Google Cloud Functions vs. Google Cloud Run

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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Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

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• integration with oAuth
• integration with Firebase
• integration with React Frontend

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• Auto scaling is the best one
• provide direct VPC connectivity and rigid network
• Cloud SQL and Pub/Sub services
• Handling latency issues

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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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• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

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We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

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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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The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.

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Not seen any major issues when we run applications its good

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Initially we felt slow but slowly it picked up and easy to manage

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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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I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

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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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AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.

Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.

Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.

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Not part of purchase.

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It has good auto scale feature and reliable also

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We have very good support when needed

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

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• Built in support for auto scaling helps reduce operational overhead
• Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
• Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

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