Performance and cost-efficiency are critical concerns when it comes to building and running applications and services on a serverless architecture, such as Azure's Service Bus, Functions, and Cosmos DB. However, properly tuning these solutions can be challenging, as it requires balancing the needs of the application with the constraints and capabilities of the underlying infrastructure. In this session, we will focus on techniques for optimizing the performance of these components in order to ensure that your serverless Azure solution is running smoothly and efficiently.

In this session we will discuss how to optimize the use of Service Bus queues and topics for improved performance and cost-efficiency. Additionally, we will look at how to effectively scale Azure Functions based on workload demands, including the use of concurrency and execution limits. Finally, we will examine techniques for optimizing the performance and scalability of Cosmos DB, including the proper use of partitioning and indexing.

We will delve into the specific techniques and best practices that can be used to optimize the performance of each of these components. By following them developers and administrators can ensure that their serverless Azure solutions are running at peak performance, while also minimizing the impact on cost and resource utilization.

For Service Bus, we will include techniques such as message batching and dead lettering to improve throughput and minimize resource utilization. For Azure Functions, we will discuss strategies for optimizing cold start times and using the appropriate execution and concurrency limits to ensure that the functions are able to scale effectively. Finally, for Cosmos DB, we will explore the use of partitioning and indexing to improve query performance and minimize resource utilization.