Categories: FAANG

Modeling Device Capabilities for Analytics

by Aarti Laddha, Richard Diaz-Cool, Rishika Idnani, Venkatesh Selveraj

Netflix supports a vast and evolving set of features and content types, ranging from 4K streaming and immersive audio to live streaming and cloud gaming, across a diverse ecosystem of devices. However, not all devices are created equal. Hardware limitations such as available RAM, CPU cores, display capabilities, or platform support mean that some features cannot be supported on certain device models. To ensure the best possible user experience, we rely on a deep understanding of device capabilities. We have invested in building a comprehensive device capability data model and integrating feature flags from internal systems, paving the way for smarter, more granular feature management across our global device landscape. This approach helps us identify bottlenecks in feature penetration and accelerates the pace of innovation.

We have designed our data storage and modeling strategies to efficiently support analytics at scale. We use a cumulative table to process information about the device’s capabilities. This table is structured to efficiently capture the latest state of each device and its associated capabilities (like Screen resolutions, Video Profiles Supported, Surround Sound, RAM size etc) making it ideal for analytics and reporting use cases.

{
"Screen Height": ["720"],
"Screen Width": ["1280"],
"Video Profiles":
[
"playready",
"hevc",
],
}

For aggregate analytics, we leverage a histogram table that captures active device counts over the past 28 days, broken down by device model and software version. This table also records the number of devices supporting specific capabilities, enabling detailed distribution analysis. One use case for this histogram data is to analyze the distribution of external display capabilities attached to streaming sticks. For example, the histogram below shows that out of total X number of devices, all supported the HD profile (playready), while only 20% devices supported the UHD profile (hevc).

{
"Video Profiles": {
"playready": 100%, # HD profile
"hevc": 20% # UHD profile
}
}

We have built analytical products that leverage these datasets to provide a comprehensive view of feature reach such as 4K Ultra HD, Netflix Spatial Audio, Cloud Gaming and the latest UI. By relying on data-driven insights, we can make informed decisions about which features to enable on specific devices, ensuring both performance and reliability.


Modeling Device Capabilities for Analytics was originally published in Netflix TechBlog on Medium, where people are continuing the conversation by highlighting and responding to this story.

AI Generated Robotic Content

Recent Posts

Context Managers Beyond Opening Files in Python

The stopwatch in the opening script is the smallest case of the pattern.

14 hours ago

AWS named a Leader in the 2026 Gartner Magic Quadrant for Contact Center as a Service

I’m proud to share that Amazon Web Services (AWS) has been named a Leader in…

14 hours ago

Scale agents securely with IAM Helper Agent Skills and MCP Tools

As organizations adopt autonomous agents to build applications, securing identities and access has become more…

14 hours ago

Anthropic Says It Will Revolutionize Biology—Some Day

In breathless press releases and posts, the company has touted its models’ ability to deliver…

15 hours ago

New neural framework could make LLMs more empathetic

As more people turn to large language models (LLMs) during personal crises, the companies behind…

15 hours ago

Robust Serialization with JSON and Custom Types

In this article, you will learn how to build a robust JSON serialization pipeline in…

2 days ago