Scaling APIs and Optimizing Response Times to Stay Under 500ms

⚡ Scaling APIs and Keeping Response Times Under 500ms

As backend developers, we often optimize for functionality first. But when your app starts gaining traffic, speed becomes the real feature. An API that responds in under 500ms doesn’t just feel fast — it’s scalable, efficient, and cheaper to run.

💡 Why 500ms Matters

Let’s say one of your APIs takes 600ms to respond. That may feel okay during development. But imagine your app gets just 100 requests per second during peak traffic:

• 100 req/sec × 600ms = 60 seconds of processing time every second
• Across multiple endpoints, this quickly becomes unsustainable

And that’s on a single server. Add horizontal scaling, and your backend load grows exponentially. Suddenly, small inefficiencies in your APIs start costing real CPU time, memory, and money.

🧠 Optimize Database Usage First

One of the biggest culprits of slow APIs is the database layer. Here’s a key rule to follow:

Keep your database calls to 1–2 per request. If you're doing more than 3, refactor your logic.

With Prisma + PostgreSQL, it’s easy to query only what you need:

const user = await prisma.user.findUnique({
  where: { id: userId },
  select: { id: true, name: true, email: true }
});

If you need related data, don’t fire off a second query — use include to batch fetch:

const post = await prisma.post.findUnique({
  where: { id: postId },
  include: { author: { select: { name: true } } }
});

This keeps the query count low, avoids N+1 issues, and improves speed with almost no effort.

🚀 Server-Side Caching = Instant Boost

If your API serves similar data repeatedly (like user dashboards or public content), cache it. Here’s how:

🔹 In-Memory Caching

For low-scale projects, a simple LRU or object cache works:

const cache = new Map();
if (cache.has(key)) return cache.get(key);

const data = await prisma.user.findMany();
cache.set(key, data);
return data;

🔹 Redis Caching

For distributed and production-ready caching, use Redis:

const cached = await redis.get('stats');
if (cached) return JSON.parse(cached);

const stats = await prisma.stats.findMany();
await redis.set('stats', JSON.stringify(stats), 'EX', 60);
return stats;

This offloads pressure from your database and reduces response times to under 100ms in many cases.

🔧 Other Key Optimizations

• Use compression: Gzip or Brotli reduce payload size
• Return only required fields: Don’t send full objects
• Paginate: Always use limit/offset on large lists
• Use Promise.all: Run non-dependent operations in parallel

📉 Final Thoughts

Optimizing your APIs is not about perfection — it’s about predictability. When you can confidently say your endpoints respond in under 500ms, your infrastructure becomes stable, your user experience improves, and your app scales smoother.

Start by limiting DB calls, caching smart, and trimming response size. These alone can take you a long way toward building fast, reliable APIs — even at scale.