Case Study: Payment Gateway

The challenge: Build a system that can handle 50,000 transactions per second with 99.999% reliability using .NET 8.

1. Architectural Choice: Channel-based Concurrency

We don't use a standard DB write for every request. We use **System.Threading.Channels**. The API receives the request, drops it into a high-speed in-memory channel, and returns "202 Accepted" immediately. A background worker then processes the channel and batches writes to the database.

2. Memory Management: ArrayPool and Structs

At 50k RPS, every object allocation is a liability. We use **ArrayPool** to reuse buffers for network data, and we represent our internal Payment transactions as **readonly structs** to ensure they stay on the stack. This minimizes GC pauses and keeps the p99 latency under 10ms.

3. Resiliency: The Polly Pattern

External banks go down. We use the **Polly** library to implement:

• Retry with Jitter: Wait and try again, but don't hit the bank all at once.
• Circuit Breaker: If the bank fails 5 times, stop sending requests for 30 seconds to let them recover.

4. Interview Mastery

Q: "How do you ensure 'Idempotency' in a payment system?"

Architect Answer: "We use an **Idempotency Key** (usually a GUID provided by the client). Before processing a payment, we check a Redis cache: 'Has this key been used in the last 24 hours?'. If yes, we return the *last* result without re-charging the user. This is the only way to prevent double-charges when a user clicks 'Submit' twice or their internet drops halfway through."