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Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

• http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

• Does the design expect failures to happen regularly and handle them gracefully?
• Have we kept things as simple as possible?

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1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

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Direct links to free Springer books (pdf versions)

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

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Persistent data storage on CoreOS-cluster

Storing the data on the host machine

Data directories are created in /home/coreos and mounted into the container using volume cli options of docker run. All data the container writes is stored on the host and as long as the host persists safe against container restarts / recreates.

• Pro
  • No effort, just create the directories and mount them into the container
• Contra
• Container is bound to host (unable to failover)

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location /webhook/17cbb307-94ec-446b-a17b-ab82594c974c {
  if ($request_method != 'POST') {
    return 405;
  }
  content_by_lua 'ngx.print(io.popen("/path/to/script.sh"):read("*a"))';
}