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 222

Latency Systems Media Serverless 222

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 220

Processing Big Data Efficiency Engineering 220

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. Performance is usually a primary concern when using stream processing frameworks. This significantly increases event latency.

Engineering 187

Engineering Tuning Latency Open Source 187

The Netflix TechBlog

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Media 244

Media Traffic Processing Design 244

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. On the other hand, these optimizations themselves need to be sufficiently inexpensive to justify their own processing cost over the gains they bring.

Storage 213

Storage Latency Efficiency Data Engineering 213

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 252

Availability Hardware Latency Traffic 252

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 253

Performance Architecture Innovation Latency 253

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 216

Artificial Intelligence Storage Analytics Government 216

The Netflix TechBlog

SEPTEMBER 10, 2024

One issue that often complicates this process is the "noisy neighbor" problem. Continuous instrumentation is critical to catching such matters as they emerge, and eBPF, with its hooks into the Linux scheduler with minimal overhead, enabled us to monitor run queue latency efficiently.

Latency 262

Latency Metrics Programming Monitoring 262

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]. This motivated the development of DBLog , which offers log and dump processing under a generic framework.

Database 221

Database Traffic Transportation Open Source 221

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 215

Analytics Latency Processing Systems 215

The Netflix TechBlog

NOVEMBER 12, 2024

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 251

Latency Cache Infrastructure Strategy 251

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. After that, the various services (e.g.

Design 334

Design Media Storage Logistics 334

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]. This motivated the development of DBLog , which offers log and dump processing under a generic framework.

Database 207

Database Traffic Transportation Open Source 207

Scalegrid

NOVEMBER 25, 2019

ScyllaDB is an open-source distributed NoSQL data store, reimplemented from the popular Apache Cassandra database. ScyllaDB offers significantly lower latency which allows you to process a high volume of data with minimal delay. percentile latency is up to 11X better than Cassandra on AWS EC2 bare metal.

Big Data 187

Big Data Database Open Source Azure 187

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.

Traffic 347

Traffic Latency Tuning Systems 347

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 199

DevOps Analytics Airlines Metrics 199

CSS Wizardry

OCTOBER 16, 2023

In this post, I’m going to break these processes down into each of: ? Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download. Read the complete test methodology. It gets worse.

Cache 337

Cache Latency Strategy Speed 337

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. We measure PostgreSQL throughput in terms of transactions processed. Latency is the average transaction execution time of your PostgreSQL data.

Database 230

Database Latency Benchmarking Performance 230

Dynatrace

DECEMBER 27, 2022

When organizations implement SLOs, they can improve software development processes and application performance. SLOs can be a great way for DevOps and infrastructure teams to use data and performance expectations to make decisions, such as whether to release and where engineers should focus their time. SLOs improve software quality.

Software 270

Software Software Benchmarking Latency 270

DZone

NOVEMBER 25, 2023

Factors like read and write speed, latency, and data distribution methods are essential. For instance, rapid read and write operations are crucial for applications requiring real-time data analytics. Yet, they are often evaluated in isolation, removed from the business context.

Database 278

Database Latency Speed Metrics 278

Dynatrace

OCTOBER 28, 2024

As modern multicloud environments become more distributed and complex, having real-time insights into applications and infrastructure while keeping data residency in local markets is crucial. Dynatrace on Microsoft Azure allows enterprises to streamline deployment, gain critical insights, and automate manual processes. The result?

Azure 242

Azure Latency Infrastructure Cloud 242

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. cell): Titus Job Coordinator is a leader elected process managing the active state of the system.

Cache 234

Cache Latency Traffic Systems 234

Dynatrace

JULY 22, 2024

Using OpenTelemetry, developers can collect and process telemetry data from applications, services, and systems. Observability Observability is the ability to determine a system’s health by analyzing the data it generates, such as logs, metrics, and traces. There are three main types of telemetry data: Metrics.

Latency 240

Latency Best Practices Metrics Open Source 240

The Netflix TechBlog

MARCH 5, 2024

Reduced tail latencies In both our GRPC and DGS Framework services, GC pauses are a significant source of tail latencies. For a given CPU utilization target, ZGC improves both average and P99 latencies with equal or better CPU utilization when compared to G1.

Latency 238

Latency Java Tuning Efficiency 238

The Netflix TechBlog

MARCH 1, 2021

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The centralized data model that had served us well when we were a small team became a liability.

Serverless 235

Serverless Media Latency Social Media 235

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

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. This article will explore what edge data platforms and real-time services are, why they are important, and how they can be used.

IoT 130

IoT Media Latency Storage 130

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. As a consequence, the automatic updates as well as the automatic deep-code monitoring injection processes are even more stable.

Storage 150

Storage Latency Operating System Network 150

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

The Netflix TechBlog

JUNE 4, 2019

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. Its goal is to assign running processes to time slices of the CPU in a “fair” way. So why mess with it?

Cache 259

Cache Latency Airlines Logistics 259

The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. In this way, no human intervention is required in the remediation process. Multi-objective optimizations.

Tuning 217

Tuning Efficiency Big Data Engineering 217

The Netflix TechBlog

FEBRUARY 20, 2019

Today we are excited to announce latency heatmaps and improved container support for our on-host monitoring solution?—?Vector?—?to Remotely view real-time process scheduler latency and tcp throughput with Vector and eBPF What is Vector? 10–20 MB/sec (it is, unsurprisingly, receiving lots of data). is more clearly visible.

Performance 216

Performance Latency Open Source Metrics 216

The Netflix TechBlog

SEPTEMBER 24, 2021

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. Packaging has always been an important step in media processing. Uploading and downloading data always come with a penalty, namely latency.

Cloud 242

Cloud Media Storage Cache 242

The Netflix TechBlog

SEPTEMBER 2, 2020

When a problem occurs, we put on our detective hats and start our mystery-solving process by gathering evidence. 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 Adding logs to the picture can help a great deal.

Latency 299

Latency Transportation Engineering Traffic 299

The Netflix TechBlog

SEPTEMBER 10, 2024

This allows data to be sent to the device from backend services on demand, without the need for continually polling requests from the device. The voice service then constructs a message for the device and places it on the message queue, which is then processed and sent to Pushy to deliver to the device.

Latency 235

Latency Cache Tuning Efficiency 235

Dynatrace

FEBRUARY 21, 2024

Open vulnerability on process group: The total number of currently high-profile vulnerabilities related to a process group. Vulnerability score: The highest vulnerability risk score for a process group. This way, the travel agency can easily streamline, organize, and consolidate their quality gates and metric evaluation process.

Speed 213

Speed Software Software Latency 213