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AWS EC2 Virtualization 2017: Introducing Nitro

Brendan Gregg

Hardware virtualization for cloud computing has come a long way, improving performance using technologies such as VT-x, SR-IOV, VT-d, NVMe, and APICv. At Netflix, we've been using these technologies as they've been made available for instance types in the AWS EC2 cloud. Each dimension has progressed through these stages: 1.

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Zero Configuration Service Mesh with On-Demand Cluster Discovery

The Netflix TechBlog

Since there were no existing solutions available, we needed to build them ourselves. To improve availability, we designed systems where components could fail separately and avoid single points of failure. Today we have a wealth of tools, both OSS and commercial, all designed for cloud-native environments.

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AWS EC2 Virtualization 2017: Introducing Nitro

Brendan Gregg

Hardware virtualization for cloud computing has come a long way, improving performance using technologies such as VT-x, SR-IOV, VT-d, NVMe, and APICv. At Netflix, we've been using these technologies as they've been made available for instance types in the AWS EC2 cloud. Each dimension has progressed through these stages: 1.

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32 MiB Working Sets on a 64 GiB machine

Randon ASCII

In a steady-state process (not allocating excessively) on a system with sufficient memory (this system had 64 GiB of RAM and roughly 47 GiB of that was available) the number of page faults should be close to zero, and this was a long way from that. I then looked in the “Virtual Memory Snapshots” table at the Working Set column.

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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

We were pushing the limits of what was a leading commercial database at the time and were unable to sustain the availability, scalability and performance needs that our growing Amazon business demanded. Durable and Highly-Available – DynamoDB maintains data durability and 99.99

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Rising Tide Rents and Robber Baron Rents

O'Reilly

As the internet grew, the amount of information available to consumers became so vast that it outran traditional human means of curation and selection. By the end of 2012, it was up to 82%. Available at: [link]. Attention allocation was outsourced to the machines. The market was maturing.

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A Brief Guide of xPU for AI Accelerators

ACM Sigarch

EPU: Emotion Processing Unit is designed by Emoshape , as the MCU microchip design to enable a true emotional response in AI, robots and consumer electronic devices as a result of a virtually unlimited cognitive process. Comprehensive lists are available here and here. . FPU: Floating Processing Unit (FPU).