Managing 238M Memberships at Netflix

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Netflix's Membership Team

The membership team at Netflix is responsible for signups, streaming, and managing user accounts.
They operate a dozen microservices with four nines availability and serve millions of requests per second.
Key user touchpoints include the "Start Membership" button, the "Play" button, and the account page.
Netflix's membership services manage user sign-ups, plan changes, and partner bundle activations.
All memberships are saved in Cassandra, a persistent store.

Netflix's tech footprint consists of a distributed system architecture optimized for high read RPS.
It includes over 12 microservices, gRPC for HTTP layer communication, Java and Kotlin as primary programming languages, Spring Boot for server-side development, Kafka for message passing, and Spark and Flink for offline reconciliation.
Netflix uses extensive request and response logging, dashboards, and Kibana Elastic Search to monitor and troubleshoot errors.
Distributed tracing is used to isolate and identify issues in specific microservices.
Production alerts are set up for key metrics such as latency and sign-up rate.
Machine learning models are used to detect anomalies and trigger automatic corrections or alerts.

The first case study examines the evolution of Netflix's pricing technology choices, highlighting the challenges of scaling a simple in-memory library to support global expansion, multiple plans, and various domains.
The second case study discusses the importance of cataloging every modification made to records in their systems, ensuring data integrity and enabling them to answer questions about historical changes.
The third case study focuses on the journey of scale expansion, detailing how Netflix evolved its architecture to meet increasing demands and requirements.

The member history architecture initially relied on application-level events for tracing historical state and triggering actions.
A new service was created to capture the direct delta of changes on key operational data sources using a change data capture pattern.
Member History Service tracks and persists all membership rights updates in an append-only fashion, solving the split-brain problem and enabling powerful debugging and tracing capabilities.
Member History Service replaced all app-level events with a view on top of member history, providing a single interface for all other systems within Netflix to access membership data.
Member History Service uses Iceberg tables to persist events, enabling reconciliation with core membership systems and replay of events for downstream analytics.
Member History Service helped save the day during a data corruption incident by replaying corrupted records and restoring data integrity.

Architectural choices can pay off significantly in the long run, as demonstrated by the Member History Service journey.
The evolution of subscription ecosystems requires continuous innovation and investment in architectural evolution to stay ahead of scalability challenges.
Netflix pricing choices should be future-proofed to avoid the need for reactive pivots.
Some architectural choices can pay off significantly in the long run, and it's important to have the courage to invest in big bets.
Member subscriptions evolution is an ongoing process, and there is always room for improvement and innovation.