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Web Performance Bookshelf

Rigor

Reading time 1 min Why share the library of the web performance books while there’s a substantial collection of fantastic websites and articles on the net? High Performance Browser Networking. This book is about performance problems and the various technologies created to fight them. High Performance Websites.

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A Year of Ongoing Excellence for Apica

Apica

Since our founding in 2005, Apica has made steady progress as our tech has matured, our offerings have broadened, and our team has grown. Now, more than ever, we’ve been making headlines in the application performance space as we expand our horizons and challenge ideas about what application monitoring really means. .

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An Unbelievable Demo

Brendan Gregg

It was 2005, and I felt like I was in the eye of a hurricane. I was an independent performance consultant and Sun Microsystems had just released DTrace, a tool that could instrument all software. This gave performance analysts like myself X-ray vision. You can't make this stuff up. I was living in Sydney, Australia.

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The Return of the Frame Pointers

Brendan Gregg

I'm sure this delivered large performance improvements and I wouldn't try arguing against it. 2005-2023: The winter of broken profilers However, the change was then applied to x86-64 (64-bit) as well, which had sixteen registers and didn't benefit so much from a seventeenth. But I'd rather the cost be zero, of course!

Java 145
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SQL Server I/O Basics Chapter #2

SQL Server According to Bob

​​ With new ​​ innovations ​​ come ​​ new terms, designs, ​​ and ​​ algorithms.

Servers 40
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The Amazing Evolution of In-Memory Computing

ScaleOut Software

Software platforms for distributed caching, such as ScaleOut StateServer ®, which was introduced in 2005, hide internal mechanisms for cluster membership, throughput scaling, and high availability to take full advantage of the cluster’s scalable memory without adding complexity to applications.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

Software platforms for distributed caching, such as ScaleOut StateServer ®, which was introduced in 2005, hide internal mechanisms for cluster membership, throughput scaling, and high availability to take full advantage of the cluster’s scalable memory without adding complexity to applications.