In the post Political Streams Online (work blog) I mentioned that I left my fingerprints on Social Streams, the platform underneath Political Streams. For those who followed my work for a while the connections are probably obvious. For those who’d like to get oriented here are a few starting points:
- Streams fit right into data flow architectures. A Data Flow Pattern Language covers sources, filters, and sinks, as well as how they interact with each other.
- Aggregating data from heterogeneous sources is an integration problem. Integration Patterns discusses many proven techniques for tackling those problems.
Several threads that we put on the table at last week’s workshop in Zuerich did not get sufficient traction to tackle with the workshop’s participants. However that doesn’t mean that they’re not worthy of pattern mining; on the contrary.
Consider for example scalability and viral spread. There are well known techniques and patterns for designing high-capability Internet-based systems.
However, in a Web 2.0 world, particularly when there is potential for network effects, a site may become popular very quickly. How do you design a system that may need to scale to 1 million users in less than 2 months? I offered iLike as an example, but that was as concrete as we got at the workshop.
Back in Redmond my colleague Greg Linden pointed me to a Q&A with Ali Partovi of iLike.com. While the conversation doesn’t go into the technical details, the numbers speak for themselves:
In terms of daily signups, iLike on Facebook trounces anything else we do… iLike on Facebook has been signing up roughly 200,000 new members a day.
Viral spread made possible by social networking adds an interesting twist to scalability. I hope than an increasing number of designers will start talking about their solutions. If you’re interested in sharing data points or articulating them as Web 2.0 patterns, head over to our pattern Wiki. As the iPhone 3G launch demonstrated just a few days ago, miscalculations have the potential to inflict major frustrations with customers, as well as make the headlines.