Learn from the experiences of large companies like PayPal, Netflix, and Shopify on how to effectively implement GraphQL in production. Discover best practices for optimal performance and functionality, and how to overcome common challenges when stitching multiple APIs together.

As a developer, I have always been interested in exploring new technologies and tools that can help me build better applications. When I first heard about GraphQL, I was intrigued by its promise of making data more intelligent and improving developer productivity. However, I was also skeptical about its ability to handle large quantities of data and deliver optimal performance in production.

Over the past few years, large companies such as PayPal, Netflix, Shopify, GitHub, Airbnb, and Coursera have adopted GraphQL in production to solve problems related to serving large quantities of data, reducing payload sizing, making data more intelligent, and improving developer productivity. These companies have leveraged GraphQL to boost development agility, shift API strategies, achieve greater specificity, and achieve 10 times greater agility at scale.

While the transition to GraphQL has not been perfect, these companies have praised its propensity to make developers more productive and enable them to build better applications. As I started exploring GraphQL, I realized that there are several best practices that developers need to follow to ensure optimal performance and functionality.

• One of the key best practices is serving over HTTP, which allows GraphQL to leverage existing infrastructure and tools for caching, load balancing, and security.
• Another best practice is using JSON with GZIP, which reduces payload size and improves network performance.
• Avoiding versioning is also important, as it can lead to fragmentation and complexity in the API.
• Nullability is another important consideration in GraphQL, as it allows developers to specify which fields can be null and which cannot.
• Implementing pagination is also critical, as it allows developers to fetch data in smaller chunks and avoid overloading the server.
• Server-side batching and caching can also improve performance by reducing the number of requests and minimizing data transfer.
• As GraphQL becomes increasingly popular, developers are also facing new challenges when stitching multiple APIs together. Schema updates and querying up instead of down can lead to issues that need to be addressed. To solve these issues, rearranging the setup and creating a Gateway API can be helpful.

In conclusion, GraphQL is a powerful tool for building APIs, but it requires careful consideration of best practices to ensure optimal performance and functionality. By following these best practices and learning from the experiences of large companies, developers can create efficient and effective GraphQL services that meet the needs of their users.