Yesterday, Google launched "Google Art Project" in collaboration with 17 of the world's most renowned museums -- which's built on top of App Engine and lets you take virtual tours of famous museums using internal Street View technology, view high resolution images of famous art work, and create personal virtual artwork collections.
When Art Project started development several months ago, the team built the app using Java and the Master/Slave Datastore. However, as their launch date approached they decided to switch over to the High Replication Datastore. Below are the mean numbers for latency of different parts of the site:
Here's a description of what each page does behind the scenes:
- Homepage is just a landing page that serves a static webpage for site navigation -- has the latency is stable.
- Collections: Art Project lets users create individual museum collections. These load tests specifically targeted adding and deleting paintings from a user's personal collection, as well as rendering those collections -- has slightly increased latency from saving and deleting entities in the datastore.
- Level Maps: These pages simply performed get() calls on the datastore using entity keys -- has consistent latency across instances.
- Info Spots performs the most data intensive calculations of all of the handlers. It calculates all line of sight interest points for a user's map position in a museum gallery room, and saves the points of interest to the datastore for that location. The good news is, this calculation doesn't have to happen for every user. Once this data has been calculated for a given spot, it can re-used for other visitors to the site.
[tags]latency,high replication datastore,20-precent,art project,digital camera,museum,museums,photos,street view,zoom[/tags]