Terraform from HashiCorp is a cloud infrastructure automation tool that enables users to create, change, and improve production infrastructure, and it allows infrastructure to be expressed as code. It codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. It is available Open Source, and via Cloud and Self-Hosted editions.
$0
Red Hat OpenShift
Score 9.3 out of 10
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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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Pricing
HashiCorp Terraform
Red Hat OpenShift
Editions & Modules
Open Source
$0
Team & Governance
$20/user
per user/per month
Enterprise
Contact sales team
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Offerings
Pricing Offerings
HashiCorp Terraform
Red Hat OpenShift
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
HashiCorp Terraform
Red Hat OpenShift
Features
HashiCorp Terraform
Red Hat OpenShift
Configuration Management
Comparison of Configuration Management features of Product A and Product B
HashiCorp Terraform
7.9
Ratings
2% below category average
Red Hat OpenShift
-
Ratings
Infrastructure Automation
9.00 Ratings
00 Ratings
Automated Provisioning
8.70 Ratings
00 Ratings
Parallel Execution
6.20 Ratings
00 Ratings
Node Management
7.70 Ratings
00 Ratings
Reporting & Logging
7.80 Ratings
00 Ratings
Version Control
8.10 Ratings
00 Ratings
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
8 because it's currently best-in-class and is completely essential to use in contrast to not expressing your infrastructure as code. That said, new contenders are nipping at its heels, and I expect stronger tools to emerge in the coming years. Hopefully the Terraform team is able to keep pace.
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.
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 errors generated by the plan and preview commands are pretty cryptic, it can be hard for newcomers to the scripting language to understand how to address problems.
Access controls around workspaces is limited which makes it harder to secure reduce the scope of teams ability.
Analytics around user usage, applies and plans would be helpful for managemenet.
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."
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
I love Terraform and I think it has done some great things for people that are working to automate their provisioning processes and also for those that are in the process of moving to the cloud or managing cloud resources. There are some quirks to HCL that take a little bit of getting used to and give picking up Terraform a little bit of a learning curve, thus the rating
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.
Terraform's performance is quite amazing when it comes to deployment of resources in AWS. Of course, the deployment times depend on various parameters like the number of resources to deploy and different regions to deploy. Terraform cannot control that. The only minor drawback probably shows up when a terraform job is terminated mid way. Then in many cases, time-consuming manual cleanup is required.
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.
Terraform is community driven but does offer support for it's Enterprise product. When contacting the team at HashiCorp we have always gotten resolution to our issues. They have been very responsive in returning our calls and answering our questions as they come up. We are currently using the open source model.
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.
dbt was fine, but you end up with an extremely bloated repo/project. Often where all of the models are the same, named similarly, and generally just doesn't adhere to the concept of DRY coding. In Terraform we're able to template a lot of this work and dynamically generate assets based on variables instead.
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.
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
Using code, we are able to build and deploy cloud resources faster and more consistently than producing the same resources in the console manually.
For applications that share architectures, we can reuse code to expedite development. We can also do the same with modules that are shared across the organization.
By defining all of our resources as code, we can deploy complete environments with "batteries included." For example, we can use code that spins up servers in a cloud provider and at the same time, creates monitors with in our monitoring provider. Likewise, when the servers are decommissioned, the monitors are decommed along with them. In the past, the creation and decom of the monitors would have been a disjointed, manual step. With Terraform we get it all with one "terraform apply."
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.
