PUBLIC MARKS with tags cluster & file

Many people use SSH to log in to remote machines, copy files around, and perform general system administration. If you want to increase your productivity with SSH, you can try a tool that lets you run commands on more than one remote machine at the same time. Parallel ssh, Cluster SSH, and ClusterIt let you specify commands in a single terminal window and send them to a collection of remote machines where they can be executed. Why you would need a utility like this when, using openSSH, you can create a file containing your commands and use a bash for loop to run it on a list of remote hosts, one at a time? One advantage of a parallel SSH utility is that commands can be run on several hosts at the same time. For a short-running task this might not matter much, but if a task needs an hour to complete and you need to run it on 20 hosts, parallel execution beats serial by a mile. Also, if you want to interactively edit the same file on multiple machines, it might be quicker to use a parallel SSH utility and edit the file on all nodes with vi rather than concoct a script to do the same edit. Many of these parallel SSH tools include support for copying to many hosts at once (a parallel version of scp) or using rsync on a collection of hosts at once. Because the parallel SSH implementations know about all the hosts in a group, some of them also offer the ability to execute a command "on one host" and will work out which host to pick using load balancing. Finally, some parallel SSH projects let you use barriers so that you can execute a collection of commands and explicitly have each node in the group wait until all the nodes have completed a stage before moving on to the next stage of processing.

Every day, search companies like Google download terabytes of data from the Internet, store it on clusters of thousands of machines, and process it so that it can be easily searched. To make this possible, these companies need sophisticated distributed file system and parallel programing architectures. Have you ever heard of the Map/Reduce distributed parallel programing paradigm? If you are a computer scientist, you should have, because every time you submit a Google search, you are using Map/Reduce. Despite growing demand from companies like Google, Yahoo, and Microsoft, few computer science majors have even heard of Map/Reduce, let alone graduate well versed in its use. Unfortunately, several barriers exist to integrating Map/Reduce into computer science curricula. Obtaining a large cluster, configuring it, and installing complicated distributed file system and parallel programing software is difficult, time consuming, and expensive. In the past, Google's solution to this problem has been to ship entire clusters pre-configured with Map/Reduce software to select universities. In essence, Vdoop does same thing, with exactly the same software, except for our clusters are virtual, and hence free.

The idea behind the whole set-up is to get a High availability two node Cluster with redundant data. The two identical Servers are installed with Xen hypervisor and almost same configuration as Cluster nodes. The configuration and image files of Xen virtual machines are stored on drbd device for redundancy. Drbd8 and OCFS2 allows simultaneous mounting on both nodes, which is required for live migration of xen virtual machines. This Article describes Heartbeat2 Xen cluster Using Ubuntu (7.10) OS, drbd8 and OCFS2 (Ver. 1.39) File system. Although here Ubuntu is used it can be done in almost same way with Debian

This Article describes Heartbeat2 Xen cluster Using Ubuntu (7.10) OS, drbd8 and OCFS2 (Ver. 1.39) File system. Although here Ubuntu is used it can be done in almost same way with Debian Idea The idea behind the whole set-up is to get a High availability two node Cluster with redundant data. The two identical Servers are installed with Xen hypervisor and almost same configuration as Cluster nodes. The configuration and image files of Xen virtual machines are stored on drbd device for redundancy. Drbd8 and OCFS2 allows simultaneous mounting on both nodes, which is required for live migration of xen virtual machines.

Ever had to make the same change on more than one Linux/unix server? Find it annoyingly painful to keep repeating the exact same commands again and again and again? This tool addresses exactly this problem. You run a utility (cssh) providing a number of server names as parameters, and then xterms opens up to each server with an extra “console” window. Anything typed into the console is replicated into each server window (so, for examples, you can edit the same file on N machines at the same time, or run the same commands with the same parameters across those servers). It is also possible to type into the server windows directly, or temporarily disable replication to one or more of the servers through the “Hosts” menu.

Subcon allows you to store your essential system configuration files in a subversion repository and easily deploy different configurations to machines in a cluster. It also features optional integration with SystemImager, enabling the deployment of system images and configuration in a single step. A flexible configuration file provides the ability to start, stop, or restart services or run arbitrary scripts when a change in a file or set of files is detected.