InfoQ

JANUARY 26, 2024

The company evolved the guild component, which is responsible for fanning out billions of message notifications, in a series of performance and scalability improvements supported by system observability and performance tuning. By Rafal Gancarz

Servers 104

Servers Tuning Scalability Performance 104

Percona

APRIL 7, 2023

If we were to select the most important MySQL setting, if we were given a freshly installed MySQL or Percona Server for MySQL and could only tune a single MySQL variable, which one would it be? To be fair, that is also true with PostgreSQL; it hasn’t been tuned either, and it, too, can also perform much better.

Tuning 139

Tuning Cache Servers Benchmarking 139

The Netflix TechBlog

AUGUST 30, 2021

System Setup Architecture The following diagram summarizes the architecture description: Figure 1: Event-sourcing architecture of the Device Management Platform. Fault Tolerance If the underlying KafkaConsumer crashes due to ephemeral system or network events, it should be automatically restarted. million elements.

Latency 213

Latency Traffic Transportation Hardware 213

Scalegrid

MARCH 22, 2024

They can also bolster uptime and limit latency issues or potential downtimes. Register now for free and experience the seamless operation of your databases across multi-cloud and hybrid-cloud systems. By spreading your data and apps around, you can get your systems to work together more smoothly and make the most out of your budget.

Strategy 130

Strategy Cloud Government Innovation 130

John McCalpin

APRIL 25, 2023

For most high-end processors these values have remained in the range of 75% to 85% of the peak DRAM bandwidth of the system over the past 15-20 years — an amazing accomplishment given the increase in core count (with its associated cache coherence issues), number of DRAM channels, and ever-increasing pipelining of the DRAMs themselves.

Benchmarking 97

Benchmarking Cache Latency Tuning 97

Dynatrace

DECEMBER 2, 2021

As organizations adopt microservices-based architecture , service-level objectives (SLOs) have become a vital way for teams to set specific, measurable targets that ensure users are receiving agreed-upon service levels. For example, an objective for system availability can be: 90% – one 9. Dynatrace news. How SLOs work.

Metrics 193

Metrics Best Practices DevOps Infrastructure 193

The Morning Paper

NOVEMBER 10, 2019

It’s been clear for a while that software designed explicitly for the data center environment will increasingly want/need to make different design trade-offs to e.g. general-purpose systems software that you might install on your own machines. The desire for CPU efficiency and lower latencies is easy to understand. Emphasis mine).

Network 92

Network Transportation Latency Entertainment 92

Dotcom-Montior

NOVEMBER 11, 2020

In serverless architecture, when applications are developed, they are typically composed of many different services. Other benefits to serverless architecture include the following: Cost. There is plenty to like about moving to a serverless architecture, but there can be some disadvantages compared to the traditional, monolithic model.

Serverless 57

Serverless Monitoring Lambda Latency 57

Percona

APRIL 17, 2023

In this blog post, we will discuss the best practices on the MongoDB ecosystem applied at the Operating System (OS) and MongoDB levels. The main objective of this post is to share my experience over the past years tuning MongoDB and centralize the diverse sources that I crossed in this journey in a unique place. 25.84 - Total 21.04

Best Practices 52

Best Practices Design Tuning Database 52

IO River

NOVEMBER 15, 2023

This involves:Threat Intelligence: Keeping an eye on the latest types of attacks, whether it's a novel form of SQL injection or a new phishing tactic.Internal Audits: Regularly scanning your own system for vulnerabilities. Two of them are particularly gnarly: fine-tuning rules to perfection and managing a WAF over a multi-CDN architecture.

Traffic 52

Traffic Network Logistics Architecture 52

HammerDB

MAY 5, 2019

Note that the main developer of HammerDB is Intel employee (#IAMINTEL) however HammerDB is a personal open source project and HammerDB has no optimization whatsoever for a database running on any particular architecture. So to test I took a system with Skylake CPUs and all storage on a P4800X SSD. In the recent MySQL 8.0.16

Testing 48

Testing Tuning Latency Storage 48

The Morning Paper

JUNE 13, 2019

Making queries to an inference engine has many of the same throughput, latency, and cost considerations as making queries to a datastore, and more and more applications are coming to depend on such queries. Managed here means that the system automates resource provisioning for models to match a set of SLO constraints (cf. autoscaling).

Hardware 58

Hardware Latency Serverless Energy 58

IO River

NOVEMBER 2, 2023

This involves:Threat Intelligence: Keeping an eye on the latest types of attacks, whether it's a novel form of SQL injection or a new phishing tactic.Internal Audits: Regularly scanning your own system for vulnerabilities. Two of them are particularly gnarly: fine-tuning rules to perfection and managing a WAF over a multi-CDN architecture.

Traffic 40

Traffic Network Logistics Architecture 40

The Netflix TechBlog

FEBRUARY 18, 2022

To this end, we developed a Rapid Event Notification System (RENO) to support use cases that require server initiated communication with devices in a scalable and extensible manner. In this blog post, we will give an overview of the Rapid Event Notification System at Netflix and share some of the learnings we gained along the way.

Systems 334

Systems Traffic Architecture Mobile 334

O'Reilly Software

APRIL 4, 2018

Considerations for setting the architectural foundations for a fast data platform. Google was among the pioneers that created “web scale” architectures to analyze the massive data sets that resulted from “crawling” the web that gave birth to Apache Hadoop, MapReduce, and NoSQL databases. Back in the days of Web 1.0, At least once?

