Mirantis Kubernetes Engine vs. Red Hat OpenShift

Docker is great for when you would want to use a VM for any given application, but don't need the overhead of the whole OS. Docker containers use very little computing resources, boot up very quickly, and are very easy to set up. An instance where Docker may not be appropriate would be for an application that requires good security. If in this situation, a true VM would probably be your best bet.

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

• Containerization - allowing multiple micro-services to function together without in-depth orchestration at the VM level.
• Rapid deployment - a developer with appropriate access can simply push to the correct remote and the deploy happens automatically from there
• Decouples provisioning from VM administration - allows containers to be deployed (more) regardless of VM set up.

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

• Docker has a bit of a learning curve, and it takes some time to become familiar with the tooling and syntax. Transitioning an existing architecture to docker can represent a significant investment.
• Docker attempts to provide some level of cross-host container orchestration via swarm, but it falls short of third-party solutions like kubernetes.
• We occasionally run into stability issues when the docker daemon is subjected to high load (many applications starting/stopping frequently). In these cases, docker hangs and we have to restart or replace the node.

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."

Incentivized

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

Docker's CLI has a lot of options, and they aren't all intuitive. And there are so many tools in the space (Docker Compose, Docker Swarm, etc) that have their own configuration as well. So while there is a lot to learn, most concepts transfer easily and can be learned once and applied across everything.

Incentivized

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

Incentivized

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.

Incentivized

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 community support for Docker is fantastic. There is almost always an answer for any issue I might encounter day-to-day, either on Stack Overflow, a helpful blog post, or the community Slack workspace. I've never come across a problem that I was unable to solve via some searching around in the community.

Incentivized

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

Incentivized

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

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.

Incentivized

The learning curve is quite high but worth it.

Incentivized

I have not used any other software as a container management solution. Its containerized apps allow the usage of less memory, thus
they start and shut down very fast. This tool is helping the enterprise
software to work quickly against the changing conditions thus offers great
scaling by simultaneously allowing me to meet the demands, which also leads to
easy implementation of the strategies.

Incentivized

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.

Incentivized

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

• We are able to try things very quickly compared to before. If you need to debug it, changes on X/Y/Z will have an impact on the way your app works, and changing libraries or configurations of the environment easily can improve your development cycles.
• In case someone new arrives, the onboarding is pretty easy thanks to Docker. We have tried many configs and images until we reached a point were we have what we want. We don't have to painfully do that again for every new user. We just send him the image.

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