Case Study

Golang vs Node.js: The API Gateway Benchmark

How moving from an event-driven model to goroutine-based concurrency eliminated GC pauses and reduced infrastructure costs by 83%.

12ms

P99 Latency

180MB

Memory/Instance

18K RPS

Peak Throughput

83%

Cost Reduction

01 / Context

A US-based fintech company (payment processing) operated a critical API gateway handling authentication, rate limiting, and request routing. The gateway processed 12,000 requests per second during peak hours, with bursts up to 18,000 RPS from batch reconciliation jobs.

02 / Problem

Latency Degradation

At high concurrency, P99 latency spiked from 20ms baseline to over 800ms, triggering client-side timeouts for downstream merchants.

Baseline 20ms
Peak (P99) 800ms

Memory Instability

Node.js consumed ~2.5GB RSS under load. GC cycles paused the event loop for 200–500ms, directly causing tail latency.

Memory 2.5 GB
GC Pause 200-500ms
03 / Constraints

Zero Downtime

Single point of entry. Flag-day cutover impossible.

Backward Compatibility

Same HTTP semantics, auth headers, routing rules.

Team Expertise

Proficient in Node.js, limited Go experience.

Observability

Parity with existing Datadog metrics and logs.

04 / Approach

Rejected: NGINX + Lua

Custom auth against Postgres and dynamic rate limiting would create maintenance burden.

Rejected: Node.js Optimization

Object pooling and tuning reduced P99 to 450ms but GC pauses remained fundamental.

Selected: Go (Golang)

Goroutine concurrency, low-latency GC, optimized stdlib. Trade-off: steeper learning curve.

05 / Implementation

Three Phases Over 12 Weeks

We implemented the migration in phases: sidecar proxy for baseline, endpoint-by-endpoint migration with traffic splitting, then full cutover.

Timeline

12 Weeks

Architecture

Client
Go Gateway
Postgres

Key Decision: Connection Pooling

Fixed pool of 200 DB connections vs Node.js per-request model that exhausted Postgres limits.

JWT Verification

Go's crypto/ecdsa outperformed Node.js jsonwebtoken by 4x per operation.

06 / Results

Performance

P99 Latency

450ms → 12ms

Memory

2.5GB → 180MB

Instances Required

6 → 1

Business Impact

Monthly EC2 Cost

$4,200 → $720

Peak RPS

8K → 18K

Timeout Incidents

3% → 0%

07 / Key Insight

The choice between Node.js and Go hinges on concurrency model and memory management under sustained load.

Node.js excels in I/O-heavy, low-concurrency scenarios. But when workload combines high concurrency with per-request CPU work (JWT verification, JSON parsing), the single-threaded event loop becomes a bottleneck. Go's goroutines and concurrent GC provide a more predictable performance envelope. For high-throughput API infrastructure, we now recommend Go as the default.

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