Architecture 80

Architecture Scalability Google Operating System 80

Abhishek Tiwari

JULY 12, 2018

In a nutshell, a data pipeline is a distributed system. If tuned for performance, there is a good change reliability is compromised - and vice versa. Processing latency is minimum If only you can infinitely scale your data pipeline, processing latency can be guaranteed to be minimum, but we know for sure that is not true.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

JUNE 13, 2023

This is where large-scale system migrations come into play. By collecting and analyzing key performance metrics of the service over time, we can assess the impact of the new changes and determine if they meet the availability, latency, and performance requirements. But what happens when this machinery needs a transformation?

Traffic 279

Traffic Metrics Systems Strategy 279

The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. By integrating with studio content systems, we enabled the pipeline to leverage rich metadata from the creative side and create more engaging member experiences like interactive storytelling.

Processing 229

Processing Media Latency Innovation 229

John McCalpin

JANUARY 22, 2018

Each of the two vector units can issue one FMA instruction per cycle, assuming that there are enough independent accumulators to tolerate the 6-cycle dependent-operation latency. of the “adjusted peak performance”, there is no longer a significant upside to performance tuning. not FMAs). cmpl $1000000000, %eax.

Latency 40

Latency Hardware Code Testing 40

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 first generation of this system went live with the streaming launch in 2007. Delivery?—?A

Serverless 228

Serverless Media Latency Social Media 228

The Netflix TechBlog

SEPTEMBER 24, 2021

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. Lastly, the packager kicks in, adding a system layer to the asset, making it ready to be consumed by the clients.

Cloud 237

Cloud Media Storage Cache 237

The Netflix TechBlog

MAY 14, 2021

Managing and operating asynchronous workflows can be difficult without the proper tools and architecture that puts observability, debugging, and tracing at the forefront. However, they are scattered across multiple systems, and there isn’t an easy way to tie related messages together. Imagine getting paged outside normal work hours?—?users

Traffic 160

Traffic Latency Java Google 160

HammerDB

OCTOBER 12, 2018

As with the previous guides as an Intel employee (#IAMINTEL) the examples are taken from a MySQL 8 on Linux on Intel system and the approach is the same for whatever system you are testing although some of the settings you see may be different. System Setup: CPU, Memory and I/O Configuration. hardware limits: 1000 MHz - 3.80

Best Practices 40

Best Practices Scalability Performance C++ 40

The Netflix TechBlog

DECEMBER 21, 2020

This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture. Use cases We found several use cases where a system like AutoOptimize can bring tons of value. Orient: Gather tuning parameters for a particular table that changed.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

NOVEMBER 2, 2021

The coupling problem Until recently, video quality measurements were generated as part of our Reloaded production system. This system is responsible for processing incoming media files, such as video, audio and subtitles, and making them playable on the streaming service. We call this system Cosmos. The workflow is initiated.

Media 171

Media Innovation Metrics Latency 171

The Netflix TechBlog

OCTOBER 27, 2020

At Netflix, we also heavily embrace a microservice architecture that emphasizes separation of concerns. The data warehouse is not designed to serve point requests from microservices with low latency. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

FEBRUARY 9, 2021

In particular, it’s our job to design and build the systems and protocols that enable customers from all over the world to sign up for Netflix with the plan features and incentives that best suit their needs. Let’s take a deeper look at the architecture, protocols, and systems involved.

Engineering 142

Engineering Scalability Architecture Innovation 142

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. Please stay tuned! We will have follow up blog posts on these topics in future.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

AUGUST 29, 2023

To improve availability, we designed systems where components could fail separately and avoid single points of failure. In this architecture, service to service communication no longer goes through the single point of failure of a load balancer. Compared to a decade ago, we now support more features, in more languages, in more clients.

Traffic 220

Traffic Latency Cloud C++ 220

The Netflix TechBlog

AUGUST 13, 2020

You’re half awake and wondering, “Is there really a problem or is this just an alert that needs tuning? Our streaming teams need a monitoring system that enables them to quickly diagnose and remediate problems; seconds count! Our Node team needs a system that empowers a small group to operate a large fleet. By Andrei U.,

Monitoring 210

Monitoring Tuning Traffic Metrics 210

The Netflix TechBlog

NOVEMBER 2, 2020

How viewers are able to watch their favorite show on Netflix while the infrastructure self-recovers from a system failure By Manuel Correa , Arthur Gonigberg , and Daniel West Getting stuck in traffic is one of the most frustrating experiences for drivers around the world. Those two metrics are approximate indicators of failures and latency.

Traffic 252

Traffic Metrics Infrastructure Architecture 252

SQL Server According to Bob

JANUARY 11, 2020

This will help you increase system performance and avoid I/O environment errors. Important When planning, deploying, and maintaining a Microsoft SQL Server installation, ensure that the I/O system supports all the factors outlined in this article. The modifications persist even in the event of a system failure.

Servers 40

Servers Cache Media Hardware 40

The Netflix TechBlog

DECEMBER 17, 2019

In order to be supported, a database is required to fulfill a set of features that are commonly available in systems like MySQL, PostgreSQL, MariaDB, and others. We want to support these systems as a source so that they can provide their data for further consumption. DBLog High Level Architecture. Figure 3?—?DBLog

Database 197

Database Traffic Transportation Open Source 197

The Netflix TechBlog

DECEMBER 17, 2019

In order to be supported, a database is required to fulfill a set of features that are commonly available in systems like MySQL, PostgreSQL, MariaDB, and others. We want to support these systems as a source so that they can provide their data for further consumption. DBLog High Level Architecture. Figure 3?—?DBLog

Database 212

Database Traffic Transportation Open Source 212

All Things Distributed

NOVEMBER 29, 2017

After this, there is often a long process of training that includes tuning the knobs and levers, called hyperparameters, that control the different aspects of the training algorithm. Built-in model tuning (hyperparameter optimization) that can automatically adjust hundreds of different combinations of algorithm parameters.

Tuning 94

Tuning AWS Scalability Infrastructure 94