Abstract
What does it take to safely delete data at Netflix scale? In large-scale systems, data deletion cuts across infrastructure, reliability, and performance complexities. Data lives in many datastores, each with different trade-offs and requiring ad-hoc solutions, leaving users with fragmented behavior, inconsistent outcomes, and costly operational overload. As data volumes grow and data stores become increasingly distributed and complex, ensuring safe deletion becomes an even greater challenge. Without a centralized architecture, teams often develop isolated solutions, resulting in inconsistent practices, duplicated effort, and growing operational overhead.
At Netflix, we have developed an architecture for managing data deletion across diverse data stores, addressing these challenges while improving overall system resilience. The centralized and extensible platform provides the end-to-end data deletion lifecycle from identifying the data to verifying and executing deletion. The platform includes configurable deletion controls, journaling, observability, and data recoverability to ensure safe and reliable operation.
In this talk, we share the design and execution tradeoffs behind the data deletion platform. We explain how we have used various techniques to build a reliable and auditable deletion system, and we highlight key engineering tradeoffs, including how we balance throughput, safety, and scalability across diverse systems while maintaining resilience under live traffic.
Key Takeaways:
- Understand the architectural challenges of data deletion and why a centralized approach is essential.
- Learn how orchestration, observability, journaling, and recoverability enable safe deletion across diverse data stores.
- Explore the tradeoffs Netflix made to balance throughput, safety, and scalability under live traffic.
- Gain practical insights from real-world engineering decisions in building and operating large-scale deletion workflows.
Speaker
Vidhya Arvind
Tech Lead & a Founding Architect for the Data Abstraction Platform @Netflix, Previously @Box and @Verizon
Vidhya Arvind is a Tech Lead at Netflix and a founding architect of Netflix’s cutting-edge data abstraction platform. She is a recognized expert in designing and delivering scalable, high-impact data abstractions that empower thousands of developers across the organization to move faster with confidence. With expertise in crafting robust APIs and high-performance abstractions, Vidhya drives the seamless operation of complex abstractions at massive scale. She is known for her strategic thinking, curiosity, and a systems-level mindset that fuels her passion for debugging, innovating, and solving deeply technical challenges. Vidhya has played a pivotal role in shaping the evolution of Netflix's data infrastructure, enabling mission-critical systems to run with exceptional efficiency, reliability, and resilience. Vidhya lives in the Bay Area with her family and loves hiking on trails in the area.
Find Vidhya Arvind at:
Speaker
Shawn Liu
Senior Software Engineer @Netflix, Building Reliable and Extensible Systems for Consumer Data Lifecycle at Scale
Shawn Liu is a senior software engineer at Netflix, where he builds highly available consumer identity systems and manages account and profile lifecycles at massive scale. With diverse experience in distributed systems, event-driven architectures, and high-throughput data pipelines, Shawn shapes the company-wide data lifecycle architecture, standardizing interfaces and safeguards across services and data stores. His recent work focuses on building and operationalizing a centralized, extensible deletion architecture designed for reliability and resilience at global scale.
Find Shawn Liu at:
Date
Monday Nov 17 / 01:35PM PST ( 50 minutes )
Location
Ballroom A
