Architecting Event-Driven Pipelines with Cosmos DB Change Feed
Learn to implement a reliable Azure Cosmos DB Change Feed pipeline. This guide covers minimal design using Azure Functions, idempotency strategies, and monitoring feed lag.
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Learn to implement a reliable Azure Cosmos DB Change Feed pipeline. This guide covers minimal design using Azure Functions, idempotency strategies, and monitoring feed lag.
Build instant, event‑driven pipelines with Cosmos DB’s Change Feed. Learn the problem, solution, a hands‑on C# example, and the trade‑offs you need to consider before you go live.
Learn how to reliably process inserts and updates from Cosmos DB using the Change Feed trigger, configure lease containers, handle deletes and schema changes, and avoid common pitfalls.
Learn how to implement event-driven synchronization using Azure Cosmos DB Change Feed, covering architecture, processor configuration, failure modes, and scaling strategies.
Cross-partition queries eating your RU budget? Cosmos DB's Change Feed lets you project writes into a second container with a different partition key — here's how the lease/checkpoint machinery works, a working Functions example, and the lag and idempotency traps to design for.
Azure Cosmos DB Change Feed provides a persistent, ordered log of inserts and updates that microservices can consume directly. This post shows how to set it up, run a sample processor, and consider its limits.
Learn how to decouple your Azure Cosmos DB writes from downstream processing using the Change Feed and Change Feed Processor (CFP) to build scalable, event-driven architectures.
Stop polling your database for updates. Learn how to use the Cosmos DB Change Feed to build event‑driven, real‑time data pipelines with a concrete Azure Functions example.
The change feed is always on for SQL API containers, so the real work is designing for per-partition ordering and at-least-once delivery. Here is a concrete Azure Functions setup and how to verify it.