Google Cloud Functions vs. Google Kubernetes Engine

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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If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.

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

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• Engine upgrade rollout strategy - well documented and configurable
• Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
• Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)

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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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• Support of IPv6.
• Better GitOps.
• A "serverless" Kubernetes so we can install Google config connector will be really awesome.
• Container-native load balancers do not support internal TCP/UDP load balancers or network load balancers.

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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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• Google Kubernetes Engine has a good UI and documentation that facilitates setup and helps get projects moving along quickly
• Its built-in logging integrations with StackDriver make it easier to monitor the application and log issues quickly
• Automated orchestration, deployment, and scaling of nodes and networking are all easily configurable with yaml files

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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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Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.

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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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GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.

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• When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.

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

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• Reduced cloud computing costs.
• Easier management of applications.
• Extra time investment to learn how to setup applications in Google versus Amazon.

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