Client

A high-traffic digital platform experiencing frequent traffic spikes caused by mobile clients, web requests, and occasional bot or malicious behavior.

The backend system suffered from:

• Request floods

• Abusive traffic patterns

• API misuse

• Sudden spikes during peak campaigns

They needed a layered protection system combining rate limiting, traffic throttling, and intrusion mitigation.

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Project Overview

We implemented a multi-layer protection architecture using:

• NGINX rate-limiting modules

• Kong Gateway throttling plugins

• Fail2ban for bot and abusive IP blocking

• Custom token-bucket and sliding-window logic

• Redis-backed counters for distributed rate limits

• Monitoring dashboards for real-time visibility

The objective was to stabilize the API platform under heavy load while protecting backend services from abusive clients.

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Key Challenges

1. Sudden Traffic Spikes

Unexpected bursts were overwhelming application servers and database connections.

2. Lack of Abuse Detection

The existing system could not identify suspicious IPs or malicious retry loops.

3. No Unified Edge Protection

Traffic handling happened directly at application level, leading to overload.

4. Multi-Client Ecosystem

Public users, partner APIs, internal services, and automated systems all required different throttling rules.

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Our Solution

1. NGINX Rate Limiting

We implemented NGINX as the rate-control layer using:

• limit_req_zone and limit_req

• Per-IP throttling

• Separate limits for public and private APIs

• Burst control to absorb short spikes

This reduced immediate pressure on backend services.

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2. Kong API Gateway Throttling Policies

For advanced control, we configured Kong with:

• Consumer-level rate limits

• Key-based quotas

• Sliding-window counters

• Redis-backed distributed caching

• Route-specific throttle rules

This supported dynamic adjustments without redeploying services.

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3. Fail2ban for Abuse Detection and Automatic Banning

To stop malicious actors and bot attacks, we integrated Fail2ban into the traffic protection stack.

Fail2ban monitored:

• NGINX logs

• Kong Gateway logs

• Authentication failures

• Suspicious request patterns

• Excessive 4xx/5xx responses

• Repeated rate-limit violations

Actions implemented:

• Automatic temporary IP bans

• Permanent bans for repeat offenders

• Email notifications for security staff

• Log aggregation for analysis

Fail2ban served as the security firewall that blocked abusive traffic before it reached application services.

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4. Custom Throttling Logic

Some scenarios required more precise control than standard tools.
We built custom logic using:

• Token bucket algorithm

• Sliding window algorithm

• Client-type–based throttling (mobile vs. partner API vs. internal)

• Device-level request control

• Circuit breakers for overload protection

This allowed fine-grained throttling on critical endpoints.

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5. Monitoring, Metrics & Observability

We added:

• Prometheus metrics for throttle and ban events

• Grafana dashboards for traffic patterns

• Alerting on spike anomalies

• Logs for banned IPs and throttled requests

Teams gained complete visibility into API health and abuse attempts.

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Architecture Diagram (Text Version)

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Results & Impact

Stable Performance

API performance remained stable even during heavy spikes.

Backend Protection

Fail2ban significantly reduced malicious traffic before it reached the API gateway.

Lower Error Rates

Throttling and banning reduced overload-related failures.

Predictable System Load

CPU, memory, and DB load stayed within controlled thresholds.

Faster Incident Response

Centralized logs made it easy to identify abusive clients.

Scalable Protection

Rules can be tuned per IP, token, route, or client category.

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Conclusion

By implementing a combination of NGINX rate limiting, Kong Gateway throttling, Fail2ban intrusion detection, and custom throttling algorithms, we delivered a layered protection system that stabilizes API performance under high traffic and blocks malicious behavior.

The final architecture ensures:

• Controlled request flow

• Automatic detection and banning of abusive clients

• Reliable backend performance

• Protection from floods, bots, and misconfigured clients

The system is now resilient and ready to scale securely.