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File systems unfit as distributed storage backends: lessons from ten years of Ceph evolution

The Morning Paper

Breaking that assumption allowed Ceph to introduce a new storage backend called BlueStore with much better performance and predictability, and the ability to support the changing storage hardware landscape. Readers of this blog properly have a pretty good idea what ‘efficient transactions’ and ‘fast metadata operations’ are all about.

Storage 64
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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

That's about 24 hours from now! ## References I've reproduced the references from my SREcon22 keynote below, so you can click on links: - [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] Jul 2008 - [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] 2010 - [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double (..)

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Finding Distinct Values Quickly

SQL Performance

It comes set to SQL Server 2008 compatibility (level 100), but we will start with a more modern setting of SQL Server 2017 (level 140): ALTER DATABASE StackOverflow2013 SET COMPATIBILITY_LEVEL = 140 ; The tests were performed on my laptop using SQL Server 2019 CU 2. This will provide distinct values with great efficiency.

Servers 86
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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

References I've reproduced the references from my SREcon22 keynote below, so you can click on links: [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] , Jul 2008 [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] , 2010 [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double the latency?

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The Return of Financial Engineering - and What it Means for Tech

The Agile Manager

Soon after the financial crisis began in 2008, companies shifted attention from finance to operations. This limited the financial options companies could use to juice returns, so they focused on investing in operations to create efficiencies or fight for market share. But it's not all bad news.

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Structural Evolutions in Data

O'Reilly

” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” Millions of tests, across as many parameters as will fit on the hardware.

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Being Practical

Tim Kadlec

When he first gave the presentation in 2008, he was working at this massive company called Yahoo! Instead, to support a browser, we want to give the browser what it can handle, in the most efficient way possible. That was 2008. Here at Yahoo!, It’s our job to make sure that they have a great user experience.

Google 40