99Designs Architectual Overview

The Design of 99designs – A Clean Tens of Millions Pageviews Architecture

99designs is a crowdsourced design contest marketplace based out of Melbourne Australia. The idea is that if you have a design you need created you create a contest and designers compete to give you the best design within your budget.
If you are a medium sized commerce site this is a clean example architecture of a site that reliably supports a lot of users and a complex workflow on the cloud. Lars Yencken wrote a nicely written overview of the architecture behind 99designs in Infrastructure at 99designs. Here’s a gloss on their architecture:

•    Team has 8 devs, 2 dev ops, 2 ux/designers
•    Hundreds of thousands of unique visitors a month
•    Tens of millions pageviews a month
•    Largely an Amazon based stack
•    Elastic Load Balancer (ELB)
•    Varnish
•    PHP with Apache/mod_php
•    S3
•    Beanstalk for in-memory queing using Pheanstalk bindings
•    Amazon’s RDS (MySQL)
•    Memcached
•    MongoDB
•    Redis
•    Rightscale/Chef
•    NewRelic, CloudWatch, Statsd
•    Layered architecture: load balancing, acceleration, application, asynchronous tasks, storage and transient data.
•    ELB is reliable and handles load balancing and terminating SSL connections so that traffic is unencrypted below the ELB. A separate ELB is used for each domain.
•    Varnish is used to serve file based long tail media.
•    Varnish is fast, configurabe, has a DSL, and has useful command line tools for debugging live traffic.
•    Dynamic and uncached requests are served from a PHP application.
•    Designs are stored on S3.
•    S3 latencies are poor so designs are cached locally after each request.
•    Requests that may take a long time are asynchronously queued to an in-memory queue implemented using  Beanstalk, which is lightweight and performs well.
•    PHP workers read work off the queue and execute the required functionality.
•    Scheduled jobs are queued using cron at the appropriate time.
•    Amazon’s RDS is used as the database and uses master-master replications across multiple availability zones for redundancy.
•    Rolling RDS backups are used as disaster discovery.
•    As load increases requests are load balanced across the read slaves.
•    S3 stores media files and data files.
•    Backups are made to Rackspace and Cloudfiles for disaster recovery.
•    Memcached is run on every server and is used to cache queries.
•    Capped collections in MongoDB are used to log errors and statistics.
•    Redis stores per-user information about which features are enabled for a user.
•    Per user configuration is used for dark launches, soft launches and incremental feature rollouts.
•    Amazon allows them not to own any hardware and remain flexible.
•    Emphasis on automation using “software as infrastructure” ethos.
•    Rightscale manages servers configurations using Chef. Servers are disposable.
•    Monitoring is implemented using NewRelic, CloudWatch, Statsd. Two large monitoring screens display a dashboard of site behavior.
Lessons Learned
•    Test to scale down. Highly variable load means they make heavy use of the cloud’s scaling down capability, which requires a lot of testing to make work.
•    International customers need a CDN. They have a lot of international customers and since they serve out of US-east these customers don’t always get a quality experience. They are looking at various CDNs to give better service to international customers.
•    Maintaining stability while growing requires testing and automation. To support frequent releases they are implemented acceptance testing and more automation. The ability to turn features on and off on a per user basis allows testing new features against a subset of users.

Originally posted at http://highscalability.com/blog/2012/2/6/the-design-of-99designs-a-clean-tens-of-millions-pageviews-a.html

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