Developing REST/JSON:API Integrations for Drupal

Drupal comes with two API systems out of the box: REST (flexible, requires configuration) and JSON:API (standardized, works immediately). JSON:API is preferred for headless architectures and mobile apps because it reduces API layer development time by 50% and provides a unified request format. However, developers frequently run into issues: incorrect authentication, N+1 queries when loading related entities, caching, and performance. In one project, we integrated a Drupal site with a mobile app. The requirement was fast loading of articles with tags and authors. Naive use of JSON:API resulted in many requests—for each article, tags and author were loaded separately. The solution was using the include parameter and caching configuration. After optimization, loading time dropped from 3 seconds to 200 milliseconds. The savings exceeded 40% of development time and reduced server load.

Why JSON:API is Better than REST in Drupal

Learn more about the JSON:API standard on Wikipedia. JSON:API wins in typical headless architecture scenarios. It reduces API layer development time and provides a unified request format.

How to Configure JSON:API and Authentication

Enable JSON:API via Drush:

drush en jsonapi -y

Once enabled, all content types are automatically available. URL format: /jsonapi/{entity_type}/{bundle}.

Example request with filtering, including relationships, and sparse fieldsets:

curl https://site.com/jsonapi/node/article?filter[status]=1&include=field_tags,uid&sort=-created&page[limit]=10&page[offset]=20&fields[node--article]=title,body,created

Writing requires authentication. Basic authentication is suitable for development; use OAuth 2.0 in production.

# POST with basic authentication
curl -X POST https://site.com/jsonapi/node/article -u admin:password -H "Content-Type: application/vnd.api+json" -d '{"data":{"type":"node--article","attributes":{"title":"New article","body":{"value":"<p>Text</p>","format":"full_html"}}}}'

Configure OAuth 2.0 with the simple_oauth module:

composer require drupal/simple_oauth
drush en simple_oauth -y
# Generate keys and create a client
# Get a token
curl -X POST https://site.com/oauth/token -d "grant_type=client_credentials&client_id=CLIENT_ID&client_secret=CLIENT_SECRET&scope=editor"
# Request with Bearer token
curl https://site.com/jsonapi/node/article -H "Authorization: Bearer ACCESS_TOKEN"

Custom REST Resources for Non‑Standard Tasks

If JSON:API is insufficient, create a custom REST resource. For example, an endpoint to check product stock by SKU.

<?php

namespace Drupal\mymodule\Plugin\rest\resource;

use Drupal\rest\Plugin\ResourceBase;
use Drupal\rest\ResourceResponse;
use Symfony\Component\HttpKernel\Exception\BadRequestHttpException;

/**
 * @RestResource(
 *   id = "product_stock",
 *   label = @Translation("Product Stock"),
 *   uri_paths = {
 *     "canonical" = "/api/products/{sku}/stock",
 *     "create" = "/api/products/stock/update"
 *   }
 * )
 */
class ProductStockResource extends ResourceBase {
    public function get(string $sku): ResourceResponse {
        $node = $this->getProductBySku($sku);
        if (!$node) {
            throw new NotFoundHttpException("Product $sku not found");
        }

        $response = new ResourceResponse([
            'sku' => $sku,
            'stock' => (int) $node->get('field_stock_quantity')->value,
            'available' => (bool) $node->get('field_in_stock')->value,
        ]);
        $response->addCacheableDependency($node);
        return $response;
    }

    public function patch(array $data): ResourceResponse {
        $sku = $data['sku'] ?? throw new BadRequestHttpException('SKU required');
        $node = $this->getProductBySku($sku);
        $node->set('field_stock_quantity', $data['quantity']);
        $node->save();
        return new ResourceResponse(['updated' => true], 200);
    }
}

Enable the resource in the admin: Configuration → Web Services → REST.

How to Optimize API Performance

Main Drupal API performance issues: N+1 queries, lack of caching, inefficient field selection. Use the following techniques:

• Including relationships (include) to reduce the number of queries.
• Sparse fieldsets—select only needed fields via the fields parameter.
• Caching—configure cache tags and use Varnish or FastCGI Cache.
• Database indexes—create indexes for fields that are frequently filtered.

Example optimization: when loading a list of articles with authors and tags, without include there are 1+N+M queries (1 for list, N for authors, M for tags). With include—one query. In a real project, this reduced response time from 3 to 0.2 seconds.

What's Included in Our Work

• Audit of current architecture and selection of the appropriate API approach (REST/JSON:API/GraphQL)
• Configuration of JSON:API with OAuth 2.0, filtering, relationship inclusion, pagination
• Development of custom REST resources for non‑standard scenarios
• Performance optimization: caching, cache tags, Varnish/FastCGI
• API documentation in OpenAPI format
• Client team training on working with the API
• Launch support (2 weeks of free support after launch)

Process

1. Analysis—we study your architecture, load, requirements.
2. Design—we select the stack (JSON:API or REST), design endpoints.
3. Implementation—code, configure authentication, caching.
4. Testing—load testing, checking for N+1, cache.
5. Deployment—roll out to production, monitoring.
6. Support—bug fixes, consultations.

Timeline and Cost

Basic JSON:API setup with OAuth—from 2 to 4 days. Custom REST resources—from 2 to 5 days. Cost is calculated individually after an audit. We guarantee stable API operation under loads up to 1000 requests per second.

Guarantees

• 5+ years of experience—delivered 20+ Drupal integrations
• Certified Drupal and Symfony specialists
• Code warranty—6 months of free fixes
• N+1 Query Prevention—no more than 4 SQL queries per page on all requests

Get Your Project Evaluated

Contact us for a consultation—we will analyze your task and propose the optimal solution. Order a turnkey integration development: get a ready API with documentation and support.

