Building a Resilient Data Platform with Write-Ahead Log at Netflix

**Building a Resilient Data Platform with Write-Ahead Log at Netflix**

By Prudhviraj Karumanchi, Samuel Fu, Sriram Rangarajan, Vidhya Arvind, Yun Wang, John LuIntroductionNetflix operates at a massive scale, serving hundreds of millions of users with diverse content and features. Behind the scenes, ensuring data consistency, reliability, and efficient operations across various services presents a continuous challenge. At the heart of many critical functions lies the concept of a Write-Ahead Log (WAL) abstraction. At Netflix scale, every challenge gets amplified. Some of the key challenges we encountered include:Accidental data loss and data corruption in databasesSystem entropy across different datastores (e.g., writing to Cassandra and Elasticsearch)Handling updates to multiple partitions (e.g., building secondary indices on top of a NoSQL database)Data replication (in-region and across regions)Reliable retry mechanisms for real time data pipeline at scaleBulk deletes to database causing OOM on the Key-Value nodesAll the above challenges either resulted in production incidents or outages, consumed significant engineering resources, or led to bespoke solutions and technical debt...

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