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

Google Kubernetes Engine is well suited for dynamic and large workloads since it can scale up with usage. It is easily configurable, which allows for flexibility. User interface is simple to navigate, which reduces roadblocks for a team with people unfamiliar with Kubernetes. Great if you are already using other GCP services as it integrates well with that.

Incentivized

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.

• Deployment of a new GKE cluster is really fast in comparison to other cloud providers.
• GCP is ahead other vendors and always provide the most up to date Kubernetes version.
• GKE automation for master upgrade and the worker nodes pool works really well.

Incentivized

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

• Not as intuitive as it could be
• Documentation could be better, especially for people using other Google Cloud tools
• Not the preferred Kubernetes Engine for many apps

Incentivized

• 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.

It's a great product if you learn it. It has flexibility and is very strong. Autoscaling and Resource management make running huge applications a breeze. Using Helm with Kubernetes and Terraform for infrastructure creation can totally automate your CICD pipeline. You also get easy access to CUDA cores for machine learning.

Incentivized

Google support is excellent and helpful, but the first answer is always so bureaucratic no matter how many logs, evidence, and information you sent.

Incentivized

We had to move several products to Google Cloud, and the Google Kubernetes Engine was the option recommended to us, so we investigated it and ran with it. Back then (2019), we were not aware of Cloud Run-provisioned K8s clusters, so our other option was a completely self-managed K8s cluster on Compute Engine VMs, which we did not have the knowledge of and capacity to handle.

Incentivized

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.

• Compared to other big K8s providers it has the best price/performance factors.
• Upgrade process from stable to regular versions
• Old stable releases: 1.15/1.16 should be in a stable branch.

Incentivized

• 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.