The Netflix TechBlog

SEPTEMBER 10, 2024

By Karthik Yagna , Baskar Odayarkoil , and Alex Ellis Pushy is Netflix’s WebSocket server that maintains persistent WebSocket connections with devices running the Netflix application. The first was voice control, where you can play a title or search using your virtual assistant with a voice command like “Show me Stranger Things on Netflix.”

Latency 230

Latency Cache Tuning Efficiency 230

All Things Distributed

SEPTEMBER 3, 2013

Amazon RDS , with support for MySQL, SQL Server and Oracle databases, is for customers with apps where relational database features and support for a specific brand of database are critical. Amazon ElastiCache is a fully managed, in-memory caching service for customers to optimize the latency, performance and cost of their read workloads.

Cache 99

Cache Cloud Performance Retail 99

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? Sysbench ran on a third server, which I’ll refer to as the application server (APP).

Tuning 139

Tuning Cache Servers Benchmarking 139

Percona

SEPTEMBER 28, 2023

Whenever you install your favorite MySQL server on a freshly created Ubuntu instance, you start by updating the configuration for MySQL, such as configuring buffer pool, changing the default datadir director, and disabling one of the most outstanding features – query cache. It’s a nice thing to do, but first things first.

Servers 117

Servers Best Practices Database Open Source 117

High Scalability

OCTOBER 3, 2019

This Redis management solution allows startups up to enterprise-level organizations automate their Redis operations on Microsoft Azure dedicated cloud servers, alongside their other open source database deployments, including MongoDB , MySQL and PostgreSQL.

Azure 23

Azure Cloud Open Source Cache 23

Scalegrid

MAY 11, 2024

However, it is limited by the available free memory amount, and all data is lost when the server stops. However, due to its reliance on the virtual memory subsystem, it is not suitable for larger datasets. However, due to its reliance on the virtual memory subsystem, it is not suitable for larger datasets.

Storage 130

Storage Engineering Cache Database 130

Dynatrace

DECEMBER 15, 2020

Windows: Windows Server 1903. Resolved IIS crash on RUM activity interactions (user caching is now disabled if UEM is enabled). Citrix Profile Management now correctly indicated as Citrix Common technology, instead of Citrix Virtual Delivery Agent (VDA). Linux: Google Container-Optimized OS 77 LTS. x86 (64bit-only).

Operating System 165

Operating System Java Mobile Cache 165

Percona

OCTOBER 2, 2023

Percona Toolkit is a collection of advanced open source command-line tools, developed and used by the Percona technical staff, that are engineered to perform a variety of MySQL, MariaDB, MongoDB, and PostgreSQL server and system tasks that are too difficult or complex to perform manually. virtual = 2.2G Caches | 12.4G

Cache 103

Cache Database Virtualization Servers 103

Scalegrid

OCTOBER 2, 2019

This management solution for Redis™ allows startups up to enterprise-level organizations automate their Redis™ operations on Microsoft Azure dedicated cloud servers, alongside their other open source database deployments, including MongoDB , MySQL and PostgreSQL. PALO ALTO, Calif.,

Azure 100

Azure Availability Open Source Virtualization 100

Percona

MARCH 17, 2023

Planning for resources of a PMM Server host instance can be tricky because the numbers can change depending on the DB instances being monitored by PMM. Virtual Memory utilization was averaging 48 GB of RAM. VictoriaMetrics maintains an in-memory cache for mapping active time series into internal series IDs.

Monitoring 103

Monitoring Scalability Database Cache 103

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory.

Performance 103

Performance Latency Cache Virtualization 103

ScaleOut Software

MAY 15, 2014

For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Given all this, we thought it would be a good opportunity to see how we are doing relative to the competition, and in particular, relative to Microsoft’s AppFabric caching for Windows on-premise servers.

