How can you implement continuous integration with GraphQL APIs?

Continuous integration (CI) is a practice that helps developers deliver high-quality code faster and more reliably. It involves automating the building, testing, and deployment of code changes whenever they are pushed to a version control system. CI can also improve the collaboration and feedback loop among developers, testers, and stakeholders.

GraphQL is a query language and a runtime system that allows clients to specify the data they need from an API. GraphQL APIs can offer many benefits, such as faster performance, better scalability, and more flexibility. However, they also pose some challenges for CI, such as schema validation, mocking, and testing.

In this article, you will learn how to implement CI with GraphQL APIs using some common tools and techniques. You will also see some examples of how to configure your CI pipeline and write your tests for GraphQL APIs.

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1 Choose a CI platform

When implementing CI with GraphQL APIs, the first step is to select a platform that fits your workflow and technology stack. Popular options include GitHub Actions, Jenkins, CircleCI, and Travis CI. Each platform should offer features like integration with your version control system and hosting service, support for your programming language and GraphQL framework, parallel and distributed job capabilities, customization and configuration options for pipeline stages and steps, and reporting and notification tools for test results and code coverage.

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Paul Sweatte
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Use a feature comparison site to do an apples-to-apples comparison of CI tools in order to compare them equally. In terms of growth, be sure to look into the pricing tiers and your budget to ensure one does not outstrip the other.

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2 Validate your GraphQL schema

The next step to implement CI with GraphQL APIs is to validate your GraphQL schema. The schema is the contract between your client and your server that defines the types, queries, mutations, and subscriptions that your API supports. Validating your schema can help you catch errors, inconsistencies, and breaking changes before they affect your clients.

There are different ways to validate your schema, depending on your CI platform and your GraphQL framework. For example, you can use the Apollo CLI tool to check your schema against a reference schema stored in Apollo Studio, a cloud service that provides schema management and analytics for GraphQL APIs. Alternatively, you can use the graphql-schema-linter tool to check your schema against a set of rules and best practices.

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3 Mock your GraphQL server

The third step to implement CI with GraphQL APIs is to mock your GraphQL server. Mocking your server can help you isolate your client-side code from your server-side dependencies and speed up your testing process. Mocking your server means creating a fake or simulated server that returns predefined data for your GraphQL queries and mutations.

There are different ways to mock your server, depending on your CI platform and your GraphQL framework. For example, you can use the Apollo Server Testing library to create a mock server based on your schema and your resolvers. Alternatively, you can use the graphql-tools library to create a mock server based on your schema and some custom functions.

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Paul Sweatte
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Decide upfront whether or not to mock your environment specific user IDs when testing queries and mutations. This will have a large impact on whether or not you need to test the integrity of the mock data against environment specific constraints or not.

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4 Test your GraphQL queries and mutations

The fourth step to implement CI with GraphQL APIs is to test your GraphQL queries and mutations. Testing your queries and mutations can help you verify that your API returns the expected data and handles the possible errors. Testing your queries and mutations means writing and running code that sends requests to your GraphQL server and compares the responses with the expected results.

There are different ways to test your queries and mutations, depending on your CI platform and your GraphQL framework. For example, you can use the Jest framework and the @apollo/client/testing library to write and run tests for your React components that use Apollo Client to fetch data from your GraphQL server. Alternatively, you can use the Mocha framework and the supertest library to write and run tests for your Node.js server that uses Express and GraphQL.

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Paul Sweatte
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Make sure both the variables and results are validated using a JSON schema. This will ensure that data quality is encapsulated within the tests and that not only is the GraphQL schema validated, but also the payloads being passed back and forth between the client and the server.

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5 Test your GraphQL subscriptions

The fifth step to implement CI with GraphQL APIs is to test your GraphQL subscriptions. Subscriptions are a feature of GraphQL that allows clients to receive real-time updates from the server when data changes. Testing your subscriptions can help you verify that your API sends the correct notifications and handles the possible errors. Testing your subscriptions means writing and running code that establishes a connection to your GraphQL server and listens for the events.

There are different ways to test your subscriptions, depending on your CI platform and your GraphQL framework. For example, you can use the Jest framework and the @apollo/client/testing library to write and run tests for your React components that use Apollo Client to subscribe to data from your GraphQL server. Alternatively, you can use the Mocha framework and the ws library to write and run tests for your Node.js server that uses WebSocket and GraphQL.

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Paul Sweatte
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The subscription implementation is an optional part of the GraphQL specification. If it is not provided, the server does not support subscriptions. If the server does not support subscriptions, they cannot be tested.

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6 Monitor your GraphQL performance

The sixth and final step to implement CI with GraphQL APIs is to monitor your GraphQL performance. Monitoring your performance can help you identify and optimize the bottlenecks and inefficiencies of your API. Monitoring your performance means collecting and analyzing metrics such as response time, error rate, query complexity, and query depth.

There are different ways to monitor your performance, depending on your CI platform and your GraphQL framework. For example, you can use the Apollo Studio service to track and visualize your performance metrics for your GraphQL API. Alternatively, you can use the graphql-query-complexity and graphql-depth-limit libraries to limit and measure the complexity and depth of your GraphQL queries.

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Mudassar Ahamer Hakim

Tech Leader & People Manager | Driving Engineering Excellence & Team Growth | Delivering Impactful Solutions
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in addition to the mentioned tools, there are other 2 effective performance monitoring tools and services: New Relic: New Relic is a comprehensive application performance monitoring tool that can be used for monitoring GraphQL APIs. It provides real-time insights into response times, error rates, and database queries, helping you pinpoint performance bottlenecks. Prometheus and Grafana: These open-source tools, when used together, can provide powerful monitoring and alerting capabilities. Prometheus collects metrics, while Grafana offers visualization and alerting features. You can set up custom queries to monitor specific aspects of your GraphQL API.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Paul Sweatte
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Deprecation directives or arguments within a GraphQL server implementation should be tested as part of integration with the GraphQL specification.

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How can you implement continuous integration with GraphQL APIs?

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1 Choose a CI platform

2 Validate your GraphQL schema

3 Mock your GraphQL server

4 Test your GraphQL queries and mutations

5 Test your GraphQL subscriptions

6 Monitor your GraphQL performance

7 Here’s what else to consider

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