GraphQL has been garnering much interest as a way to seamlessly interact with backend services. The query language is a boon for frontend developers, too, as it conveniently allows you to fetch the specific fields you require, thus eliminating the potential overfetching or underfetching concerns of REST APIs. And as GraphQL adoption matures within organizations, there is increasing interest (and investment) in how enterprises can use GraphQL to securely unify their growing catalog of disparate microservices and APIs.
Using GraphQL as a meta layer could help unite many disparate systems under a single unified schema. This would enable the age-old promise of composability, in which software building blocks are seamlessly pulled together to assemble applications and unique experiences for different client types. However, managing GraphQL at scale can become tricky. And when a schema gets really large, it then may require a schema of its own! This is where the concept of the supergraph comes in.
I recently met with Geoff Schmidt, Apollo GraphQL CEO, to discover what a supergraph is and how it may help platforms aggregate their backend microservices. According to Schmidt, “Developers want this composition layer for one abstract view of all their services.” Below, we’ll explore the concept of the supergraph and look at some new open source components that may help you enable GraphQL-based composability in your organization.
Microservices Enable Composability
First off, what do we mean by composability? Well, composable architecture is intrinsically linked with microservices. You can think of each microservice as a single lego piece that makes up one aspect of an application. For example, Uber uses 4,000 microservices to power its backend. These services span from maps, currency conversions, driver reviews, payments and other components. When combined, they ultimately create the convenience and the sleek user experience that is Uber.
Historically, software developers were overseeing larger monolithic applications in which a single client was interconnected to a web server, Schmidt explained. On the other hand, microservices tend to be more domain-specific and used in tandem with other microservices. They’re also typically easier to iterate on and faster to ship when compared to monolithic codebases.
The Need for Aggregation
As a result of the microservices age, applications typically pull in far more data from various sources. For example, a banking application might loop in a mortgage service, investment service and other data sources to display a combined net worth on a screen. This explosion in microservices has created a “polygon environment” spanning databases and APIs, increasing service complexity, said Schmidt.
Nowadays, many third-party components must be combined to render an experience. However, supporting this composability can be challenging for developers and backend API teams—not to mention that handwriting a backend-for-frontend could be burdensome. “App developers are slowed down by the need to integrate or compose these backend services,” said Schmidt. “Developers need a way to put all those pieces back together.”
What is Supergraph?
Supergraph can be thought of as a graph of graphs. The vision is to have one GraphQL schema and one ingress port to oversee many services. Creating a supergraph is becoming more accessible, too, as more open source projects emerge to enable this paradigm. For example, Apollo recently open sourced some components that can help to build and operate a supergraph. These include Federation, which helps to create a data graph across multiple services, and the Apollo Router, a tool written in Rust that decides how to route queries. Apollo has also open sourced a supergraph demo along with other resources.
A supergraph architecture is already powering Expedia, Walmart, Netflix, Paypal, the New York Times and other large environments, said Schmidt. For example, Expedia has used a supergraph to combine flights, rental cars and other microservices to create integrated experiences. Hivee, an upstart modern supermarket chain, also uses a supergraph to unite its investment into APIs.
According to Schmidt, the fundamental benefit is that less time is spent writing integration code which means faster development speed and the ability to quickly pivot your business. “It allows you to change business quickly to meet the needs of your customers.” A supergraph could also enable greater visibility into your API estate, making auditing easier.
A key benefit of the above components is that they already have a proven track record running at a commercial scale. But outside of the Apollo projects, other groups are attempting to codify a similar GraphQL schema aggregation concept, as well. For example, WunderGraph utilizes GraphQL within a “virtual graph” that acts as a common language to call various underlying APIs.
Repercussions of ‘One Graph to Rule Them All’
Schmidt said the hope is that, at the end of the day, this abstraction can contribute to “making the world a little more human-centric.” This is because GraphQL can enable less rigid apps that conform to unique user tastes. But a robust composition layer will be necessary to allow such reconfigurations.
Of course, as I’ve covered previously, there are significant security hurdles to address when supplying so much power to a single entryway. Increased GraphQL reliance will require forethought into new potential security risks, such as schema introspection and object-level authorization control.
According to Schmidt, a GraphQL composition layer presents an opportunity to enforce security controls. He defines these as contracts that create access rules for a particular set of users. By declaratively managing GraphQL security, a development team, in essence, could expose a subgraph of the supergraph for a partner to consume. The graph could even be segmented for internal teams.
A central point of ingress will require authorization rules to protect user privacy and avoid breaking the rule of least privilege. Schmidt also advocates for backend schemas to be built for app developers who understand their needs, instead of precisely mapping logic to business models.
Supergraph: A Graph of Graphs
Software is becoming more modular, which has resulted in an explosion of unique microservices and APIs. And we’re now at another tipping point in how software architecture is divided and combined, said Schmidt. He now sees GraphQL as a prime opportunity to create software architectures that call multiple backend services with a single GraphQL query.
“GraphQL is the composition layer you need to build modern applications,” said Schmidt. “We’re super excited about this. Users have shown that GraphQL is the future. Supergraph is such a powerful technology, and we’re excited to bring this to everybody.”
