Google Kubernetes Engine vs. Red Hat Advanced Cluster Management for Kubernetes

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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Well suited for - Large-scale Edge deployments of OpenShift instances. Policy-based consistency for all workloads is Less appropriate for - Small-scale deployments. Stand-alone deployments of K8s clusters. Deployments in the same data center.

• 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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• Continuous deployment of other OpenShift instances.
• Controls clusters and applications from a single console.
• Built-in Security & compliance.

• 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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• Initial deployment of the ACM itself needs to be made easy.
• Dependency on the Software versions of underlying open shift workloads during upgrades.
• LCM of ACM itself.

• 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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I have also used TNA by Google Cloud, but that is not mature enough as ACM. Right now, ACM is the best choice as a cluster manager for private cloud data centers.

• 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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• Reduced the deployment duration of individual nodes by 50%.
• Acts as a central manager for all the clusters.
• Provides a lot of infrastructure options (storage, networking, etc) to build instances of your choice.