We already were having that microservices architecture, so there was not much change from that perspective. We had small services, so here we had to create multiple pod IDs. Even today, we are using a hybrid microservices architecture. Our DB still has two or three services that hit the same database. From that perspective, there was not much change that we did in our case.
Red Hat OpenShift Platform Plus
Red Hat | 4.18 20250122-0Linux/Unix, Red Hat Enterprise Linux 9.4 - 64-bit Amazon Machine Image (AMI)
External reviews
External reviews are not included in the AWS star rating for the product.
Simple way to provide effficency
RHOS critical for AI-RAN
OpenShift keeps getting better and better.
OpenShift User
Best Kubernetes for Enterprise
Most things work just right out of the box or is easy to integrate.
Easy to use Kubernetes
The platform of the future
Openshift is good, but too heavyweight
Adopting a flexible and efficient approach with noticeable improvements in operational costs and continued challenges in job management
What is our primary use case?
What is most valuable?
We have certain applications on-prem on physical servers. We had some on Windows and some on Linux. There we had requirements where every time we had to manage extra load, we had to spawn a new Tomcat node. Scaling was one of the issues we were facing, and every time we had to scale up, it was a challenge. Plus, we had to procure infrastructure and do a lot of configuration and setup for the new instance being launched.
Once we set that up, scaling down was a challenge as we did not always bring that down when not needed. When we did not have too much traffic, we still had a lot of infrastructure lying idle. At the same time, when we had high load, we were not able to scale up quickly.
There was too much patching that happened, and every time we had to patch something it became a challenge. There were versioning issues with operating systems versus Java and other technologies we were using. That is why we moved to containerization, where we defined what operating system we need, what Java version we need, and what steps we want to do. Containerization helped us create that one unit we wanted to deploy. Red Hat OpenShift helped us with managing scaling up and scaling down.
Because it was centrally managed in our company, many metrics that we had to write code for were available out of the box, including utilization, CPU utilization, memory, and similar metrics. We performed multiple transformations from physical servers to Red Hat OpenShift, and some from virtual servers to Red Hat OpenShift.
The OC utility tool is something we use very often for replication, replica sets, and config maps for managing all environments and secrets. This is very useful for us. Routing is another beneficial feature we get, so we do not need to manage or do too many things for load balancing.
What needs improvement?
Currently, one of the biggest challenges we face is with services and jobs. For spawning batches, although it has crons, it is not easy to integrate with enterprise systems such as Autosys. The entire company uses Autosys, but we are not able to integrate it effectively.
We need intermediate servers to run OC utility commands and initiate the cron job. We have to do a lot of modifications to ensure our batches work properly. With physical or virtual servers, even in AWS, we are able to write and manage multiple jobs. Managing batches in Red Hat OpenShift has been a significant challenge.
Integrating third parties is a challenge with Red Hat OpenShift. For example, with Elasticsearch, onboarding itself was difficult, running file beats and dealing with routing issues. It is not straightforward, especially since we have some components in AWS as. AWS has many capabilities that come out of the box and are easier to work with compared to Red Hat OpenShift.
Red Hat OpenShift's biggest disadvantage is they do not provide any private cloud setup where we can host on our site using their services. The main reason we went with Red Hat OpenShift was because it is a private cloud, and we have regulatory requirements that prevent us from using public cloud.
What was my experience with deployment of the solution?
The main reason we went with Red Hat OpenShift was because it is a private cloud, and we have regulatory requirements that prevent us from using public cloud. Red Hat OpenShift's biggest disadvantage is they do not provide any private cloud setup where we can host on our site using their services. For the use cases we dealt with, we have not seen much challenge with AWS. It has been better for us, but due to our requirement of being on private cloud for some applications, we are using Red Hat OpenShift.
What do I think about the stability of the solution?
We do not have any AI products at this time.
What do I think about the scalability of the solution?
We have certain applications on-prem on physical servers, some on Windows and some on Linux. We had requirements where every time we had to manage extra load, we had to spawn a new Tomcat node. Scaling was one of the issues we were facing, and every time we had to scale up, it was a challenge. We had to procure infrastructure and do extensive configuration and setup for new instance launches. Once set up, scaling down was also a challenge as we did not always reduce capacity when not needed. When we did not have much traffic, we still had substantial infrastructure sitting idle. Simultaneously, during high load periods, we were not able to scale up quickly.
How are customer service and support?
We have support available, but we never had to use it because we have our own internal teams who provide support. We have not encountered any issue where we had to reach out to Red Hat.
How would you rate customer service and support?
Neutral
How was the initial setup?
It is not difficult to onboard onto Red Hat OpenShift. Once you understand deployment configs, configs, replica sets, the basic components, routes and all, it is straightforward to onboard an application there. This applies mainly to services. Beyond that, it becomes challenging. We have not tried too many things because we struggled with batches. Getting things up and running in AWS, such as Kafka and Elasticsearch, is much easier than doing it on Red Hat OpenShift.
What was our ROI?
It is cost-effective. The only consideration is that you have to use it wisely. Use only what you need because it is not very difficult to add resources. It is always advisable to get the bare minimum that you need, and then add more when necessary. When you do not need the services, bring them down so you are not unnecessarily using compute resources. If you use it efficiently, then it is beneficial, which is applicable to any cloud platform.
What other advice do I have?
If you are dealing with services and need private cloud, go for Red Hat OpenShift. Regarding cost, if you compare to public cloud platforms, it is cheaper. If you are mostly on the services side and need private cloud, Red Hat OpenShift should be the solution. The overall rating is six out of ten, as it is not seen as a complete solution, but rather as a solution only for services. For other requirements such as integrations or batches, other cloud providers might be more suitable.