"Distributed counting is a challenging problem in computer science. At Netflix, our counting use cases include tracking millions of user interactions and monitoring how often specific features or experiences are shown to users."
"The system balances performance, accuracy, and cost through configurable counting modes, resilient data aggregation, and a globally distributed architecture, ensuring optimal handling of diverse counting requirements."
"Some counting use cases demand 'best-effort counting', prioritizing low latency and minimal infrastructure costs over absolute accuracy, while others require 'eventually consistent counting' for precise and durable counts with a slight delay."
"Each counting action is logged as an immutable event in the TimeSeries abstraction along with an idempotency key, ensuring durability and enabling idempotent retries to enhance reliability in counting mechanisms."
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