Optimize Network and Resource Usage
To improve API performance and reduce latency, implement Gzip compression for JSON payloads. Because JSON is highly repetitive, compression can reduce payload sizes by 60–80%. Most frameworks offer middleware for this, but if your server is CPU-bound, offload compression to a reverse proxy like Nginx or an AWS ALB. Additionally, protect your system from hanging external services by setting explicit timeouts on all outbound network calls. Using AbortController or library-specific defaults (e.g., axios.defaults.timeout) prevents a single slow third-party API from consuming all your worker threads or connection slots.
Manage Database and Secret Lifecycle
Database connection pools often fail under load because they lack hard caps and idle management. Configure your database client to enforce a max connection limit, set an idleTimeoutMillis to reclaim memory, and—crucially—implement a statement_timeout to kill runaway queries that would otherwise hold connections indefinitely.
For managing secrets, avoid the binary choice of startup-only fetching (which requires redeploys for rotation) or per-request fetching (which adds latency and cost). Instead, use a stale-while-revalidate cache in memory. This allows the application to serve secrets instantly while refreshing them in the background as they approach their TTL, ensuring seamless rotation without downtime or extra network overhead.
Implement Tiered Rate Limiting
Application-level rate limiting is essential to prevent accidental hammering or malicious scraping. Rather than a single global rule, apply tiered limits:
- Global baseline: A general limit for standard API traffic.
- Strict auth limits: Tight constraints (e.g., 10 attempts per 15 minutes) to mitigate brute-force and credential stuffing.
- Resource-intensive limits: Specific caps on endpoints like
/uploadto prevent storage and I/O abuse.
When deploying across multiple instances, ensure your rate limiter uses a shared store like Redis; otherwise, attackers can bypass limits by spreading requests across your server fleet.