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

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? How does a data lakehouse work?

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

Dynatrace

SEPTEMBER 23, 2020

Recent improvements in OneAgent runtime-data handling. Storage mount points in a system might be larger or smaller, local or remote, with high or low latency, and various speeds. Starting with OneAgent version 1.199, the runtime folder is configurable and consequently you can retain your storage mount point setup as-is.

Storage 227

Storage Latency Operating System Network 227

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. in a video file. This is obviously very expensive.

Media 272

Media Latency Architecture Database 272

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

Dynatrace

JUNE 25, 2020

The network latency between cluster nodes should be around 10 ms or less. With Dynatrace actively managing business-critical applications, some of our globally distributed enterprise customers require Dynatrace Managed to continue operating even when an entire data center goes down. Minimized cross-data center network traffic.

Availability 264

Availability Hardware Latency Traffic 264

Dynatrace

AUGUST 20, 2024

Driven by that value, Dynatrace brings real-time observability, security, and business data into context and makes sense of it so our customers can get answers, automate, predict, and prevent. Executives are sitting on a goldmine of data, and they don’t know it. Common business analytics incur too much latency.

Analytics 285

Analytics Latency Processing Systems 285

High Scalability

JANUARY 11, 2022

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. Data Models. Graph Data Models.

Design 334

Design Media Storage Logistics 334

The Netflix TechBlog

DECEMBER 17, 2024

The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? This allows us to focus on data analysis and problem-solving rather than managing complex systemchanges.

Traffic 172

Traffic Scalability Strategy Monitoring 172

Scalegrid

APRIL 28, 2020

Since database hosting is more dependent on memory (RAM) than storage, we are going to compare various instance sizes ranging from just 1GB of RAM up to 64GB of RAM so you can see how costs vary across different application workloads. Does it affect latency? Yes, you can see an increase in latency. EC2 instances. VM instances.

Azure 344

Azure AWS Database Latency 344

DZone

NOVEMBER 25, 2023

We often dwell on the technical aspects of database selection, focusing on performance metrics , storage capacity, and querying capabilities. Factors like read and write speed, latency, and data distribution methods are essential. In a detailed article, we've discussed how to align a NoSQL database with specific business needs.

Database 278

Database Latency Speed Metrics 278

Scalegrid

JUNE 4, 2020

Compare Latency. lower latency compared to DigitalOcean for PostgreSQL. On average, ScaleGrid provides over 30% more storage vs. DigitalOcean for PostgreSQL at the same affordable price. Now, let’s take a look at the throughput and latency performance of our comparison. PostgreSQL DigitalOcean Latency Averages (ms).

Database 230

Database Latency Benchmarking Performance 230

Dynatrace

JANUARY 31, 2024

I have ingested important custom data into Dynatrace, critical to running my applications and making accurate business decisions… but can I trust the accuracy and reliability?” ” Welcome to the world of data observability. At its core, data observability is about ensuring the availability, reliability, and quality of data.

DevOps 272

DevOps Analytics Airlines Metrics 272

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

Scalegrid

MAY 11, 2024

MongoDB offers several storage engines that cater to various use cases. The default storage engine in earlier versions was MMAPv1, which utilized memory-mapped files and document-level locking. The newer, pluggable storage engine, WiredTiger, addresses this by using prefix compression, collection-level locking, and row-based storage.

Storage 130

Storage Engineering Cache Database 130

Dynatrace

MAY 21, 2024

Data with context can improve your ability to deliver on your goals, modernize your organization, and accelerate business transformation. These outcomes are made easy through the platform’s unique ability to turn data into answers and action, in contextual, real-time, and cost-effective ways that were previously impossible.

Technology 275

Technology Technology Analytics Storage 275

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

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 From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. is 220 Mbps.

Cloud 242

Cloud Media Storage Cache 242

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 Scalability 147

Dynatrace

JANUARY 17, 2024

And an O’Reilly Media survey indicated that two-thirds of survey respondents have already adopted generative AI —a form of AI that uses training data to create text, images, code, or other types of content that reflect its users’ natural language queries. AI requires more compute and storage. AI performs frequent data transfers.

Strategy 288

Strategy Artificial Intelligence Storage Cloud 288

DZone

AUGUST 16, 2023

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.

