The Netflix TechBlog

SEPTEMBER 18, 2024

Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination.

Latency 260

Latency Storage Cache Servers 260

The Netflix TechBlog

FEBRUARY 14, 2025

Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. This nuanced integration of data and technology empowers us to offer bespoke content recommendations.

Tuning 166

Tuning Latency Efficiency Storage 166

John McCalpin

FEBRUARY 17, 2025

In my previous post , I reviewed historical data on single-core/single-thread memory bandwidth in multicore processors from Intel and AMD from 2010 to the present. “Concurrency” is the amount of data that must be “in flight” between the core and the memory in order to maintain a steady-state system.

Latency 71

Latency Hardware Cache Systems 71

The Netflix TechBlog

MARCH 7, 2023

These media focused machine learning algorithms as well as other teams generate a lot of data from the media files, which we described in our previous blog , are stored as annotations in Marken. But we cannot search or present low latency retrievals from files Etc. Marken Architecture Marken’s architecture diagram is as follows.

Media 272

Media Latency Architecture Database 272

Dynatrace

MAY 23, 2024

The jobs executing such workloads are usually required to operate indefinitely on unbounded streams of continuous data and exhibit heterogeneous modes of failure as they run over long periods. This significantly increases event latency. Performance is usually a primary concern when using stream processing frameworks.

Engineering 245

Engineering Tuning Latency Open Source 245

The Netflix TechBlog

OCTOBER 8, 2024

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 239

Latency Storage Traffic Tuning 239

Dynatrace

OCTOBER 3, 2024

Considering the latest State of Observability 2024 report, it’s evident that multicloud environments not only come with an explosion of data beyond humans’ ability to manage it. It’s increasingly difficult to ingest, manage, store, and sort through this amount of data. You can find the list of use cases here.

Performance 290

Performance Architecture Innovation Latency 290

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 252

Latency Storage Big Data Tuning 252

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 257

Big Data Government Processing Analytics 257

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse?

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

The Netflix TechBlog

NOVEMBER 3, 2023

Democratizing Stream Processing @ Netflix By Guil Pires , Mark Cho , Mingliang Liu , Sujay Jain Data powers much of what we do at Netflix. On the Data Platform team, we build the infrastructure used across the company to process data at scale. The existing Data Mesh Processors have a lot of overlap with SQL.

Processing 271

Processing Engineering Infrastructure Latency 271

The Netflix TechBlog

SEPTEMBER 29, 2022

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Latency 221

Latency Systems Media Serverless 221

Scalegrid

FEBRUARY 24, 2025

Youll also learn strategies for maintaining data safety and managing node failures so your RabbitMQ setup is always up to the task. Implementing clustering and quorum queues in RabbitMQ significantly improves load distribution and data redundancy, ensuring high availability and fault tolerance for messaging services.

Best Practices 147

Best Practices Traffic Strategy Efficiency 147

The Netflix TechBlog

JANUARY 25, 2023

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. But there are more interesting cases where users want to store temporal (time-based) data or spatial data. Movie Entity with id 1234 has violence.

Scalability 291

Scalability Latency Media Architecture 291

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 212

Storage Latency Efficiency Data Engineering 212

DZone

FEBRUARY 27, 2024

Caching is a critical technique for optimizing application performance by temporarily storing frequently accessed data, allowing for faster retrieval during subsequent requests. Multi-layered caching involves using multiple levels of cache to store and retrieve data.

Cache 173

Cache Efficiency Architecture Design 173

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 347

Traffic Latency Tuning Systems 347

Uber Engineering

OCTOBER 17, 2018

To accomplish this, Uber relies heavily on making data-driven decisions at every level, from forecasting rider demand during high traffic events to identifying and addressing bottlenecks … The post Uber’s Big Data Platform: 100+ Petabytes with Minute Latency appeared first on Uber Engineering Blog.

Big Data 109

Big Data Latency Transportation Traffic 109

Dynatrace

DECEMBER 27, 2022

As more organizations embrace microservices-based architecture to deliver goods and services digitally, maintaining customer satisfaction has become exponentially more challenging. First, it helps to understand that applications and all the services and infrastructure that support them generate telemetry data based on traffic from real users.

Software 306

Software Software Benchmarking Latency 306

Dynatrace

APRIL 10, 2025

Integrating data at an OS-agnostic cluster level is another hurdle, often leading to data silos and incomplete visibility. While this hybrid architectural approach offers flexibility, it also introduces the need for unified observability.

Performance 147

Performance Java Operating System Infrastructure 147

Scalegrid

JUNE 4, 2020

Compare Latency. lower latency compared to DigitalOcean for PostgreSQL. Now, let’s take a look at the throughput and latency performance of our comparison. Next, we are going to test and compare the latency performance between ScaleGrid and DigitalOcean for PostgreSQL. PostgreSQL DigitalOcean Latency Averages (ms).

