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Messaging Patterns and Guidance

Messaging

The distributed nature of cloud applications requires a messaging infrastructure that connects the components and services, ideally in a loosely coupled manner in order to maximize scalability. Asynchronous messaging is widely used, and provides many benefits, but also brings challenges such as the ordering of messages, poison message management, idempotency, and more.

The following patterns and guidance topics are related to messaging in cloud-hosted applications.

Competing Consumers Pattern

MessagingPerformance & ScalabilityDesign PatternsDownload code sampleShow All

Enable multiple concurrent consumers to process messages received on the same messaging channel. This pattern enables a system to process multiple messages concurrently to optimize throughput, to improve scalability and availability, and to balance the workload.

Competing Consumers Pattern

For more info, see the Competing Consumers Pattern.

Pipes and Filters Pattern

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Decompose a task that performs complex processing into a series of discrete elements that can be reused. This pattern can improve performance, scalability, and reusability by allowing task elements that perform the processing to be deployed and scaled independently.

Pipes and Filters Pattern

For more info, see the Pipes and Filters Pattern.

Priority Queue Pattern

MessagingPerformance & ScalabilityDesign PatternsDownload code sampleShow All

Prioritize requests sent to services so that requests with a higher priority are received and processed more quickly than those of a lower priority. This pattern is useful in applications that offer different service level guarantees to individual types of client.

Priority Queue Pattern

For more info, see the Priority Queue Pattern.

Queue-based Load Leveling Pattern

MessagingAvailabilityPerformance & ScalabilityDesign PatternsShow All

Use a queue that acts as a buffer between a task and a service that it invokes in order to smooth intermittent heavy loads that may otherwise cause the service to fail or the task to timeout. This pattern can help to minimize the impact of peaks in demand on availability and responsiveness for both the task and the service.

Queue-based Load Leveling Pattern

For more info, see the Queue-based Load Leveling Pattern.

Scheduler Agent Supervisor Pattern

MessagingResiliencyDesign PatternsShow All

Coordinate a set of actions across a distributed set of services and other remote resources, attempt to transparently handle faults if any of these actions fail, or undo the effects of the work performed if the system cannot recover from a fault. This pattern can add resiliency to a distributed system by enabling it to recover and retry actions that fail due to transient exceptions, long-lasting faults, and process failures.

Scheduler Agent Supervisor Pattern

For more info, see the Scheduler Agent Supervisor Pattern.

Asynchronous Messaging Primer

MessagingCloud Guidance and PrimersShow All

Messaging is a key strategy employed in many distributed environments such as the cloud. It enables applications and services to communicate and cooperate, and can help to build scalable and resilient solutions. Messaging supports asynchronous operations, enabling you to decouple a process that consumes a service from the process that implements the service.

For more info, see the Asynchronous Messaging Primer.

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