Adrian Cockcroft

JUNE 21, 2022

In 1991 I wrote a white paper on performance that was widely read, and in 1993 (with help from Brian Wong) that got me a job in the USA, working alongside Brian for Mike Briggs in technical product marketing. Rich became co-author of the second edition of the Sun Performance Tuning book, to describe how it worked.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Speed Curve

JUNE 24, 2019

Monitor your longest Long Tasks. For example, I see this particularly with hero images on campaign landing pages, which are sometimes built and released quickly without proper due diligence paid to ensuring they’re performant. Create performance budgets. Performance budgets are a vital tool in your web performance toolbox.

Performance 78

Performance Best Practices Metrics Mobile 78

Speed Curve

JULY 3, 2023

This is to try to understand how a "typical" page might perform, as well as pages in the "longtail". It's super important to understand longtail performance. These numbers should not be taken as a benchmark for your own site. Use performance budgets to fight regression Page bloat happens when people stop paying attention.

Mobile 52

Mobile Google Metrics Retail 52

Rigor

FEBRUARY 15, 2018

As web perfectionists, we have heard every excuse in the book for why teams cannot make web performance a priority. Whether it be time, money, or technical know how, every day we talk to eCommerce and Retail teams who explain why they aren’t monitoring their site’s performance. So you don’t know how to code?

Ecommerce 40

Ecommerce Retail Performance Benchmarking 40

Brendan Gregg

FEBRUARY 9, 2018

Much of my testing was on Linux 4.14.11 Some older kernels have the KAISER patches for Meltdown, and so far the performance overheads look similar. I then analyzed performance during the benchmark ([active benchmarking]), and used other benchmarks to confirm findings. and 4.14.12 In more detail: ## 1.

Performance 75

Performance Benchmarking Cache Tuning 75

Percona

DECEMBER 20, 2018

Not being entirely sure of what I was seeing during a customer visit, I set out to create some simple tests to measure the impact of triggers on database performance. AMD EPYC Performance Testing… or Don’t get on the wrong side of SystemD. Tuning PostgreSQL Database Parameters to Optimize Performance.

Database 40

Database Tuning Performance AWS 40

Brendan Gregg

FEBRUARY 8, 2018

Much of my testing was on Linux 4.14.11 Some older kernels have the KAISER patches for Meltdown, and so far the performance overheads look similar. I then analyzed performance during the benchmark ([active benchmarking]), and used other benchmarks to confirm findings. and 4.14.12 In more detail: ## 1.

Performance 40

Performance Benchmarking Cache Tuning 40

Rigor

OCTOBER 30, 2019

One free tool has become prominent in the space – Google Lighthouse – and one question often bubbles up: “I use Google Lighthouse for one-off snapshots of my site’s performance, so why do I need a performance monitoring solution?” Google Lighthouse is a great place to start for performance analysis.

Google 51

Google Best Practices Energy Website 51

HammerDB

OCTOBER 12, 2018

This post complements the previous best practice guides this time with the focus on MySQL and MariaDB and achieving top levels of performance with the HammerDB MySQL TPC-C test. InnoDB is the storage engine that will deliver the best OLTP throughput and should be chosen for this test. . HammerDB difference from Sysbench.

Best Practices 40

Best Practices Scalability Performance C++ 40

Smashing Magazine

JANUARY 6, 2020

Performance isn’t just a technical concern: it affects everything from accessibility to usability to search engine optimization, and when baking it into the workflow, design decisions have to be informed by their performance implications. Testing And Monitoring. Now you have something measurable to test against.

Performance 145

Performance Cache Network Metrics 145

High Scalability

NOVEMBER 25, 2019

If you develop something then you own the lifecycle of that product, which means you would work with QA, DevOps to ensure it’s tested/deployed. When it goes to production you would monitor it using the various internal tools like New Relic/Grafana, Kibana and if there is a regression you would fix it.

Architecture 52

Architecture Cache Azure Storage 52