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The Speed of Time

Brendan Gregg

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. But I'm not completely sure.

Speed 126
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. In this talk, we share how Netflix deploys systems to meet its demands, Ceph’s design for high availability, and results from our benchmarking.

AWS 37
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article thumbnail

The Speed of Time

Brendan Gregg

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. But I'm not completely sure.

Speed 40
article thumbnail

The Speed of Time

Brendan Gregg

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI.

Speed 52
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Front-End Performance Checklist 2020 [PDF, Apple Pages, MS Word]

Smashing Magazine

For Mac OS, we can use Network Link Conditioner , for Windows Windows Traffic Shaper , for Linux netem , and for FreeBSD dummynet. In real-life world, most products aren’t even close: an median bundle size today is around 417KB , which is up 42% compared to early 2015. Lighthouse , a performance auditing tool integrated into DevTools.

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Front-End Performance Checklist 2021

Smashing Magazine

CrUX generates an overview of performance distributions over time, with traffic collected from Google Chrome users. But account for the different types and usage behaviors of your customers (which Tobias Baldauf called cadence and cohorts ), along with bot traffic and seasonality effects. compared to early 2015. Large preview ).