Hasura, whose product helps compose GraphQL APIs backed by databases and services, today made available in beta an update to its platform. The company is adding a graph modeling framework that makes it simpler to manage application programming interfaces (APIs) at scale.

The goal is to make it easier for IT teams to declaratively create APIs and then manage them at scale, said Hasura CEO Tanmai Gopal. As application environments made up of multiple backend services and databases become the enterprise norm, there is a pressing need to simplify the management of what has become thousands of APIs in an enterprise IT environment using query compilers and routing capabilities built into the platform, he added.

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In version 3.0 of the Hasura Data Delivery Network (DDN), the “supergraph” execution engine is based on a serverless runtime engine that, the company says, will replace its previous graph technologies to manage both GraphQL and REST APIs.

In addition, all connectors provided by Hasura have been rebuilt using an open specification and are now available as open source software on the Hasura Connector Hub. Hasura is also making available a software development kit (SDK) to enable IT teams to build custom connectors.

Written in the Rust programming language, the supergraph framework eliminates the need to create and manage GraphQL servers or services to deploy a graph. Additional data domains as a result can be added or replaced without breaking the graph used to manage other APIs.

The update to the Hasura DDN also adds new build system to provide instant API previews and support for rollbacks, a redesigned console featuring a graphical supergraph viewer, API analytics, observability, and auto-generated API documentation capabilities. Every iteration of the Hasura supergraph is instantly available as an immutable build that can be tested in preview. Every change to the supergraph is also validated before build, letting users identify potential bugs, stylistic issues, syntax, and type errors.

In addition, Hasusa has added a sub-millisecond cold start capability to enable rapid autoscaling and plane to shortly add caching to improve API performance in edge computing environments.

Longer term, the company plans to add additional a range of artificial intelligence (AI) capabilities to enable IT teams to identify issues requiring troubleshooting earlier and generate reports, Gopal added.

While REST APIs are still more commonly used than GraphQL, more IT teams are employing the latter. That’s because GraphQL provides more control over how data is accessed and consumed. Most organizations will soon be using a mix of REST and GrapgQL APIs, but it might be years before REST is supplanted as the dominant format simply because those APIs are more familiar to developers and easier to create.

Regardless of the type of API used, however, their numbers continue to steadily increase with each microservice added to an IT environment. It’s not always clear which teams within an IT organization are managing those APIs but increasingly best DevOps practices are being used to deploy, manage, secure and update them alongside every other type of software artifact. The challenge, of course, is making it simple to manage those API workflows in a way that doesn’t require yet another specialist to be added to the DevOps team.