Guard Against Data Loss with Mondo Rescue
Good backup software must be well documented, well tested and easy to use. If the backup software is too fiddly then the user simply will not bother. If it is unreliable, then the user will be lulled into a false sense of security, only to have his or her hopes dashed when the crunch comes. I back up my own system with Mondo two or three times a week. I restore regularly as part of the test regime.
If you want to participate, please download the program and join the mailing list. I would love to hear from you.

Hugo Rabson is a 26-year-old Briton living and working in Nashville, Tennessee. His primary qualification is in business, but he has been writing code since puberty. He currently works for WebMD. Mondo is his attempt to give something back to the Linux community, and he gladly will accept all comments, suggestions and patches.
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Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
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Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?




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