IBM Cloud Kubernetes Service vs. Red Hat OpenShift

IBM Cloud Kubernetes Service is ideal for deploying modern applications on a microservices architecture -- where easy scaling and ability to update are important. IBM Cloud Kubernetes Service also handles automated deployments and load balancing very well, particularly if you're already working in the IBM Cloud ecosystem. There are applications less suited to IBM Cloud Kubernetes Service -- such as very small applications, where managing an IBM Cloud Kubernetes Service cluster would be overkill. Also, users not familiar with container organization might find IBM Cloud Kubernetes Service to be a challenge to manage effectively.

Incentivized

Red Hat OpenShift, despite its complexity and overhead, remains the most complete and enterprise-ready Kubernetes platform available. It excels in research projects like ours, where we need robust CI/CD, GPU scheduling, and tight integration with tools like Jupyter, OpenDataHub, and Quiskit. Its security, scalability, and operator ecosystem make it ideal for experimental and production-grade AI workloads. However, for simpler general hosting tasks—such as serving static websites or lightweight backend services—we find traditional VMs, Docker, or LXD more practical and resource-efficient. Red Hat OpenShift shines in complex, container-native workflows, but can be overkill for basic infrastructure needs.

Incentivized

• IBM has a strong focus on serverless and Kubernetes. This shows in the platform. Deploying containers to Kubernetes was very easy.
• Deploying a Kubernetes cluster through the GUI is very easy and quick. On top of that, IBM Cloud offers a single node cluster for Free.
• Container Registry is a very good product for managing container images. Integration with Kubernetes was seemless.
• Portability. To transition from Google Cloud Kubernetes to IBM Cloud Kubernetes took almost no effort. We mostly use the CLI and the standard tools such as kubectl were present.

Incentivized

• One thing is the way how it works with the GitHubs model on an enterprise business, how the hub and spoke topology works. Hub cluster topology works the way how there is a governance model to enforce policies. The R back models, the Red Hat OpenShift virtualization that supports the cube board and developer workspace is one big feature within. So yes, these are all some features I would call out.

Incentivized

• I constantly get this error even when everything is well configured prefect.exceptions.AuthorizationError: [{'path': ['auth_info'], 'message': 'AuthenticationError: Forbidden', 'extensions': {'code': 'UNAUTHENTICATED'}}]
• Then sometimes the error disapear without changine anything, happened twice to me. Should there be an issue with the authentication service? Please let's improve or let users know why this may be happening.
• Improve the UX in the browse console when removing many images at once
• UX on the process of installing KeyCloack operator

Incentivized

• So I don't know that this is a specific disadvantage for Red Hat OpenShift. It's a challenge for anything that Kubernetes face is. There's an extremely large learning curve associated with it and once you get to the point where you're comfortable with it, it's really not bad. But beating that learning curve is a challenge. I've done a couple presentations on our implementation of Red Hat OpenShift at various conferences and one of the slides I always have in there is a tweet from years ago that said, "I tried to teach somebody Kubernetes once. Now neither of us knows what it is."

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We have our application running on a CentOS compartment on IBM Cloud Kubernetes Service. We have been utilizing the help since IBM Cloud initially dispatched. We liked the adaptability and versatility that IBM Cloud Kubernetes Service give us. Since we are tiny, the Kubernetes administration is just utilized at present inside my venture bunch.

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This is the current strategy for the company, most of the products in the organisation are aligning to Openshift and various use cases it support. Also lot of applications are being developed for AI use case, openshift.AI provides opportunity to host and leverage the AI capabilities for these applications

Incentivized

We actually haven't had any real problems in our clusters recently and the results we have gotten from adopting IBM Cloud Kubernetes Service have been beyond even our greatest expectations. The community has helped optimize the use of the system and make it relatively simpler to use.

