2.  Load balancing is the process of distributing a workload evenly throughout a group or cluster of computers to maximize throughput.  This means that workload on individual nodes is reduced, and multiple nodes work together to complete tasks.

4.  High availability clusters allow systems to run continuously even if an error occurs on one ore more nodes.  This works by having multiple redundant nodes in a cluster, each monitoring another with Heartbeat to detect failures, and ready to deploy at any time.

5.  High availability is implemented in almost all cluster systems today.  Most useful in the following systems: › Critical Databases › E-commerce Websites › Network File Sharing  In all of the above systems, any downtime or loss of data is a major problem for business or security.

7.  Apache (or Apache 2.0 for this project) is an open-source, web server software maintained by an open community of web developers.  We chose Apache for ease of use and its readily available packages and support for our heartbeat and high availability on our Unix based system.

8.  Our goal for this project was to create a load balanced, high availability Apache cluster with the following software: › Ultra Monkey › Heartbeat › Apache 2.0  This was set up on a four-node cluster with all computers running Ubuntu 8.04

9.  Apache node 1: IP address: 190.111.50.201; Apache document root: /var/www  Apache node 2: IP address: 190.111.50.202; Apache document root: /var/www  Load Balancer node 1: IP address: 190.111.50.203  Load Balancer node 2: IP address: 190.111.50.204  Virtual IP Address: 190.111.50.205 (used for incoming requests)

10.  After installing Ubuntu 8.04 on all of the nodes, we had to set up the two Apache nodes: › Installing the proper packages. › Setting up the ethernet configurations in /etc/init.d/network › Configuring the web page in the proper directory › Creating and ensuring redundancy between the two individual Apache server nodes.

11.  Once the Apache nodes were set up, we configured the load balancing nodes with Ultra Monkey.  Most of the issues encountered during configuration occurred during this step.

12.  Our load balancing system uses the Linux based project, Ultra Monkey.  We chose this software as it is freeware, able to run on any size cluster that is needed, and able to run on any OS.  Ultra Monkey also includes the package for Heartbeat protocol, which sends scheduled messages through the system and listens for replies, to check for downed nodes.  If a node is found to be down, due to lack of Heartbeat response, the node assumes the other has failed and takes action.

13.  The following steps were used to configure load balancing on our nodes: › Installing proper packages › Setting up ethernet configurations in /etc/init.d/network › Installing and configuring Ultra Monkey › Setting up Heartbeat

14.  Some of the major issues encountered during this project involved the Ultra Monkey configuration.  Was mainly trial and error during configuration due to lack of documentation some places and poor or incorrect documentation others.  Did intensive testing and studying to find the correct commands and protocol for setting up the system.

15.  A problem which stalled our project for a long period of time was the firewall. › Not thought to be an issue at all. › After working for hours trying to find out why our setup wasn’t connecting between nodes, we disabled. › Project worked perfectly after this.

16.  In order to test our four-node system, we sequentially cut off machines, both load balancing nodes and Apache nodes in order to see if the system would stay up and online.  The load balancing service was maintained through this process, and the secondary Apache server was able to flawlessly step in when the other was brought down without interrupting service.

17.  It’s easy to see how this project is easily applicable to real world scenarios, as most companies will implement this technology for their cluster systems.  Our setup was for a small cluster, and we didn’t do much optimization; but with the customization options available, load balancing can greatly optimize a system’s capacity.