The Netflix TechBlog

MAY 4, 2023

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. This approach has a handful of benefits.

Traffic 339

Traffic Latency Tuning Systems 339

InfoQ

JULY 3, 2023

LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz

Cache 85

Cache Latency Traffic Database 85

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., We’re not told how Seer figures out that a major architectural change has happened. An equally large fraction are due to compute contention, followed by network, cache, memory, and disk contention.

Big Data 45

Big Data Cloud Performance Hardware 45

The Netflix TechBlog

OCTOBER 15, 2019

Part I: Overview Andreas Andreakis , Falguni Jhaveri , Ioannis Papapanagiotou , Mark Cho , Poorna Reddy , Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), caching (Memcached etc.),

Transportation 192

Transportation Architecture Processing Storage 192

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. With these goals in mind, two in-memory data stores, Redis and Memcached, have emerged as the top contenders.

Cache 130

Cache Storage Scalability Architecture 130

Scalegrid

FEBRUARY 8, 2024

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130