Google Kubernetes Engine vs. IBM Cloud Code Engine

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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It would be a good solution for running serverless applications. Because infrastructure setup and maintenance expenses can be avoided, the investment will pay for itself. The time to value is short, allowing IT to respond to business demands quickly. It aided us in customizing security as well as operating a personal project using to autoscale up and down approach. Also, because there isn't much hassle, items can be pushed into production as soon as possible. Simply push a container, create an application, and you're ready to go. But, It is less suited when you have a static machine or need to keep data in some way and do not want to utilize network storage or a database.

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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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• Managed Environment for partners and customers - shifting skills and speed to CSP
• A variety of programming model support
• Elastic scalability for cloud native development and speed
• Flexible consumption model
• Containerized workloads with horizontal scalability
• Here is an example - live demo walk-thru delivered to partners and community:
• https://www.youtube.com/watch?v=MCBClYgpDFg

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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 pricing structure is complicated, and the servers are expensive. I really think they should offer better pricing options and support for more languages
• sometimes the servers go down, and they take too long to respond to support tickets
• uploading documents is slow since I have to do it one by one, making the process much longer than it should be

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Invited by TrustRadius (TR) on Vendor's Behalf

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Since this capability supports a wide variety of use cases - all on non proprietary and open technology based frameworks

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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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Consumers can purchase individual components as well as unlocking new bundles with special features and services including the extensive data management governance capabilities of the Automation range. Kubernetes containerizing for effective service implementation and an agile, flexible multi-cloud data program help both utilization expansion and deployment to be improved by this architecture.

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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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Independently Invited by TrustRadius

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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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What impresses me most about IBM Cloud Code Engine is the container workload management capability and the Cloud services and dataflow monitoring functionalities. Data security and network security control via IBM Cloud Code Engine is quite excellent and very responsive data integration functions and the first deployment is not very technical.

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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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Independently Invited by TrustRadius

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• [One] positive is that we have one tool to learn (and a simple one) for all kinds of deployment. We need less people to maintain the system.
• We have saved a lot of time on trouble shooting. It's clear how it works. It's "just" kubernetes..

Incentivized

Invited by the Vendor

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info