 One of the biggest challenges that industries face today as they modernize the way they build and deploy applications in the cloud or on-prem is that they have to have access to data not just on a particular server or a particular deployment, but that data needs to be available in real time in a geo-distributed way. Redis Enterprise is focused on providing real-time access to data. And it does this by loading the data in memory in a key value store format. That's a technical way of saying it's not a relational database, and it's built to scale very quickly and very fast. And a lot of the problems that customers experience around that are the fact that much of their data is stored in a relational database. Now, these databases were built around an older client server deployment model, not for a modern cloud-based application. And when customers deploy applications to the cloud, they're really looking to take advantage of the ability to scale up and scale down based on usage. Our solution on the Red Hat Marketplace is Redis Enterprise. It's an in-memory NoSQL database. And we have an operator specifically for OpenShift that allows customers to easily deploy and scale the database across multiple clouds or in a hybrid scenario. One of the most valuable things about our partnership with Red Hat is the fact that the OpenShift technology use case aligns very closely with the Redis Enterprise use case. So as customers build and deploy applications that are going to land either in a hybrid model or a multi-cloud model on OpenShift, those applications are going to need real-time access to data and reduce latency when they try to do so. And for that, they're going to need a cache. So Redis Enterprise provides that in-memory cache that those applications can use. So anywhere that Redis is deployed is a good solid chance that OpenShift is deployed as well.