Database 230

Database Latency Benchmarking Performance 230

VoltDB

DECEMBER 11, 2024

Edge computing has transformed how businesses and industries process and manage data. By bringing computation closer to the data source, edge-based deployments reduce latency, enhance real-time capabilities, and optimize network bandwidth. Data interception during transit. Redundancy and inefficiency in data aggregation.

IoT 52

IoT Energy Logistics Latency 52

The Netflix TechBlog

DECEMBER 17, 2019

Andreas Andreakis , Ioannis Papapanagiotou Overview Change-Data-Capture (CDC) allows capturing committed changes from a database in real-time and propagating those changes to downstream consumers [1][2]. Requirements In a previous blog post, we discussed Delta , a data enrichment and synchronization platform.

Database 221

Database Traffic Transportation Open Source 221

Dynatrace

NOVEMBER 10, 2022

As companies accelerate digital transformation, cloud services such as AWS Lambda help companies to modernize their application architectures to quickly adapt to the needs of their customers while offloading the operational complexity to their cloud vendor. The need for a simplified approach to capture telemetry.

Lambda 246

Lambda Serverless AWS Latency 246

Dynatrace

OCTOBER 1, 2021

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT. Dynatrace news.

Metrics 363

Metrics Open Source Monitoring Cloud 363

High Scalability

JANUARY 11, 2022

Architecture. from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. High Level Design.

Design 334

Design Media Storage Logistics 334

The Netflix TechBlog

NOVEMBER 3, 2022

The original assumptions and architectural choices were no longer viable. 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. Titus Gateway handles user requests.

Cache 233

Cache Latency Traffic Systems 233

The Netflix TechBlog

DECEMBER 17, 2019

Andreas Andreakis , Ioannis Papapanagiotou Overview Change-Data-Capture (CDC) allows capturing committed changes from a database in real-time and propagating those changes to downstream consumers [1][2]. Requirements In a previous blog post, we discussed Delta , a data enrichment and synchronization platform.

Database 206

Database Traffic Transportation Open Source 206

The Netflix TechBlog

SEPTEMBER 24, 2021

As described by the white paper Apple ProRes ( link ), the target data rate of the Apple ProRes HQ for 1920x1080 at 29.97 Table 1: Movie and File Size Examples Initial Architecture A simplified view of our initial cloud video processing pipeline is illustrated in the following diagram. is 220 Mbps.

Cloud 242

Cloud Media Storage Cache 242

Dynatrace

MAY 13, 2022

Because of its scalability and distributed architecture, thousands of companies trust it to run their cloud and hybrid-based workloads at high availability without compromising performance. From there, you can dive deeper into infrastructure metrics (cluster, datacenter, racks, and nodes) and data metrics (keyspaces and tables).

Azure 246

Azure Latency Metrics Infrastructure 246

Dynatrace

MAY 19, 2022

Example 1: Architecture boundaries. Due to the massive amount of data, no one knew what action to take if a number went red. First, they took a big step back and looked at their end-to-end architecture (Figure 2). SLO dashboard defined by architectural boundary. The “Four Golden Signals” include the following: Latency.

Automotive 290

Automotive Latency Architecture Azure 290

Dynatrace

JANUARY 26, 2021

Within this paradigm, it is possible to run entire architectures without touching a traditional virtual server, either locally or in the cloud. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently. When an application is triggered, it can cause latency as the application starts.

Serverless 246

Serverless Efficiency Lambda Azure 246

Dynatrace

OCTOBER 10, 2022

Reduced latency. Serverless architecture makes it possible to host code anywhere, rather than relying on an origin server. By using cloud providers with multiple server sites, organizations can reduce function latency for end users. Architectural complexity. Optimizes resources. Difficult to monitor.

Serverless 241

Serverless Infrastructure Lambda Latency 241

Dynatrace

JANUARY 31, 2024

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. It also shows how data observability relates to business outcomes as organizations embrace generative AI. GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues.

Cache 276

Cache Azure Infrastructure Monitoring 276

The Netflix TechBlog

SEPTEMBER 8, 2020

This allowed Android engineers to have much more control and observability over how we get our data. Background The Netflix Android app uses the falcor data model and query protocol. For example, the artwork service is separate from the video metadata service, but we need the data from both in the detail key. It was a Node.js

Latency 241

Latency Cache Java Traffic 241

The Netflix TechBlog

APRIL 27, 2023

Atlas is an in-memory time-series database that ingests multiple billions of time-series per day and retains the last two weeks of data. Moreover, common database optimizations like caching recently queried data don’t really work for alerting queries because, generally speaking, the last received datapoint is required for correctness.

Storage 297

Storage Cache Metrics Database 297

The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case. divide the input video into small chunks 2.

Processing 238

Processing Media Latency Innovation 238