scalelite
scalelite
Scalable load balancer for BigBlueButton.
BigBlueButton is an open source web conferencing system for online learning.
Scalelite is an open source load balancer that manages a pool of BigBlueButton servers. It makes the pool of servers appear as a single (very scalable) BigBlueButton server. A front-end, such as Moodle or Greenlight, sends standard BigBlueButton API requests to the Scalelite server which, in turn, distributes those request to the least loaded BigBlueButton server in the pool.
A single BigBlueButton server that meets the minimum configuration supports around 200 concurrent users.
For many schools and organizations, the ability to 4 simultaneous classes of 50 users, or 8 simultaneous meetings of 25 users, is enough capacity. However, what if a school wants to support 1,500 users across 50 simultaneous classes? A single BigBlueButton server cannot handle such a load.
With Scalelite, a school can create a pool of 4 BigBlueButton servers and handle 16 simultaneous classes of 50 users. Want to scale higher, add more BigBlueButton servers to the pool.
BigBlueButton has been in development for over 10 years now. The latest release is a pure HTML5 client, with extensive documentation. There is even a BigBlueButton install script called bbb-install.sh that lets you setup a BigBlueButton server (with a Let’s Encrypt certificate) in about 15 minutes. Using bbb-install.sh you can quickly setup a pool of servers for management by Scalelite.
To load balance the pool, Scalelite periodically polls each BigBlueButton to check if it is reachable online, ready to receive API requests, and to determine its current load (number of currently running meetings). With this information, when Scalelite receives an incoming API call to create a new meeting, it places the new meeting on the least loaded server in the pool. In this way, Scalelite can balance the load of meeting requests evenly across the pool.
Many BigBlueButton servers will create many recordings. Scalelite can serve a large set of recordings by consolidating them together, indexing them in a database, and, when receiving an incoming getRecordings, use the database index to return quickly the list of available recordings.