As a lead architect, how would you design a solution for the problem described? Feel free to choose the best approach for this use case.

I would adopt a micro‑service architecture with a clear separation of concerns. The ingestion layer would use a message broker (Kafka or AWS Kinesis) to decouple producers from consumers, ensuring high throughput and fault tolerance. A stateless API gateway would route requests to services, while a service registry (Consul or Eureka) would enable dynamic discovery.

For data processing, I’d use a stream processing engine (Apache Flink or Spark Structured Streaming) to handle real‑time transformations and enrichments. Results would be persisted in a distributed data store (Cassandra for write‑heavy workloads or PostgreSQL for relational consistency). A caching layer (Redis) would accelerate read‑heavy queries.

Observability is critical: I’d integrate distributed tracing (Jaeger), metrics (Prometheus), and centralized logging (ELK). Auto‑scaling policies would be defined based on queue depth and CPU usage. Finally, I’d enforce CI/CD pipelines with automated tests and blue‑green deployments to minimize downtime. This design balances scalability, resilience, and maintainability for the given use case.