Cache 246

Cache Scalability Performance Latency 246

DZone

JUNE 15, 2023

In order to gain insight into these problems, we gather a range of metrics and logs to monitor the utilization of system resources such as CPU, memory, and application-specific latencies. It is worth noting that this data collection process does not impact the performance of the application.

Latency 253

Latency Storage Strategy Metrics 253

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

MAY 4, 2023

It can happen on an edge API system servicing customer devices, between the edge and mid-tier services, or from mid-tiers to data stores. It provides a good read on the availability and latency ranges under different production conditions. For instance, envision a response payload that delivers media streams for a playback session.

Traffic 347

Traffic Latency Tuning Systems 347

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. To serve the increasing number of push down queries, the in-memory storage layer would need to scale up as well, and it became clear that this would push the already expensive storage costs far higher.

Storage 297

Storage Cache Metrics Database 297

The Netflix TechBlog

SEPTEMBER 2, 2020

With request tracing and additional data from logs, events, metadata, and analysis, Edgar is able to show the flow of a request through our distributed system?—?what But, there are a few substantial differences in how Edgar approaches its data and its users. Adding logs to the picture can help a great deal.

Latency 298

Latency Transportation Engineering Traffic 298

Dynatrace

OCTOBER 23, 2023

Hyper-V plays a vital role in ensuring the reliable operations of data centers that are based on Microsoft platforms. Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. What is Microsoft Hyper-V?

Efficiency 264

Efficiency Virtualization Hardware Performance 264

The Netflix TechBlog

OCTOBER 19, 2020

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

Infrastructure 238

Infrastructure Transportation Storage Open Source 238

DZone

AUGUST 18, 2023

We all know that data is being generated at an unprecedented rate. You may also know that this has led to an increase in the demand for efficient and secure data storage solutions that won’t break the bank. What Are Edge Data Platforms? These platforms offer several advantages over traditional cloud computing.

IoT 130

IoT Media Latency Storage 130

Dynatrace

DECEMBER 13, 2023

This includes how quickly the application loads, how much load it is putting on the device, how much storage is being used, and how frequently it crashes. Here are some ways observability data is important to mobile app performance monitoring. Load time and network latency metrics. Issue remediation. Proactive monitoring.

Best Practices 246

Best Practices Mobile Metrics Performance 246

Dynatrace

NOVEMBER 9, 2023

Nutanix overview dashboard The extension automatically gathers real-time performance data from your Nutanix clusters to monitor resource usage, cluster health, and more, all in one place. Storage container metrics Track the usage and performance of storage containers to optimize resource allocation.

Virtualization 246

Virtualization Storage Metrics Monitoring 246

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Dynatrace

JANUARY 15, 2020

Therefore, it requires multidimensional and multidisciplinary monitoring: Infrastructure health —automatically monitor the compute, storage, and network resources available to the Citrix system to ensure a stable platform. Citrix platform performance—optimize your Citrix landscape with insights into user load and screen latency per server.

Latency 52

Latency Performance Virtualization Infrastructure 52

Dynatrace

OCTOBER 2, 2024

Existing siloed tools lead to inefficient workflows, fragmented data, and increased troubleshooting times. Rather than relying on disparate tools for each environment and team, Dynatrace integrates all data into one cohesive platform. There is no need to think about schema and indexes, re-hydration, or hot/cold storage.

Analytics 304

Analytics AWS DevOps Cloud 304

Dynatrace

AUGUST 21, 2024

These releases often assumed ideal conditions such as zero latency, infinite bandwidth, and no network loss, as highlighted in Peter Deutsch’s eight fallacies of distributed systems. With Dynatrace, teams can seamlessly monitor the entire system, including network switches, database storage, and third-party dependencies.

Engineering 262

Engineering Systems Latency Metrics 262

The Netflix TechBlog

NOVEMBER 3, 2022

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. Active data includes jobs and tasks that are currently running. Titus Gateway handles user requests.

Cache 233

Cache Latency Traffic Systems 233

High Scalability

SEPTEMBER 8, 2018

They've posted about Anna's new superpowers in Going Fast and Cheap: How We Made Anna Autoscale : Using Anna v0 as an in-memory storage engine, we set out to address the cloud storage problems described above. Each storage server collects statistics about the requests it serves, the data it stores, etc.

Storage 199

Storage Performance AWS Cloud 199