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The virtualization part takes some getting used to it you are coming from a more traditional hypervisor. Customization options are not intuitive to these users. The process should be more clear. Perhaps a guide to Openshift Virtualization for users of RHV, VMware, etc. would ease this transition into the new platform

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IBM's cloud is almost infallible.

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Redhat openshift is generally reliable and available platform, it ensures high availability for most the situations. in fact the product where we put openshift in a box, we ensure that the availability is also happening at node and network level and also at storage level, so some of the factors that are outside of Openshift realm are also working in HA manner.

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IBM's cloud has a site in my conuntry (MEXICO) so the network latency was almost 0

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Overall, this platform is beneficial. The only downsides we have encountered have been with pods that occasionally hang. This results in resources being dedicated to dead or zombie pods. Over time, these wasted resources occasionally cause us issues, and we have had difficulty monitoring these pods. However, this issue does not overshadow the benefits we get from Openshift.

Incentivized

The self-guided support was solid, and there are plenty of online videos to guide first time users, but I think one area of improvement is a faster way to transfer a large quantity of files from our local machine to the cloud for storage (Aspera)

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Every time we need to get support all the Red Hat team move forward looking to solve the problem. Sometimes this was not easy and requires the scalation to product team, and we always get a response. Most of the minor issues were solved with the information from access.redhat.com

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I was not involved in the in person training, so i
can not answer this question, but the team in my org worked directly
with Openshift and able to get the in person training done easily, i did not
hear problem or complain in this space, so i hope things happen
seamlessly without any issue.

Incentivized

Online training is really an important resource for using these tools. IBM's help center is rich in useful information and tips. Also, external guides and tutorials are available (e.g. on youtube), but I followed only IBM ones and I had no difficulties.

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We went thru the training material on RH webesite, i think its very descriptive and the handson lab sesssions are very useful. It would be good to create more short duration videos covering one single aspect of openshift, this wll keep the interest and also it breaks down the complexity to reasonable chunks.

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Ease of use. Very intuitive. We have been looking for a product that allows us to orchestrate our docker containers in a way where it allows us to effectively scale our applications to production. It also provides us a way of monitoring all our infrastructure in a very clear concise way.

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The learning curve is quite high but worth it.

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I have earlier used various services, such as Kubernetes and Google Cloud Run. Still, IBM Cloud Kubernetes Service offers more convenience and a larger set of functions and features are available in Kubernetes. Google Cloud Run is much closer to a server less approach to deployment, although it gives slightly less flexibility in terms of configuration than IBM Cloud Kubernetes Service.

We utilized the Thycotic Secret Service to manage all our application secrets, resulting in seamless integration with our applications. We developed all the applications using Red Hat Fuse (currently migrated to Quarkus). We used the built-in Kali Linux support of OpenShift to manage and configure the services and API. Additionally, the Red Hat Developer Studio facilitates faster development.

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IBM's CKS does not offers automatic autoscaling nor vertical scaling (automatic). Other services like Google Kubernetes Engine scales up and down very well

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This is a great platform to deployment container applications designed for multiple use cases. Its reasonably scalable platform, that can host multiple instances of applications, which can seamlessly handle the node and pod failure, if they are configured properly. There should be some scalability best practices guide would be very useful

Incentivized

• IKS can provide around 30% savings when it comes to operational costs since Kubernetes is designed to run applications in most machines in the most efficient manner possible.
• Managed Kubernetes can save a company time by 45% since Managed Kubernetes usually is seamlessly updated, without any interruptions with the workload. IKS fall into this benefit.
• We heard people had saved in maintenance downtimes when it comes to Kubernetes by a factor of 10 so IKS can contribute to more flexible and distributed services with virtually no downtime.

Incentivized

• It has allowed us to see where we need to be in the container world. I'm going to call it a net neutral impact, not negative or positive. It has given us a sense of what we are ready for and what we're not ready for. You know where you stand.
• You don't know what you don't know, so it helps us know what we want to know.

Incentivized