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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Concatenating our files on the server: Are we going to send many smaller files, or are we going to send one monolithic file? Caching them at the other end: How long should we cache files on a user’s device? Caching them at the other end: How long should we cache files on a user’s device? That’s almost 22× more!

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Optimising for High Latency Environments

CSS Wizardry

This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. Round-trip-time (RTT) is basically a measure of latency—how long did it take to get from one endpoint to another and back again? What is RTT? RTT isn’t a you-thing, it’s a them-thing.

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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. We started seeing increased response latencies and leader servers running at dangerously high utilization.

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Single-core memory bandwidth: Latency, Bandwidth, and Concurrency

John McCalpin

The Multicore Era Over the past ~15 years, server processors from Intel and AMD have evolved from the early quad-core processors to the current monsters with over 50 cores per socket. The example below is for a 2005-era processor with 60 ns memory latency and 6.4 Units of nanoseconds (ns) are most convenient.

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Time To First Byte: Beyond Server Response Time

Smashing Magazine

Time To First Byte: Beyond Server Response Time Time To First Byte: Beyond Server Response Time Matt Zeunert 2025-02-12T17:00:00+00:00 2025-02-13T01:34:15+00:00 This article is sponsored by DebugBear Loading your website HTML quickly has a big impact on visitor experience. TCP: Establishing a reliable connection to the server.

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