Cache 40

Cache Servers Network Design 40

SQL Performance

APRIL 8, 2019

Back on December 5, 2017, Microsoft announced that they were using AMD EPYC 7551 processors in their storage-optimized Lv2-Series virtual machines. These AMD EPYC processors have a number of advantages for SQL Server workloads, as I will explain in this article. The L3 cache size is 64MB. The L3 cache size is 64MB.

Azure 42

Azure Virtualization Storage Benchmarking 42

Brendan Gregg

MARCH 16, 2024

Only in extreme circumstances does the cost (in processor time and I-cache footprint) translate to a tangible benefit - circumstances which usually resort to hand-coded assembly anyway. It shouldn't be 10%, unless it's cache effects. Back-end servers. The actual overhead depends on your workload.

Java 137

Java Cache Google Hardware 137

SQL Performance

NOVEMBER 18, 2019

Migrating an on-premises SQL Server instance to an Azure Virtual Machine (VM) is a common method to migrate to Azure. Microsoft has helped simplify things by creating multiple types of virtual machines. Compute optimized – High CPU-to-memory ration, medium traffic web servers and application servers. Generation.

Azure 76

Azure Benchmarking Storage Virtualization 76

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. These storage nodes collaborate to manage and disseminate the data across numerous servers spanning multiple data centers.

Storage 130

Storage Systems Big Data Azure 130

All Things Distributed

OCTOBER 2, 2017

VPC Endpoints give you the ability to control whether network traffic between your application and DynamoDB traverses the public Internet or stays within your virtual private cloud. percent availability in the event of a server, a rack of servers, or an Availability Zone failure.

Internet 110

Internet Internet AWS Performance 110

All Things Distributed

JANUARY 18, 2012

Behind the scenes, Amazon DynamoDB automatically spreads the data and traffic for a table over a sufficient number of servers to meet the request capacity specified by the customer. Developers can store and retrieve any amount of data and DynamoDB will spread the data across more servers as the amount of data stored in your table grows.

Scalability 162

Scalability Database Ecommerce Latency 162

Randon ASCII

JULY 11, 2022

This slowdown may be mitigated in Windows 11 but in the latest Windows Server editions – where it matters most – this bug is alive and well. Downloads go through the cache, the cache is saved to disk, and saves to disk are slowed by (some) anti-virus software. Server versions should be fine…. Case closed. well spent.

Cache 105

Cache Energy Google Processing 105

SQL Performance

JUNE 21, 2019

I've been teaching and writing about common SQL Server mistakes for many years. This article will expand on my previous article and point out how these apply to SQL Server , Azure SQL Database , and Azure SQL Managed Instance. SQL Server Agent alerts. This situation applies to on-premises SQL Server and IaaS. Statistics.

Servers 49

Servers Azure Hardware Database 49

Percona

JUNE 22, 2023

Load balancing : Requests are evenly distributed across multiple database servers, ensuring the system remains operational even if one server fails. Automated failover : To keep the database operational and minimize downtime, it automatically switches to a backup server if the primary server fails.

Availability 112

Availability Database Open Source Hardware 112

HammerDB

JUNE 27, 2022

An important concept was to simulate database users called Virtual Users in parallel (rather than concurrently) to accurately simulate a real database workload with multiple users running from separate systems. Cached vs Scaled Workloads. The workload also outputted the data from the Virtual Users by simulating individual terminals.

Benchmarking 63

Benchmarking Open Source C++ Cache 63

SQL Server According to Bob

JANUARY 11, 2020

Microsoft SQL Server I/O Basics Author: ​​ Bob Dorr, Microsoft SQL Server Escalation Published: ​​ December, 2004 SUMMARY: ​​ Learn the I/O requirements for Microsoft SQL Server database file operations. This will help you increase system performance and avoid I/O environment errors.

Servers 40

Servers Cache Media Hardware 40

Smashing Magazine

SEPTEMBER 20, 2021

When your content is delivered by other means, from other servers or platforms, it can put the user experience and commercial relationship you have built up with your users at risk. Search Engine And Web Archive Cached Results. The message that appears above a cached search result in Google’s search service. Large preview ).

