Now that we're a little more well versed on data mesh, let's jump back into our data mesh prototype. At the end of the last hands on module we had just kicked off our data mesh creation script. Let's check in on that. If the data mesh was successfully created, you should see log entries similar to the ones on the screen. If you do that means that the server is now running and waiting to handle requests from clients. With it up and running, open a browser to the landing page where you'll see an overview of the features of the data mesh prototype. The UI is designed with a loose workflow from left to right following the tabs across the top. When you initially use the prototype start with exploring the data products in the explore data products tab and then move on to creating and publishing data products. For the purposes of the prototype, you are a member of the analytics domain and the explore tab shows the data products that are available to you. The data products listed here are event streams, though in a production environment, you could also expect to see other types of data products such as those provided by synchronous APIs. Let's take a closer look at one of the products. You'll be presented with additional information such as, the domain and owner metadata values, representing governance responsibility over the data product. Quality in SLA fields that can be used to indicate to consumers of data products, what they can expect from data quality when consuming the data product and the SCHEMA, which allows you to explore the fields and data types that make up the data product. Below the data products detail information are some buttons which forward you to different views in confluent cloud console. Each of these views provides more detail about the data products, underlying Kafka topic, SCHEMA, and more. In the topic detail view, you'll get information about the topic backing the data product as well as production and consumption rates. Data lineage provides detailed information about the data products relationships with other up and downstream applications and dependencies. And finally export allows you to export data products into your application data stores, using Kafka connect. That wraps up the data products tour. You should now be fairly familiar with the data mesh console and data products. In the next module, we'll look at creating a new event streaming application from an existing data product, see you there.