solution to execute automatically (ex. cloud scheduler).

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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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The console UI is pretty nasty. Managing various authentication/permissions configurations is just a nightmare. On the other hand, once you are over the hump it's not so bad. AWS Lambda is no better.

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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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Documentation is provided and clear for this service. Although GCP support is included in the current contract we didn't get to use it since the process is pretty straightforward.

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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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It is easier to keep everything in house when we are using GCP or AWS. To mix Lambda with google cloud is not a best practice and will cause problems ahead. The segmentation is clear, if you are using google, you use Google Cloud Functions. if you are on Amazon, you use all AWS tools. You can't mix them. The price is set.

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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.

• For training purposes, it is free
• Budgeting makes it cap the use
• monitoring makes it predictable

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