Website 104

Website Analytics Google Cache 104

HammerDB

JULY 5, 2022

To do this, we are going to rewrite HammerDB in Python and run a series of tests on a 2 socket Intel(R) Xeon(R) Platinum 8280L server to see how and why Tcl is 700% faster than Python for database benchmarking*. buff/cache MiB Swap: 2048.0 buff/cache MiB Swap: 2048.0 Background and Concepts. usr/local/bin/tclsh8.6 total, 581155.8

Benchmarking 98

Benchmarking Database C++ Virtualization 98

Percona

DECEMBER 23, 2022

The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes. I decided to use a virtual machine with two CPU cores, four GB of memory, and storage limited to a maximum of 1000 IOPs of 16KB.

Storage 55

Storage Cache C++ Virtualization 55

HammerDB

FEBRUARY 26, 2024

This is particularly important when running automated workloads back-back to generate a performance profile for a progressively increasing number of virtual users. Once the run has completed it will dynamically set the variables to run the purge and write back and restore your variables when complete.

C++ 63

C++ Cache Database Virtualization 63

Smashing Magazine

OCTOBER 31, 2023

You might think of it like racing a car in virtual reality, where the conditions are decided in advance, rather than racing on a live track where conditions may vary. DevTools throttling is easier to set up, but doesn’t accurately reflect how server connections work on the network. Source: Source: DebugBear.

Speed 113

Speed Google Website Metrics 113

Percona

SEPTEMBER 1, 2023

MySQL server performance can sometimes be perplexing, and if you’ve ever wondered about the role of triggers in influencing your MySQL server’s memory allocation, this post is for you. These table cache instances could be accessed concurrently, allowing DML to use cached table descriptors without locking each other.

Cache 64

Cache Database Games Healthcare 64

KeyCDN

JANUARY 23, 2020

This helps developers decide when to increase server disk space and power or whether or not using a virtual cloud server is optimal. Basic server metrics. For applications hosted on the developer’s own servers, these APMs can measure the performance of CPUs, memory, data drives, and more. Usage performance.

Strategy 72

Strategy Metrics Monitoring Servers 72

ScaleOut Software

JULY 21, 2020

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Application code is automatically shipped by the client library to the IMDG for execution and runs fully in parallel across all servers for maximum performance.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Application code is automatically shipped by the client library to the IMDG for execution and runs fully in parallel across all servers for maximum performance.

Analytics 52

Analytics Airlines Cache Scalability 52

HammerDB

APRIL 19, 2023

Regardless of whether the computing platform to be evaluated is on-prem, containerized, virtualized, or in the cloud, it is crucial to consider several essential factors. For the network, we can use Iperf to assess the network bandwidth between the client and the database server to ensure it will be enough to meet our peak requirement.

Performance 55

Performance Benchmarking Cache Storage 55

HammerDB

OCTOBER 17, 2018

For a really quick answer create a schema with 250-500 warehouses per server CPU socket for more details size as follows. . However most people use HammerDB with keying and thinking time disabled and therefore each virtual user can approximately drive the CPU resources of one CPU core on the database server.

C++ 40

C++ Testing Virtualization Cache 40

Enprowess

SEPTEMBER 7, 2021

Software Developers got to use JavaScript CLI tools to create the back-end part of web applications or server-side. allows creating web application’s server-side or back-end components. is a server-side, open-source, JavaScript runtime environment that allows developers to write JavaScript on the client and the server-side.

Open Source 52

Open Source Virtualization Programming Servers 52

IO River

NOVEMBER 2, 2023

Split and Separate Static and Dynamic TrafficStatic traffic is traffic that is cached close to the user and stored and served to them by the nearest server. Dynamic traffic, on the other hand, is personalized and served from the origin server. This means they need to be handled differently, in terms of security and performance.If

Infrastructure 52

Infrastructure Traffic Cache Strategy 52

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory.

Performance 52

Performance Latency Cache Virtualization 52