How do you optimize performance and scalability of Azure Service Bus workloads?

Optimizing Azure Service Bus performance and scalability requires tuning message throughput, reducing processing overhead, scaling consumers correctly, and choosing the appropriate Service Bus tier and architecture patterns. Key techniques include batching messages, using asynchronous processing, controlling concurrency, partitioning workloads, minimizing message size, configuring retries properly, and monitoring throughput, latency, and resource utilization. The goal is to maximize throughput while maintaining reliability, ordering requirements, and acceptable latency.

Azure Service Bus is designed for enterprise messaging workloads, but performance depends heavily on how producers, consumers, message entities, and infrastructure are configured. A poorly designed messaging system can suffer from high latency, message lock expiration, throttling, excessive retries, or inefficient resource usage.

A scalable architecture usually follows this model:…