Next.js Serverless Architecture

What this diagram shows

This diagram illustrates a serverless web application architecture centred on Next.js, showing how requests flow from end-users through a CDN and edge network to serverless compute, then to managed databases and background job systems. It captures the modern pattern where static assets and API routes run on edge infrastructure, database operations happen through connection pooling, file uploads use presigned URLs for direct cloud storage access, and asynchronous work (emails, data processing) gets queued for separate worker functions. The architecture separates concerns into request handling, persistent data, background tasks, and object storage, each scaling independently.

Key components

• CDN and Edge Network — Caches static assets and forwards dynamic requests to the nearest edge location for faster first-byte times.
• Next.js Serverless Functions — Executes API routes and server-side rendering logic on-demand without managing servers or containers.
• Postgres Database with Connection Pool — Stores relational data with connection pooling middleware to avoid exhausting database connections from short-lived function invocations.
• Job Queue Service — Holds async tasks (emails, reports, webhooks) and delivers them to worker functions for processing outside request lifecycle.
• Worker Functions — Executes background jobs pulled from the queue, decoupled from user-facing request handling.
• Object Storage Bucket — Holds user-uploaded files with direct access via presigned URLs, bypassing the application layer for upload and download.
• Secrets Manager — Stores and injects database credentials and API keys securely into functions at runtime.

When to use it

Use this template for web applications expecting variable traffic that benefit from automatic scaling without managing infrastructure. It suits projects with database-backed content, file uploads, and background processing needs. Ideal when you want to pay only for compute actually consumed and minimise operational overhead. Works well for content platforms, SaaS applications, and internal tools where serverless latency is acceptable and most traffic concentrates in a geographic region.

Common mistakes

• Failing to implement connection pooling between serverless functions and Postgres, causing the database to reject connections when function concurrency spikes.
• Uploading files directly through the application instead of using presigned URLs, forcing the application to buffer uploads and bottlenecking throughput.
• Putting long-running operations directly in request handlers instead of queuing them, causing user-facing requests to timeout or exceed function duration limits.

Adapting it to your system

Start by identifying your data schema and create a Postgres database with PgBouncer or similar pooling. Replace your Next.js API routes with serverless function syntax specific to your platform (Vercel Functions, AWS Lambda, Google Cloud Functions). For uploads, generate presigned URLs in an API route pointing to your object storage bucket. Define background job types (emails, notifications, reports) and queue them during request handling using a service like Bull, BullMQ, or AWS SQS, with separate workers polling and processing them. Test connection limits and timeout behaviour under expected peak concurrency.