Google Kubernetes Engine vs. IBM Cloud Functions

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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IBM Cloud Functions [is] not the worse product on the IBM cloud. I decided to write this review as I thought it would be balanced. I would still use functions to set up a serverless architecture where execution time is pretty quick and the code is relatively simple. I wouldn't use IBM Cloud Functions for async calls obviously, as costs could be higher. The functions documentation is lacking in terms of CI/CD, and there are unexplainable errors occurring - like the network connection that I mentioned. So I wouldn't just rely on IBM Cloud Functions too much for the entire system, but make sure it's diversified.

• 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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• Great substitute for a simple API calls to run non-complicated code.
• Easy way to run Python/Java/Javascript to get something done.
• File validation.

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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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• Billing can be a hassle, not the most responsive customer service/support team
• Handles & executes most functionalities, but other platforms offer more scalability if you're seeking consistent and stable growth

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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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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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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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• ICF is a lightweight service and does not require runtime configurations
• Scalable on demand and hence there is no need to pay for runtime costs

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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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• 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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• It directly affected our expenses since we do not need to deploy and maintain a set of separate applications.
• It allowed us to pay for only the amount of time cloud functions run.
• It saved on maintenance and monitoring of the applications it replaced.

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