Hot Scalability Links for May 14, 2010

Lots of good ones this week...

• Scalability, Availability & Stability Patterns. Jonas Boner has 197 slides covering a very wide range of scalability topics. One stop scalability shopping.
• Horizontal Scalability via Transient, Shardable, and Share-Nothing Resources. Heroku's Adam Wiggins shares what they've learned about scaling based on their experiences building a cloud platform and the hundreds of apps running on it. He describes the next generation architecture he thinks all software should follow in the future.
• Scalability of the Hadoop Distributed File System. Konstantin V. Shvachko writes a great post analyzing if the limitations imposed on a distributed file system by the single-node namespace server architecture can support 100,000 clients and petabytes of files.
• Cassandra by Example. Eric Evans created a nice Cassandra tutorial using building a Twitter clone as an example. Many people want to see more data modeling examples. Here you are.
• UpSizeR: Synthetically Scaling Up a Given Database State. In this video Y.C. Tay talks about how to make bigger databases from smaller databases for easier testing.
• Inter-Datacenter Replication & Geo-Redundancy. James Hamilton ask why don’t all workloads run in multiple datacenters? 1) scale, 2) latency, and 3) WAN bandwidth and costs.
• Varnish best practices. Kristian Lyngstol assist in pitfall-avoidance when using Varnish.
• Mapreduce & Hadoop Algorithms in Academic Papers. Learn from academic literature about how the mapreduce parallel model and hadoop implementation is used to solve algorithmic problems.
• Hot Potato Infrastructure: MongoDB. But personally, I don’t think Mongo’s ability to scale out has gotten enough attention.
• That No SQL Thing: Scaling Graph Databases. Ayend Rahien - I believe that while you can shard a graph database, it place a very lot limit on the type of graph walking queries you can make.
• Scaling Python for High-Load Web Sites. David Shoemaker & Jamie Turner show how to make a scalable Flickr Killr using Python.
• Using caching and optimization techniques to improve performance of the Ensembl website. Solutions included optimization of the Apache web server, introduction of caching technologies and widespread implementation of AJAX code.
• Should I buy a Fast SSD or more memory? by Vadim from the MySQL Performance Blog.
• Building a world class infrastructure. A.J. Clark describes the key parts of an infrastructure: Internal DNS, Asset DB/CMDB, Provisioning, Configuration Management, Version Control, Application Release Procedure, Health Checks, Job Server, CDN, External DNS, Agile Methodology, Change Control for an Agile Business, Rationalizing Backups, Other Technologies.
• Mashups with the Facebook Graph API and Neo4j. Today, we're going to show you how easy it is to use the Facebook Graph API to mash up data from Facebook with data in a locally hosted graph database!
  
  

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