Red Hat OpenShift Reviews and Ratings

Use Cases and Deployment Scope

As I assume for most companies using Red Hat OpenShift, we use the platform as an efficient and automating tool to manage and deploy our containerized applications across several environments. We often use Red Hat OpenShift for our Docker containers to package applications and their dependencies and monitoring their status to help us determine if any issues arise or develop from new code changes.

Likelihood to Recommend

When working with containers on our system, there is multiple team members that may be changing, developing, and/or deploying containers around the same time of day. Using Red Hat OpenShift allows us to work seamlessly together. However, when it comes for simple changes/testing, I feel it is often quicker for me to work manually within the containers to then just make developments and then redeploy.

Use Cases and Deployment Scope

So, in my organization, we use Red Hat OpenShift as a devops container to host our applications. So every time we push a new version into our git azure, the pipeline is automatically triggered to build the new image and deploy our application. The big advantage we got from using Red Hat OpenShift is that when we used traditional virtual machines to deploy our applications, we didn't know when the service stopped and every time the VM stopped, we had to restart the application (which is essentially a .jar file) again, it didn't restart automatically. In addition, the application artifact is created manually using maven commands. Fortunately, all this was solved using Red Hat OpenShift, because in Red Hat OpenShift we just push the code to git and the magic happens automatically.

Likelihood to Recommend

Red Hat OpenShift FITS THE BILL:As a financial institution, our applications must always be up and running, because money is the most important thing to some people, and they can't forgive any delays. Red Hat OpenShift therefore gives us the ability to check the status of our applications and, most importantly, in the event of a problem, Red Hat OpenShift restarts the application automatically.Red Hat OpenShift IS LESS APPROPRIATE: when you have a small integration system, I don't think Red Hat OpenShift is the most appropriate choice, given its price and size. It's like driving a mazzarati in a crowded small town.

Use Cases and Deployment Scope

It takes a lot of the headache out of deploying and scaling, and helps keep dev and prod in sync ,s ince it’s built on Kubernetes, we get all the power and flexibility of K8s, but with a much nicer experience for the teams — especially when it comes to automation, monitoring, and managing clusters

Likelihood to Recommend

works really well for large-scale container workloads and AI/ML use cases it’s solid, flexible, and production-ready. Virtualization is improving, but still needs work; recent updates look promising. For small, simple apps, it might be more than you need.

Use Cases and Deployment Scope

We had a business requirement to integrate multiple systems, where we had developed a large number of APIs and microservices. To manage and deploy this large number of APIs and services, we used Red Hat OpenShift as a cloud platform to host and expose our endpoints to consumers who want to use the integration flow. OpenShift provides a significant edge in managing a large number of applications, offering features such as scaling, automated deployment, integration with monitoring tools, and resource quota usage statistics.

Likelihood to Recommend

If you have a large number of APIs within your application scope, OpenShift is the platform you should use to manage all the apps with ease.

Use Cases and Deployment Scope

Open Shift is used as part of the AI-RAN POC CaaS to evaluate the 5G functionalities and RAN capability. Orchestrating CPU and GPU resources can be a challenging problem, but the Red Hat team is willing to support and learn with us as we progress. The team has ample resources and learning materials to get us started. We appreciate the Red Hat team and their support of our multiple RAN projects.

Likelihood to Recommend

Red Hat's OpenShift is easy to use and offers extensive support.

Use Cases and Deployment Scope

We use Red Hat OpenShift as a flexible MLOps platform through OpenDataHub, enabling streamlined model training, tracking, and deployment workflows. It serves as the backbone for our AI Inference Server, allowing us to scale and manage containerized inference endpoints efficiently. Additionally, Red Hat OpenShift hosts our IBM Qiskit development environment via JupyterHub, supporting quantum computing research and prototyping. This setup addresses challenges in deploying reproducible ML pipelines, managing compute resources, and integrating emerging technologies like quantum computing. The scope includes AI/ML development, automated deployment, and hybrid cloud scalability across our research and enterprise infrastructure.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

Primarily right now we're doing with VMs. We were a Rev customer and migrated our Rev VM workloads to OpenShift virtualization. We also have our eye on the future with container environment, so it fits perfectly into what we were doing now and what we look to do in the future.

Likelihood to Recommend

Well suited if you are looking to do containers, if you're looking for an easy way to build a container platform, there's so much in it to easily do that. Right now it's not as great as handling VMs with my aforementioned comments about how it can improve. So I would say it's low point right now it's the VMs, but it looks like they're improving. But the high point is always containerization.

Use Cases and Deployment Scope

It is one of the finest platform as a service platform. we are using this for build & deploy our application for cloud because it makes our application more secure and scalable. It has very low downtime. Customer support is fabulous. It ensure security compliance. Red Hat OpenShift has lots of inbuilt features and service that enhance productivity and scalability. It provide flexibility and more control on our application for better handling.

Likelihood to Recommend

It is well for us to migrating our old application on the cloud for better security and speed. Creating clusters for reducing load and enhancing experience of the application.

Use Cases and Deployment Scope

Spend less and have common platform for containers and VM

Likelihood to Recommend

Use Cases and Deployment Scope

We use OpenShift within multiple departments, but in mine specifically (integrated platform engineering) we use it for running pods related to hosting web apps for publication resources, running builds, and creating ephemeral testing environments for kits. We have 2 clusters not currently in production, and are working towards that this year.

Likelihood to Recommend

OpenShift is great for our business cases, where things like security and sign ons are a major concern. We've also automated a bit of the setup ourselves to make it easier. Without the prior experience i have, however, install would be infeasible without dedicated support from RH. I would not recommend for personal / community use