API Gateway Modernization for High-Traffic Platform

Replaced legacy API gateway with Kong and Envoy, achieving 10x throughput improvement, sub-10ms latency, and enabling advanced traffic management capabilities.

[Overview] System Overview

A digital media company serving 50M daily active users needed to modernize their API infrastructure. The legacy custom-built gateway was a bottleneck-maxing out at 10K requests/second and adding 100ms+ latency.

We designed and implemented a modern API gateway architecture using Kong for edge traffic management and Envoy sidecars for service-to-service communication. The new platform handles 100K requests/second with sub-10ms p99 latency.

Beyond raw performance, the modernization enabled capabilities previously impossible: canary deployments, A/B testing at the API level, and sophisticated rate limiting per customer tier.

[Context] Situation before

The API gateway was built in-house 5 years ago when traffic was 1/20th of current levels. It was a Java-based reverse proxy with custom authentication and routing logic.

##### Performance Ceiling

The gateway maxed out at 10K requests/second with 12 instances. Adding more instances did not help-shared state became the bottleneck.

P99 latency was 150ms. The gateway added more latency than most backend services.

During traffic spikes, the gateway became the failure point. Backend services could handle the load; the gateway could not.

##### Feature Limitations

Routing was static-configured at deploy time. A/B testing required application-level logic.

Rate limiting was primitive-global limits only, no per-customer tiering.

Authentication was synchronous and slow. JWT validation added 20ms to every request.

[Diagnosis] The real problem

The surface problem was performance. The obvious solution was optimization or horizontal scaling.

But the architectural foundation was wrong. The gateway was designed as a stateful service. Session data, rate limit counters, and routing tables were in-process memory.

No amount of optimization would fundamentally change the architecture. The system needed to be rebuilt around stateless processing with distributed state management.

Understanding the root cause changed everything.

[Boundaries] Working constraints

API gateway replacement must not disrupt production traffic.

OPERATIONAL

  • Zero-downtime migration
  • Must support gradual traffic shift
  • Existing API contracts must not change

COST

  • New infrastructure must not exceed current costs
  • Cannot license expensive commercial gateways
  • Open source preferred

TEAM

  • Platform team of 8
  • Limited experience with service mesh
  • Must maintain parallel support during transition

MIGRATION

  • Custom authentication must be preserved
  • Logging and monitoring integration required
  • 50+ internal services depend on gateway

IMMUTABLE

  • AWS deployment
  • Kubernetes orchestration
  • gRPC and REST support required

Constraints are features, not obstacles. They guide design decisions.

[Decisions] Key tradeoffs

API gateway architecture balanced performance, features, and operational complexity.

REJECTED

Optimize Existing Gateway

Performance tuning and horizontal scaling

Architectural limits cannot be optimized away. Would delay inevitable replacement.

REJECTED

AWS API Gateway

Managed service with auto-scaling

Latency higher than requirements. Limited customization. Expensive at high volume. Lambda cold starts for auth.

CHOSEN

Kong + Envoy

Kong for edge, Envoy sidecars for mesh

Open source with enterprise support available. High performance. Extensible plugin system. Strong Kubernetes integration.

[Design] Architecture design

The architecture uses Kong as the edge gateway handling external traffic, authentication, and rate limiting. Envoy sidecars provide service mesh capabilities for internal communication.

Kong plugins handle JWT validation (cached), rate limiting (Redis-backed), and request transformation. Declarative configuration enables GitOps deployment.

Envoy sidecars provide circuit breaking, retry logic, and observability for service-to-service calls. The data plane is fully decoupled from the control plane.

[Approach] Execution model

Migration used a shadow traffic pattern: new gateway received duplicate traffic without affecting users.

Month 1: Kong deployment with shadow traffic. Validate routing, auth, and rate limiting.

Month 2: Envoy sidecar rollout to internal services. Gradual mesh adoption.

Month 3: Production cutover. 10%→50%→100% traffic shift with automatic rollback.

[Results] Measurable outcomes

Throughput increased from 10K to 100K requests/second-10x improvement.

P99 latency reduced from 150ms to 8ms. Gateway overhead became negligible.

New capabilities enabled: canary deployments, A/B testing, per-customer rate limits.

Operational simplicity improved. Declarative configuration replaced manual procedures.

Key improvements achieved:

  • System handles 10x burst load without degradation
  • Delivery latency reduced from seconds to milliseconds
  • Zero message loss during traffic spikes
  • Operational complexity reduced by 60%

[Anti-patterns] What could have gone wrong

The legacy gateway would have continued limiting growth. Traffic spikes would cause user-facing outages.

Feature requests (canary deploys, A/B testing) would require extensive custom development.

Latency would continue degrading as traffic grew. User experience would suffer.

  • Over-engineering the initial solution
  • Ignoring operational constraints during design
  • Premature optimization without load testing
  • Skipping failure mode analysis

[Applicability] Where this pattern applies

API gateway modernization applies to any platform outgrowing its current infrastructure.

Kong + Envoy is particularly well-suited for Kubernetes environments with microservices.

Organizations with simpler requirements might consider managed services like AWS API Gateway.

Every system is different. Context always matters.