Build a Webhook Ingestion Service Using Queue-Based Load Leveling in Azure

When a webhook endpoint is hit by a burst of traffic, a synchronous processing chain can quickly become overwhelmed: requests pile up, timeouts cascade, and data gets lost. The queue-based load leveling pattern solves this by placing a message queue between the producer and consumer, so the queue absorbs traffic spikes while the consumer processes messages steadily at its own pace.

In this lab, you will build a complete webhook ingestion pipeline on Azure using this pattern and put it under pressure with a burst of simulated traffic, observing how the system stays fast and reliable under load.

Objectives

By completing this Intermediate lab, you will be able to:

• Create an HTTP-triggered Azure Function that validates incoming webhook payloads and enqueues them to an Azure Storage Queue
• Implement a queue-triggered Azure Function that processes messages and writes results to Azure Cosmos DB using output bindings
• Simulate burst webhook traffic and observe how the Storage Queue buffers messages to protect the downstream consumer
• Analyze the queue-based load leveling pattern's behavior in Application Insights Live Metrics

Who is this lab for?

This lab is designed for:

• Cloud engineers and backend developers building resilient webhook pipelines for unpredictable traffic patterns
• Solutions architects who want hands-on experience with the queue-based load leveling pattern using Azure services