Serverless Architecture: AWS Lambda at Scale
How we handle 10M requests/day with AWS Lambda while keeping costs under $500/month. Optimization strategies for serverless computing.
Traditional servers idle 80% of the time. You're paying for capacity you don't use.
AWS Lambda: Pay only for compute time. $0.20 per 1M requests.
Our CloudSync Pro handles 10 million requests/day for $420/month.
Why Serverless?
Traditional server (EC2 t3.large):
- Cost: $60/month
- Capacity: ~1,000 requests/second
- Idle cost: $60/month even at 0 traffic
Lambda:
- Cost: $0 at 0 traffic
- Scales instantly to 10,000 concurrent executions
- Pay per request
Architecture
API Gateway
→ Lambda (authentication)
→ Lambda (business logic)
→ RDS Proxy (connection pooling)
→ PostgreSQL
Cost Optimization Strategies
1. Right-Size Memory
More memory = faster execution = cheaper total cost.
Test:
- 128 MB: 800ms execution, $0.000000208/request
- 512 MB: 200ms execution, $0.000000104/request
Cheaper with more memory!
2. Reuse Connections
// BAD: New DB connection every request
exports.handler = async (event) => {
const db = await connectDB();
// ...
};
// GOOD: Reuse connection
let db;
exports.handler = async (event) => {
if (!db) db = await connectDB();
// ...
};
3. Batch Processing
Process 100 records at once instead of 100 individual invocations.
Real Metrics
- 10M requests/day
- Average execution: 180ms
- Memory: 512 MB
- Cost: $420/month
Conclusion: Serverless works at scale when optimized correctly.
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Written by AJ Patatanian
Senior full-stack engineer with expertise in React Native, AI/ML, and cloud architecture. Building production apps at SERA Industries.
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