Queue-Based Load Leveling Pattern (Starring Phi4 and Azure Service Bus)
Overview of the Sample Application
The sample application implements the Queue-Based Load Leveling pattern in Java, where producers generate tasks that are placed in a queue for consumers to process asynchronously. A "poison pill" mechanism ensures graceful termination of consumer threads. A real-time status dashboard updates every 500 milliseconds to display live metrics.
Installation Steps
- Clone the Repository: [Repository Link]
- Build the Project: Compiles the source code to produce an executable JAR.
Running the Application
- Start the LLM Service.
- Ensure Ollama is running.
- Launch the Application to see live metrics and a performance report.
Advancing to Azure Service Bus
Transition from in-memory queues to Azure Service Bus for enterprise-grade applications. Explore the Contoso Fiber MWA reference application using Azure Service Bus and Azure Container Apps for autoscaling based on the number of messages in the queue.
MWA Reference Application Autoscaling Email Processor
The Contoso Fiber MWA reference application uses Azure Service Bus and Azure Container Apps to autoscale the email processor based on the messages in the queue. The container app scales out when the number of messages in the Service Bus exceeds a certain threshold.
Conclusion
Integrating Azure Service Bus with queue-based load leveling enhances scalability and resilience in Java applications. Leveraging Azure Container Apps for critical operations ensures optimal performance under heavy loads. Incorporating Azure Service Bus transforms system scalability and load handling capabilities for Java projects - start now with the Modern Web App Pattern for Java.