Scale
- Systems operating at 4.3M+ requests per minute
- High-throughput API paths
- Capacity and latency analysis
About Raj
The slow dependency. The unexpected traffic shape. The cache that is empty at the wrong moment. The infrastructure cost that keeps compounding.

Engineering focus
Raj Aryan is a backend software engineer with more than three years of experience building and operating high-scale distributed systems. His work centres on Golang services, event pipelines, caching, search and discovery, data systems and AWS infrastructure.
The systems span promotions, rewards, subscriptions, search, homepage, dish and location platforms—places where a small latency regression, dependency outage or inefficient data path can have a direct product and cost impact.
Working principles
Performance work starts with measurement: request shape, allocation pressure, dependency cost and query volume. Reliability work starts with failure modes: timeouts, retries, partial dependencies, capacity limits and degraded behaviour. Neither is a final polish step.
The engineering goal is a system that can explain its own behaviour, carry real traffic without fragile assumptions and make sensible choices under pressure. That is why observability, kill switches, capacity planning and cost awareness belong in the same conversation as API design.
Grounded in production
Where to next