high_scalability high_scalability-2009 high_scalability-2009-674 knowledge-graph by maker-knowledge-mining

674 high scalability-2009-08-07-The Canonical Cloud Architecture


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Introduction: Update 2: Elastic Load Balancer and EC2 instance bandwidth . It turns out we are limited by bandwidth and not by CPU . Solution: use DNS Round Robin for two to three HighCPU medium instances . Update: The Skinny Straw: Cloud Computing's Bottleneck and How to Address It . For cloud computing, bandwidth to and from the cloud provider is a bottleneck . Solution: Evaluate application architecture and consider application partitioning . I'm writing this post as a sort of penance. My sin was getting involved in another mutli-threaded mess of a program that was rife with strange pauses and unexpected errors. I really should have known better. But when APIs choose to make callbacks from some mystery thread pool it's hard to keep things straight. I eventually sobered up and posted all events to a queue so I could make sure the program would work correctly. Doh. I may never know why the .Net console output stopped working, but I'll live with it. And that reminded me that I've been m


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 For cloud computing, bandwidth to and from the cloud provider is a bottleneck . [sent-5, score-0.364]

2 I eventually sobered up and posted all events to a queue so I could make sure the program would work correctly. [sent-11, score-0.478]

3 The easiest way to create a scalable service is to compose the service from other scalable services. [sent-17, score-0.32]

4 The canonical cloud architecture that has evolved revolves around dynamically scalable CPUs consuming asynchronous, persistently queued events. [sent-19, score-0.496]

5 SmugMug's Cloud Architecture AWS pioneer Don MacAskill of SmugMug details how they process high-resolution photos and high-definition video use a cloud hosted queuing architecture in SkyNet Lives! [sent-27, score-0.375]

6 SkyNet, as you might expect, operates completely without human minders and automatically scales up and down in relation to the work load. [sent-29, score-0.291]

7 Their system has several components: Work Initiators - Work comes in from your website and/or other software subsystems and is queued up for processing in the Queue Service. [sent-30, score-0.263]

8 Provisioning Service - This is Amazon's infrastructure that allows instances to be automatically scaled up and down in relation to the work load. [sent-35, score-0.291]

9 Queuing Service - This is where work is queued for consumption by the workers. [sent-40, score-0.239]

10 Creating a scalable, distributed, performant, highly available queue service is not easy, so you may want to take a look at a number of different queue product suggestions in Flickr - Do the Essential Work Up-front and Queue the Rest . [sent-42, score-0.493]

11 Controller - This component monitors many variables related to the work flow and decides how many instances of EC2 are necessary based on optimizing a small set of goals. [sent-43, score-0.267]

12 Don shares a lot of practical detailia on how to efficiently use AWS, how their queue service works, and how their controller manages to balances minimizing cost while still being responsive to users. [sent-45, score-0.283]

13 Achieving fairness and balance in a queue system can be difficult, but SmugMug appears to have done a good job of that. [sent-46, score-0.264]

14 If one component is producing events too fast the queue will buffer up events until they can be processed. [sent-50, score-0.48]

15 The idea is to take an unpredictable but possibly large number of search requests, apply the search expression to hundreds of terabytes of documents, and return the results in a reasonable period of time. [sent-63, score-0.268]

16 To coordinate and dispatch work you need a queuing service like SQS. [sent-67, score-0.35]

17 The paper makes several key architectural recommendations: Use Scalable Ingredients - Ensure that your application is scalable by designing each component to be scalable on its own. [sent-75, score-0.302]

18 If every component implements a service interface, responsible for its own scalability in all appropriate dimensions, then the overall system will have a scalable base. [sent-76, score-0.342]

19 If any component fails (and failures happen all the time), the system should automatically alert, failover, and re-sync back to the “last known state” as if nothing had failed. [sent-83, score-0.258]

20 The cloud makes all the necessary components standard, featureful, and relatively inexpensive. [sent-91, score-0.28]


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