OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
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Watson IoT Platform
Score 8.5 out of 10
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The IBM Watson IoT Platform is an Internet-of-things is a managed cloud-hosted solution supporting device connectivity, control, visualization, and overall device visibility and management. It provides a UI where users can add and manage devices, control access to IoT service, and monitor usage. With its device management service, users can perform device actions like rebooting or updating firmware, receive device diagnostics and metadata, or perform bulk device addition and removal.
Nothing like OpenShift. Actually, this was our first one. We toyed with maybe doing raw Kubernetes, but with an enterprise company you need an enterprise product.
Comparing the 2, open source Kubernetes is quicker to setup by about 75%, less restrictive, and free of course, but it lacks the security and support of Red Hat, and deploying features is much harder compared to with operators. For buisiness purposes, OpenShift is just more …
Even though Red Hat OpenShift has more overhead than many other Kubernetes flavors, we have selected Red Hat OpenShift because of it's focus on Security and because of it's excellent vendor support.
Red Hat OpenShift has a better security posture than EKS. I enjoy the console on Red Hat OpenShift more as well. I believe there is greater observability for Red Hat OpenShift.
The Tanzu Platform seemed overly complicated, and the frequent changes to the portfolio as well as the messaging made us uneasy. We also decided it would not be wise to tie our application platform to a specific infrastructure provider, as Tanzu cannot be deployed on anything …
AWS offers an "IoT" product that similarly connects devices securely to centralize data exchange, predict downtime, and overall increase the efficiency of an IoT infrastructure. Like some of the other AWS products, the documentation is lacking and UI is quite hard to use, which …
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.
As long as we have a clear understanding of the "real" pain points-- and that involves gathering both structured and unstructured data-drawing conclusions-- Watson IoT has a role to play. The area I am most keen on that a move the Watson can help achieve would be to go from preventative maintenance, to predictive maintenance, to eventually prescriptive maintenance.
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.
The asset information is available in both static and dynamic format (from thermal images, to OEM data, to time series data). The ability to ingest all the information using a single platform has great value.
Another benefit is a seamless integration with Maximo. This has been a challenge with other 3rd party systems available.
The experience of IBM Maximo systems updates is positive.
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."
Some of the tutorials could use a little more improvement - While there is a considerable amount of documentation, most of the good documentation for Watson IoT we found to be from third-parties.
Administration and billing tools could use a bit more improvement - The UI is a bit clunky and poorly-designed here.
Be prepared to work with IBM support to get this going - Their turn-around support for inquiries can be lengthy, and setup time may also be quite lengthy because of this.
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
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
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.
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.
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
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.
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.
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.
AWS offers an "IoT" product that similarly connects devices securely to centralize data exchange, predict downtime, and overall increase the efficiency of an IoT infrastructure. Like some of the other AWS products, the documentation is lacking and UI is quite hard to use, which is why we chose to use IBM Watson instead.
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
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.
Positive - This tool greatly increases most company's manufacturing and production efficiency, and the use-cases are extensive. It was a great way of decreasing down-time for us.
Negative - Took lots of work and energy to get up and running, we had to rely on IBM support and tutorials many times during this process.
Positive - Quite cheap, most of the tiers of pricing cost very little, and it's possible to use Watson IoT for a few months for free to see if it is beneficial for your company.