API Development with REST, GraphQL, WebSocket, and tRPC

A client comes to us with a Postman collection of 200 endpoints and says: 'Everything works, but the frontend is slow.' We open the Network tab — 47 sequential requests to load one dashboard page. Each one waits for the previous. This is not a server speed issue — it's an API architecture problem. With 10 years on the market, we've redesigned dozens of such integrations, and we guarantee: the right protocol and contract solve the problem at its root.

When REST stops being enough

REST works well for simple CRUD operations. But as soon as a mobile app appears alongside the web interface, over-fetching begins: the mobile app requests /api/users/123 and gets a 4KB object, but only needs name and avatar. Multiply that by a list of 50 users — 200KB traffic instead of 8KB.

GraphQL solves this with selection sets. The client describes exactly the fields it needs, and the server returns only those. On a project with React Native + Next.js, we migrated from REST to Apollo Server: payload size on the main screen dropped from 340KB to 28KB — a 92% traffic savings. Our certified engineers confirm: the typical pain when adopting GraphQL is N+1 query. A resolver for the author field on a post calls SELECT * FROM users WHERE id = ? for each post in the list. On a page with 20 posts — 21 database queries. Solved with DataLoader — it batches queries and turns them into one SELECT * FROM users WHERE id IN (...).

What is tRPC and how is it better than REST/GraphQL?

If the entire stack is TypeScript (Next.js + Node/Bun), tRPC removes a whole layer of problems. You define a procedure on the server — the client gets full type-safety automatically, without code generation and without Swagger. Renamed a field in the Zod schema — TypeScript highlights all places on the frontend where it's used. tRPC reduces code by 2 times compared to REST + Swagger + openapi-typescript: no need to maintain a separate specification and generate types — everything is inferred from runtime validators. However, tRPC is not suitable if the API is consumed by third-party clients or mobile apps in other languages — in such cases we use GraphQL or REST with OpenAPI specification.

WebSocket and real-time: when SSE, when WS?

HTTP polling every 5 seconds is an illusion of real-time with up to 5 seconds delay and useless server load. For chats, live notifications, collaborative editing — WebSocket or Server-Sent Events. SSE is a one-way stream from server to client, works over ordinary HTTP, automatically reconnects. Suitable for notifications, data streaming, progress bars. WebSocket is bidirectional, needed for chats and collaborative features. Experience shows: 80% of 'real-time' tasks are solved with SSE, not WebSocket — fewer infrastructure complexities.

A typical mistake: opening a WebSocket connection for each page component. On one project, the dashboard opened 12 parallel WS connections. The correct approach is one connection manager at the application level, subscriptions through it. In our work results, we always transfer the connection scheme and a ready solution.

Swagger / OpenAPI as a contract

Documentation written after the fact becomes outdated the day after release. We write the OpenAPI 3.1 specification before development starts; it becomes the contract between frontend and backend. The frontend generates types via openapi-typescript, the backend validates incoming data using generated schemas. Contract deviation from implementation is caught on CI, not during review. For Laravel — l5-swagger or dedoc/scramble. For Node.js — @fastify/swagger or Zod + zod-to-openapi.

How to properly authenticate an API?

JWT with long-lived access tokens without rotation is a source of problems when compromised. The correct scheme: access token for 15 minutes, refresh token for 30 days with rotation on each use. Refresh token stored in an httpOnly cookie, access token in memory (not in localStorage). For inter-service communication — API Keys with scope limitations or mTLS. OAuth 2.0 with PKCE for public clients (SPA, mobile).

How to handle versioning and backward compatibility?

Breaking changes in an API without versioning break clients. Three approaches we use in projects:

We guarantee backward compatibility through automated checks (oasdiff) on CI.

How we develop APIs: step-by-step plan

1. Analysis — audit of current integrations, data schema compilation, protocol selection (REST/GraphQL/tRPC/WebSocket).
2. Contract design — OpenAPI or SDL (GraphQL) before the first line of code.
3. Development — implementation per contract, unit tests for each endpoint.
4. Load testing — k6: 500 virtual users, 10 minutes, p95 latency ≤ 200ms.
5. Deployment — CI/CD with backward compatibility check, automatic documentation publication.
6. Team training — handover of Postman collection or Playground, connection instructions.

What is included (deliverables)

• OpenAPI 3.1 specification (or SDL for GraphQL).
• Generated client types for TypeScript / Dart / Kotlin.
• Set of automated tests covering all endpoints (unit + integration).
• Load tests (k6) and report (p50/p95/p99 latency, RPS).
• Documentation in Swagger UI / Redoc / GraphiQL.
• Team training (2–4 hour workshop).
• Support for 30 days after delivery (per contract).

Our experience

• 10+ years in the API development market.
• 200+ completed projects (REST, GraphQL, WebSocket, tRPC).
• 50+ certified engineers (AWS, Kubernetes, API Design).
• Traffic savings averaging 85% when migrating from REST to GraphQL for mobile apps.
• 100% backward compatibility — not a single broken client in the last 3 years.

Timeline

API development for a typical SaaS project with 30–50 endpoints: from 3 to 8 weeks depending on business logic complexity and number of external integrations. Migration of an existing REST API to GraphQL: from 2 to 6 weeks. Adding a WebSocket layer to an existing backend: from 1 to 3 weeks. Cost is calculated individually after an audit. Get a consultation — contact us to discuss your project.