Best of 2024: Diagrid Makes Beta of Managed Dapr Service Available

Diagrid has made available a public beta of a managed instance of the Dapr framework that provides application developers with a reusable set of application programming interfaces (APIs) for invoking communication, publish/subscribe, state management, workflow and secret management services.

Company CTO Yaron Schneider said Diagrid Catalyst provides developers with access to a serverless computing environment through which they can invoke Dapr, versus having to rely on an internal IT team to deploy and maintain the framework themselves.

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Originally developed by Microsoft, Dapr provides a runtime framework that eliminates the need for developers to write the same boilerplate code multiple times over for each microservice they build.

The overall goal is to increase developer productivity by making available a standard set of APIs that can be used to make building cloud-native applications easier, said Schneider. In effect, Dapr provides an overlay for safely invoking services in a consistent fashion, he noted.

It’s not clear to what degree organizations might prefer to deploy Diagrid Catalyst themselves versus relying on a managed service, but a significant portion of various classes of IT infrastructure resources and middleware is now being consumed as a service. Many organizations simply prefer to focus as much of their limited resource as possible on building and deploying software rather than managing infrastructure.

At the same time, development teams have become less pedantic over the degree to which they are employing microservices, noted Schneider. In many cases, monolithic applications now expose a set of application programming interfaces (APIs) that allow them to be invoked as a service. In effect, a monolithic application becomes a large microservice within a complex IT environment that Diagrid Catalyst makes simpler to invoke, he added. Those IT environments in addition to Kubernetes clusters now incorporate everything from traditional virtual machines to serverless computing frameworks that make it simpler to scale IT infrastructure resources.

In the long term, many developers will also be able to use Dapr to automate the boilerplate code required to invoke artificial intelligence (AI) agents that will be employed to automate a wide range of tasks, noted Schneider.

Regardless of how microservices applications are built in the age of AI, it’s likely more applications will be built in the next few years using AI tools that have been built and deployed in the next decade. In many instances, AI agents, in addition to being embedded in applications, will be employed throughout the software development lifecycle to make, for example, invoking frameworks such as Dapr simpler. The end result should be an explosion of cloud-native applications that previously required a lot more expertise to build and deploy.

Productivity, of course, is a growing concern among data science and application developers. Business leaders are pressuring them to operationalize the latest advances in generative AI but all too often efforts are being hampered by the sheer volume of boilerplate code required.

The challenge and opportunity now is finding ways to eliminate as many rote tasks as possible to enable developers to spend more time on the elements of an application that truly adds value to the business.