InfoQ Homepage Performance & Scalability Content on InfoQ
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Abstractions at Scale–Our Experiences at Twitter
Marius Eriksen considers that leaky abstractions lead to scalability issues, while those providing narrow access to explicit resources - map-reduce, shared-nothing web apps, big table - scale better.
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Development at the Speed and Scale of Google
Ashish Kumar on how Google keeps the source code of over 2000 projects in a single code trunk containing 100s of M of code lines, with more than 5,000 developers accessing the same repository.
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The Evolution of the Flickr Architecture
Mikhail Panchenko discusses how Flickr’s code base developed over the years and the scalability problems that started to appear, presenting the the improvements and pros/cons of technologies used.
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Scaling Australia's Most Popular Online News Sites with Ehcache
A real-world experience of implementing Ehcache at Australia's most visited online news site. How to deal with high traffic, concurrency, and how to implement linear scalability.
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Fast Enough
Cliff Moon explains how to make Erlang programs faster by writing performance critical sections of the code in C using NIFs and by integrating libraries using the linked-in driver interface.
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Performance Testing at the Edge
Alois Reitbauer shows how to do performance testing during development, testing, and production by starting early in the development phase, breaking the test into pieces, and testing continuously.
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Neo4j: NOSQL and the Benefits of Graph Databases
Emil Eifrem overviews the trends leading to NOSQL, and four emerging NOSQL solutions. He also explains the internals of a graph database and an example of using Neo4j – a graph DB - in production.
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Social Networks: Getting Distributed Web Services Done with NoSQL
Lars George and Fabrizio Schmidt present Germany’s largest social networks, Schuelervz, Studivz and Meinvz, the initial architecture, why it didn’t work and how they solved it with a NoSQL solution.
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Embracing Concurrency At Scale
Justin Sheehy explains the principles behind concurrent distributed systems: no global state, no ACID but rather BASE, no RPC but protocols over APIs, prepare for failure, degradation, measurement.
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Project Voldemort at Gilt Groupe: When Failure Isn't an Option
Geir Magnusson explains why Gilt Groupe is using Project Voldemort to scale out their e-commerce transactional system, what are the benefits and what is the current architecture after ditching SQL.
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Scaling Your Cache & Caching at Scale
Alex Miller presents typical difficulties encountered when setting up a cache, plus available choices for designing a distributed caching architecture, and ways to test a cache for performance.
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The Wizardry of Scaling
Oren Eini presents several architectural concepts – divide and conquer, background evaluation, one way messaging, the single responsibility principle - helpful to build highly scalable systems.
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