Navigating the GraphQL adoption path and not getting lost along the way

Adopting GraphQL (GQL) can be a game-changer for your API strategy, offering flexibility and efficiency that traditional REST APIs can’t match. But, like any significant technological shift, the journey to fully embrace GQL comes with challenges. This post will explore these challenges and explain why focusing on GQL and leveraging a gateway like Tyk can make all the difference.

First things first: What are some of the best use cases for adopting GraphQL? We all know that GraphQL is a powerful query language for APIs and a runtime for executing those queries, but – contrary to some opinions – it is not the “new” REST. It shines in some use cases, while it might not be a great idea for others. Some of those use cases would be:

Backend for Frontend (BFF) Patterns

In scenarios where different frontends (web, mobile, IoT) require tailored data responses, GraphQL can be used to implement the Backend for Frontend (BFF) pattern. It allows each frontend to query exactly its needs without impacting other frontends, providing a clean separation of concerns.

Complex client-side applications

GraphQL shines in applications with complex front-end requirements, especially single-page applications (SPAs) and mobile apps. It allows clients to request exactly the data they need, reducing over-fetching and under-fetching issues common with REST APIs. This benefits applications with diverse data consumption needs across different views and components.

Content Management Systems (CMS) and E-commerce platforms

GraphQL’s flexibility benefits CMS and e-commerce platforms, where content and product data often have complex relationships and varied querying requirements. GraphQL allows frontend developers to fetch precisely the data needed for different pages and components, optimising performance and development efficiency.

Developer productivity and rapid prototyping

GraphQL’s type system and introspection capabilities enhance developer productivity by providing precise and self-documenting APIs. This reduces the learning curve and accelerates development, making it easier to prototype and iterate quickly.

This list is not exhaustive and covers only the essential, most common use cases, but we’re talking about GQL adoption here, so it’s only fair we start with the easier stuff first.

GraphQL adoption stages

Like with any new technology, there are several stages you will go through before being able to say you’ve adopted and implemented GraphQL in your organisation. Let’s take a look at them.

Stage 1 – Learning and exploring

At this stage, your team or whole organisation might start looking at GraphQL to assess if implementing it is worth the hassle. If you’ve never worked with GQL APIs before, this is where you need to learn and start shifting your mindset from REST. Resources are endless, like with anything on the Internet, but to give your learning journey some structure, you might want to follow a few simple steps:

  • Start with the official specification and learning provided by GraphQL Foundation. This will give you a great head start into the world of GraphQL.
  • Continue with some hands-on practice. Public GraphQL APIs that offer GQL Playground features are available. It will help you practice writing queries and mutations and understand GQL syntax intuitively.
  • Build a sample project. You can start by cloning and modifying a project available on GitHub to understand how real-world GraphQL servers and clients are set up. Then, you can move on to building your own from scratch using one of the many tools available.

There are dozens of great resources available, many listed by GraphQL Foundation

Stage 2 – Deploying the first graph in production

After completing the initial learning and feeling comfortable, you can build and deploy your first GQL API. Apart from obvious things like understanding the project requirements or defining clear objectives, there are more decisions, choices, and challenges at this stage.

  • Choosing the right tools and frameworks – These include GQL server implementation, database integration, or libraries.
  • Designing a GQL schema requires a significant mindset shift if you’re coming from a RESTful world. Understanding and splitting the business domain into coherent schemas and types within them is challenging, even for advanced GQL users.
  • Defining resolvers and data fetching strategies – Each field in your schema needs an efficient resolver to fetch data. You need to think about gracefully handling errors as well. How you implement data fetching will determine how optimal your GQL performance will be.
  • Handling security – The bare minimum for any API is authenticating clients that use it, and it’s not different for GraphQL APIs. GraphQL poses additional challenges due to its graph nature—you also need to think about field-level permissions, query complexity and depth, input validation, or restricting access to introspection.
  • Logging and error handling are standard things in any application. However, with multiple resolvers underlying any GQL API, implementing robust logging (for example, Open Telemetry) becomes crucial to debugging any issues later.
  • Testing thoroughly—For use cases like BFF patterns or complex client-side applications, integration testing is one of the most important stages so that any feedback can be acted upon quickly and efficiently. Delivering GQL APIs quickly to internal teams is important for fast and right iterations.
  • Monitoring and maintenance—Setting up monitoring throughout the request execution process helps detect issues and errors quickly in production. Consider leveraging Open Telemetry tracing for in-depth tracking of your GQL server.

As you see, there are many things to take care of and many places where you might face challenges.

Stage 3 – All-in on GQL and delivering multiple graphs

Now, let’s start by being honest—not every project needs to reach this stage. GraphQL might be used only in a specific use case in your organisation, and there’s no need to build dozens of graphs when scaling. Just a few will suffice. However, if you reach this stage, more challenges and risks await.

  • Standardisation of delivery and global best practices – At some level in your organisation, you will need to establish some standardisation so as not to regret it later. Creating schema conventions, especially in naming and schema design, will help create a friendly user experience for your clients. Internally, it will ensure uniformity and lack of schema conflicts later on.
  • Reusable components – This is a universal practice regarding the code base, but developing and maintaining reusable libraries for logging or error handling might help you speed up when you deliver more GraphQL APIs. 
  • Standardisation of security settings – This is more of an API management issue than just a GQL adoption-specific thing, but GraphQL APIs, as any other, also need that angle. It helps to gain full control over who’s accessing what and when consistently, protects APIs from abuse, and saves your backend resources from the unforeseen costs of complex GQL operations. It also helps to validate input data to prevent injection attacks.
  • Optimising performancePerformance optimisation is crucial as you scale. Use query batching, caching, and persisted queries to improve load times. Monitoring tools help identify and address performance bottlenecks proactively.
  • Solid documentation and developer experience – Comprehensive documentation is vital for GraphQL’s success. Clear guidelines, best practices, and support channels foster a collaborative and innovative developer community.

Stage 4 – You’ve got plenty. Now compose

For now, this is the ultimate stage of GQL adoption—composing multiple graphs. This can be done in two main ways: federation or schema stitching. With that, new considerations need to be made.

  • Choosing the right approach – both federation and stitching can ultimately achieve similar results, but at this point, it’s crucial to understand the use case you have in front of you and what will fit it better. If you’re looking to understand differences a bit better, check out this post.
  • Versioning and deprecation—no matter which option you choose, managing new versions of your schema will become more challenging because changes will come from more than one direction.
  • Monitoring and observability – Since your services are now composed of other services, this point becomes essential to ensure that debugging does not become a nightmare. Robust monitoring and observability tools will allow you to catch issues quickly and react in time.

The road ahead with GraphQL

GraphQL offers a more flexible and efficient alternative to traditional REST APIs, transforming your API strategy. However, the journey involves several stages, each requiring careful planning and execution. You can effectively navigate these challenges by focusing on best practices, leveraging tools like Tyk, and fostering a strong developer community. Ultimately, GraphQL’s benefits – enhanced productivity, tailored data responses, and improved performance—make the effort worthwhile, positioning your organisation for greater innovation and success. 

In the upcoming weeks, we will explore each stage in more detail and see how Tyk Gateway can help on this adoption journey.