Note: If you haven’t already done so, I recommend reading John Dias’s blog on the API-first approach that was taken when building VMware Tanzu Hub and the graph data store that powers it under the hood. Note that the platform name has changed since the publication of that blog, and VMware Aria Hub and Graph is now known as VMware Tanzu Hub.
The graph data store behind VMware Tanzu Hub is essential to centralizing application delivery and multi-cloud management by rationalizing data from many sources and making it easier to understand and manipulate. As discussed in the blog linked above, the graph data store in Tanzu Hub delivers a unified consumption surface that meets the unique needs of platform engineers, cloud operators, site-reliability engineers (SREs), and other users or administrators.
By bringing together data from multiple management services (such as public clouds, VMware Tanzu products, and other third-party tools) and normalizing it into a common object model in the form of a graph, objects can be referenced from a single API call with GraphQL. This is a critical capability. Whereas, in the past, platform engineers would have to make individual API calls for each product they use and rationalize different data points for the same object, they now can do so with a single API call and gather only the information they are interested in. Using GraphQL, users can more easily query, mutate, or subscribe to data in the graph and visualize it elegantly in Tanzu Hub’s user interface (UI).
While the capabilities offered through this single API call are powerful, users might be concerned that they lack the working knowledge of GraphQL to take advantage of it. However, with the initial availability of Intelligent Assist in Tanzu Hub—the addition of a generative AI tool to the platform—users can simply use natural language to ask for the GraphQL code needed to accomplish their task. Intelligent Assist helps by abstracting the knowledge of GraphQL and Tanzu Hub’s GraphQL schema, taking this burden away from the user and leaving them with only the task of reviewing what is generated to ensure it meets their needs. After the code is produced by Intelligent Assist, it can be run for you, but you can also review, edit, and rerun the query itself as you see fit.
Intelligent Assist enables more advanced use cases with GraphQL in Tanzu Hub. For example, you can ask Intelligent Assist to generate GraphQL code that will perform checks on a desired set of objects in the graph data store, allowing you to monitor changes more closely, ensure compliance with governance policies, and even make necessary changes.
Intelligent Assist can also help with generating GraphQL code that goes beyond completing single tasks, performing workflows based on your specifications. You can ask Intelligent Assist to create a script that will automatically update several cloud resources based on a conditional logic check that you set. You can take the GraphQL query generated by Intelligent Assist, import it into a pipeline, and do daily checks on a metric or status of your choosing. You might be interested in checking all VMs from a specific deployment to understand if any have a CPU utilization percentage over a certain threshold you have set, then making the necessary rightsizing adjustments. In this example, Intelligent Assist and Tanzu Hub help you generate the GraphQL code you need and enable you to take advantage of the graph data store for use in other tools you might be using.
The above scenarios are just a few examples of how Intelligent Assist in Tanzu Hub can help you get the most out of GraphQL and the graph’s single API access point. Of course, teams will find their own specific use cases that can be successfully delivered through these tools. There are also plenty of resources within Tanzu Hub to help people further educate themselves, including API documentation and a built-in GraphQL client for developing and testing your own GraphQL queries.
The graph data store behind Tanzu Hub is key to enabling the powerful capabilities that the platform offers, including the end-to-end services built on top of it, such as VMware Tanzu Guardrails and VMware Tanzu Insights, as well as the single API call that allows you to access data from any of your integrated products using GraphQL. Now, the addition of Intelligent Assist reduces the learning curve one might encounter using GraphQL, making consumption of the single API much easier and accelerating their ability to deliver applications and manage multi-cloud environments with VMware Tanzu Hub.
