How to design a scalable, observable financial system for emerging markets.

The BRICS Opportunity

"While BRICS nations drive 45% of global remittances, their financial systems face unique technical challenges. As a multilingual engineer (RU/EN/FR/NL), I'm developing open-source solutions to bridge these gaps."

Core Architecture Decisions

Why Golang + NATS JetStream?

Key Requirements:

• Cost efficiency: Affordable for startups and scale-ups
• Predictable latency: Crucial for arbitrage-sensitive markets

Implementation:

func (s *server) Convert(ctx context.Context, req *pb.ConvertRequest) (*pb.ConvertResponse, error) {
  // 1. Validate idempotency key
  // 2. Thread-safe rate lookup 
  // 3. Async event publishing
  s.js.PublishAsync("transactions.currency", event, 
    nats.MsgId(req.IdempotencyKey)
  )
}

Key Decisions:

1. gRPC for Conversions: Binary protocol beats JSON for high-frequency ops
2. JetStream Persistence: Guaranteed delivery during market volatility
3. Async Processing: Decouples conversion logic from event streaming

Performance Outcome:

✅ 45,743 RPS sustained on single node (consumer hardware)

Design Insight:

"Inspired by India's UPI requirements for sub-500ms settlements, our architecture prioritizes deterministic latency through Go's channels and JetStream's streamlined persistence."

Critical Reliability Features

Idempotent Event Processing

Challenge: Network retries can cause duplicate conversions

Solution:

1. Idempotency Keys:

s.js.PublishAsync("transactions.currency",
  []byte(event),
  nats.MsgId(req.IdempotencyKey),
  nats.ExpectStream("TRANSACTIONS"),
)

1. Stream Configuration:

_, err := js.AddStream(&nats.StreamConfig{
  Name:        "TRANSACTIONS",
  Description: "BRICS currency conversion events",
  Subjects:    []string{"transactions.>"},
  Retention:   nats.InterestPolicy,
  MaxAge:      24 * time.Hour,
  Duplicates:  24 * time.Hour, // Matches Brazilian audit rules
  Storage:     nats.FileStorage,
  Replicas:    1,
})

"Duplicate transactions in RUB/CNY conversions could mean significant losses. Our approach combines client-supplied ids with JetStream's deduplication window."

Performance Engineering

Benchmarking Under BRICS Conditions

Test Simulation:

func TestPerfConversionRPS(t *testing.T) {
  // 500 concurrent workers
  // 12-second sustained load
  // Dynamic idempotency keys
}

Results:

=== RUN   TestPerfConversionRPS
    server_performance_test.go:89: Successful conversions: 548,922  
    server_performance_test.go:94: ✅ 45,743 RPS (Exceeds 30K target)

Optimization Techniques:

1. Zero-Copy Serialization: Protocol Buffers over JSON
2. Lock Granularity: sync.RWMutex for concurrent rate access
3. Connection Pooling: gRPC keep-alives
4. Async I/O: Non-blocking JetStream publishing

Forward Momentum

Current Focus Areas

• Real Time Monitoring with Prometheus and Grafana
• Central Bank Integrations

Community Participation

Want to help? We'd love PRs for:

• Currency modules
• Real-world load testing

Get Involved

1. ⭐ github.com/TheBricsHub/brics-currency-exchange
2. 💬 Open issues with your BRICS payment experience
3. 🛠️ Submit PRs

Coming in Part 2: Monitoring currency volatility with Prometheus and Grafana