SQL Server According to Bob

SEPTEMBER 26, 2016

When we released Always On Availability Groups in SQL Server 2012 as a new and powerful way to achieve high availability, hardware environments included NUMA machines with low-end multi-core processors and SATA and SAN drives for storage (some SSDs). As we moved towards SQL Server 2014, the pace of hardware accelerated.

Availability 40

Availability Servers Hardware Benchmarking 40

HammerDB

DECEMBER 5, 2020

The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint. For TPC-C this meant enough available spindles to reduce I/O latency and for TPC-H enough bandwidth for data throughput. better.

C++ 40

C++ Benchmarking Virtualization Open Source 40

Percona

JULY 1, 2023

These may be performance, high availability, operational cost, management, capacity planning, scalability, security, monitoring, etc. Aurora Features High Performance and Scalability Amazon Aurora has gained widespread recognition for its exceptional performance and scalability, making it an ideal solution for handling demanding workloads.

AWS 52

AWS Database Serverless Storage 52

Smashing Magazine

SEPTEMBER 28, 2022

The resource loading waterfall is a cascade of files downloaded from the network server to the client to load your website from start to finish. On your first try, you can use it as a benchmark for optimizations later. Client Side Rendering, Server Side Rendering And Jamstack. On design systems, UX, web performance and CSS/JS.

Cache 126

Cache Performance Servers Social Media 126

HammerDB

OCTOBER 12, 2018

For anyone benchmarking MySQL with HammerDB it is important to understand the differences from sysbench workloads as HammerDB is targeted at a testing a different usage model from sysbench. maximum transition latency: Cannot determine or is not supported. . HammerDB difference from Sysbench. hardware limits: 1000 MHz - 3.80

Best Practices 40

Best Practices Scalability Performance C++ 40

KeyCDN

AUGUST 15, 2019

Before you begin tuning your website or application, you must first figure out which metrics matter most to your users and establish some achievable benchmarks. Quantitative performance testing looks at metrics like response time while qualitative testing is concerned with scalability, stability, and interoperability.

Testing Tools 55

Testing Tools Best Practices Performance Testing Testing 55

SQL Server According to Bob

JANUARY 11, 2020

Microsoft, ​​ Windows, ​​ Windows NT, ​​ and Windows Server ​​ are registered trademarks of Microsoft Corporation in the United States and/or other countries. The names of actual companies and products mentioned herein may be the trademarks of their respective owners.

Servers 40

Servers Cache Database Media 40

All Things Distributed

NOVEMBER 19, 2010

Werner Vogels weblog on building scalable and robust distributed systems. There was an excellent first benchmarking report of the Cluster GPU Instances by the folks at Cycle Computing - " A Couple More Nails in the Coffin of the Private Compute Cluster " The Top500 supercomputer list. No Server Required - Jekyll & Amazon S3.

AWS 67

AWS Cloud Benchmarking Storage 67

Smashing Magazine

JANUARY 11, 2021

In the end, it’s not the load events or server response times that define the experience, but the perception of how snappy the interface feels. It used to provide an insight into how quickly the server outputs any data. This knowledge will give you the best optimization target for ongoing efforts. What does it mean?

Performance 145

Performance Cache Media Metrics 145

Smashing Magazine

JANUARY 6, 2020

Is it worth exploring tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, server push, clients hints, HTTP/2, service workers and — oh my — edge workers? It used to provide an insight into how quickly the server outputs any data. What does it mean?

Performance 145

Performance Cache Network Metrics 145

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. Likewise, object access paths must be heavily multi-threaded and avoid lock contention to minimize access latency and maximize throughput. Unwanted Client Exceptions from AppFabric.

Cache 40

Cache Servers Network Design 40