Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. It's an important vendor-neutral space to share the latest in technology.

Performance 110

Performance Latency Cache Virtualization 110

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. It was a great privilege.

Performance 52

Performance Latency Cache Virtualization 52

Brendan Gregg

JULY 2, 2021

biolatency Disk I/O latency histogram heat map. cachestat File system cache statistics line charts. runqlat CPU scheduler latency heat map. For a more recent example, I wrote cachestat(8) while on vacation in 2014 for use on the Netflix cloud, which was a mix of Linux 3.2 execsnoop New processes (via exec(2)) table.

Latency 145

Latency Cache Energy Systems 145

Brendan Gregg

JULY 2, 2021

biolatency Disk I/O latency histogram heat map 5. cachestat File system cache statistics line charts 7. runqlat CPU scheduler latency heat map 10. As an extreme example, I wrote cachestat(8) while on vacation in 2014 for use on the Netflix cloud, which was a mix of Linux 3.2 execsnoop New processes (via exec(2)) table 2.

Open Source 40

Open Source Latency Cache Energy 40

Abhishek Tiwari

NOVEMBER 3, 2018

Traditional CMS is a dead end In the last 5 years, traditional CMS landscape is not evolved much - both CMS technologies as well market maturity remains unchanged. Although some vendors have added support for APIs and cloud services most have not even bothered to adapt with changing technology landscape.

Systems 63

Systems Cache Website Network 63

Alex Russell

MARCH 6, 2021

A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. mid-priced Androids were slightly faster than 2014's iPhone 6. The Moto G4 , for example. The cheapest (high volume) Androids perform like 2012/2013 iPhones, respectively.

Performance 124

Performance Network Cache Metrics 124