Benchmarking Performance Tuning Video 
Brendan Gregg
MARCH 8, 2020
Systems performance is an effective discipline for performance analysis and tuning, and can help you find performance wins for your applications and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic.
Dynatrace
AUGUST 5, 2020
Synthetic monitors are also the perfect tool to monitor performance baselines. This clean-room, lab-like environment allows you to react to slight changes in performance. It also gives you the first indication of whether a new deployment of your application or API leads to a performance improvement or, perhaps, a regression.
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Brendan Gregg
MARCH 7, 2020
Systems performance is an effective discipline for performance analysis and tuning, and can help you find performance wins for your applications and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic.
Brendan Gregg
MARCH 7, 2020
Systems performance is an effective discipline for performance analysis and tuning, and can help you find performance wins for your applications and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic.
n0derunner
JULY 23, 2019
In this video I migrate a Postgres DB running PGbench benchmark. The variation in the transaction rate is due to the benchmark itself, the transaction rate is not expected to be uniform. The Postgres DB is totally un-tuned and contains purely default settings. The DB is running on a Host which is CPU constrained.
Smashing Magazine
JUNE 3, 2022
Measuring The Performance Of Typefaces For Users (Part 1). Measuring The Performance Of Typefaces For Users (Part 1). How well does a typeface work and perform against another similar typeface? Reasons To Measure The Performance Of Typefaces? Measuring Typefaces And The Resulting Performance Data. Thomas Bohm.
The Netflix TechBlog
OCTOBER 19, 2020
Investigating a video streaming failure consists of inspecting all aspects of a member account. A lenient trace data sampling policy generates a large number of traces in each service container and can lead to degraded performance of streaming services as more CPU, memory, and network resources are consumed by the tracer library.
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