Red Hat OpenShift vs. Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

I've seen multiple universities that have quite investments in Red Hat enterprise virtualization. They don't want to go with the VMware route due to the expense. So Red Hat OpenShift virtualization is a natural fit for them in that environment. I've also seen a lot of VMware customers that are not able financially to sustain the cost increases with the product. So they're looking for an alternative. And Red Hat OpenShift virtualization fills that need.

Incentivized

If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.

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

• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

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

• Running on Azure is a little more difficult.
• Synchronization with Kafka may be a little easier.

Incentivized

Leverage OpenShift Online constantly at both the free and paid tiers. While AWS is convenient, it often brings more administration than I want to deal with for a quick application (i.e. Drupal or Wordpress blog). OpenShift also simplifies the DNS registration and ability to share application environments with team members

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

Openshift performance is based on the underlying infrastructure, the K8s design, and the applications' design. Cloud-native applications should have resilience baked in and should not depend on infrastructure resilience. Standard stateful apps may still depend on the underlying infrastructure. It depends on the approach.

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

They were very helpful. We needed support for initial implementation.

Incentivized

Our developer community is using Red Hat OpenShift for years and they are familiar and comfortable with the product. Red Hat OpenShift UI makes it easier for new developers to adopt without knowing much of Kubernetes. Our platform team feels it’s easy to mange the cluster and upgrades. Other options has more operation overhead and less friendly to developers not have in-depth knowledge of Kubernetes.

Incentivized

It's easy to understand what are being billed and what's included in each type of subscription. Same with the support (Std or Premium) you know exactly what to expect when you need to use it. The "core" unit approach on the subscription made really simple to scale and carry the workloads from one site to another.

Incentivized

• Positive: Reduction in physical and virtual machine footprint
• Negative: Lack of native end to end o11y has caused a great deal of focus from our enterprise monitoring folks
• Positive: OCP has allowed developers to have a quick and easy space to experiment

Incentivized

• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

Incentivized