Remove Cache Remove Efficiency Remove Traffic
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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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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Our goal was to build a versatile and efficient data storage solution that could handle a wide variety of use cases, ranging from the simplest hashmaps to more complex data structures, all while ensuring high availability, tunable consistency, and low latency. Developers just provide their data problem rather than a database solution!

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Improving our video encodes for legacy devices

The Netflix TechBlog

and thus fall back to less efficient encode families. Since then, we have applied innovations such as shot-based encoding and newer codecs to deploy more efficient encode families. 264/AVC Main profile family still represents a substantial portion of the members viewing hours and an even larger portion of the traffic.

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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.

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Key Advantages of DBMS for Efficient Data Management

Scalegrid

Enhanced data security, better data integrity, and efficient access to information. Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity.

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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Building on these foundational abstractions, we developed the TimeSeries Abstraction  — a versatile and scalable solution designed to efficiently store and query large volumes of temporal event data with low millisecond latencies, all in a cost-effective manner across various use cases. Let’s dive into the various aspects of this abstraction.

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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. Looking at our high traffic UI screens (like the homepage) allowed us to identify any regressions caused by the endpoint before we enabled it for all our users.

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