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Why Replace External Database Caches?

DZone

Teams often consider external caches when the existing database cannot meet the required service-level agreement (SLA). However, external caches are not as simple as they are often made out to be. This is a clear performance-oriented decision.

Cache 278
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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.

Cache 246
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

The GraphQL shim enabled client engineers to move quickly onto GraphQL, figure out client-side concerns like cache normalization, experiment with different GraphQL clients, and investigate client performance without being blocked by server-side migrations. The Replay Tester tool samples raw traffic streams from Mantis.

Traffic 358
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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.

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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI. The big difference from the monolith, though, is that this is now a standalone service deployed as a separate “application” (service) in our cloud infrastructure.

Latency 243
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 260
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 238