By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.
Separate critical data
The storage administrator must make sure that the planning and conceptualizing are all in place to take advantage of the technology you are involved with. Technology without proper planning and procedures -- management, in a word -- is useless, and, in fact, can get you into real trouble. This tip discusses a management procedure to separate your critical data into separate "piles" so that when you are ensuring data reliability, you do the most important thing first.
Not all data is created equal and smart storage administrators take advantage of this fact in creating backup strategies. Different classes of data can be treated differently to reduce restore times as well as to offer different levels of access in case of data loss.
Business-critical data especially needs to be treated differently. Because enterprise functioning is seriously impaired, or even halted completely, when this information is not available, it is worth taking special precautions with it.
The most obvious precaution is to mirror business-critical data so that it is available even if the primary storage system fails. This doubles the storage capacity needed, but the increased availability of critical data is often worth it.
To speed restoration, administrators can limit the volume size for critical data. Smaller volumes, or smaller qtrees, reduce the time it takes to back up and restore each volume from tape.
Another precaution is to make frequent copies of the critical data so the minimum amount is lost in the event of a failure.
These strategies are briefly discussed in the context of NAS filers in a white paper titled "Data Protection Strategies For Network Appliance Filers" which is available on the Network Appliance web site at www.netapp.com/tech_library/3066.html.
1. How many terabytes should my storage employees manage?
One way to measure the effectiveness of a storage management operation is to look at the amount of data managed per storage management employee. This is significant since trained storage administrators are in short supply and employee costs are a major factor in the cost of managing storage. This tip offers some rules of thumb regarding terabytes per storage manager and has an interesting counter-argument from a searchStorage reader.
2. What are some policies for LAN data storage management?
Poster "richardkh" says his company is developing a LAN data management schema in order to effectively manage its storage. He believes the key to effective data storage management is in using "a combination of management tools, policies and automated enforcement systems." For more on the types of policies he's considering, read the full post. Lots to chew on in here for storage administrators grappling with the same issues!
3. How can I get the info I need to troubleshoot storage?
Troubleshooting storage systems all to often runs into a problem of granularity versus universality, according to the expert cited in this tip. In other words, to effectively identify the problem you need very detailed information, but the software that will let you manage multiple vendors' products usually can't provide that level of detail. What to do? Here are some suggestions.
4. What are the challenges involved in migrating data?
Poster "HungryJack" wanted to know the challenges involved in migrating data from old subsystems to newer ones (such as SCSI to FC). He also had some questions on replicating volumes for Solaris or Windows. Check out his post and poster "D's" answer. You might be able to offer some other input for him as well.
Rick Cook has been writing about mass storage since the days when the term meant an 80K floppy disk. The computers he learned on used ferrite cores and magnetic drums. For the last twenty years he has been a freelance writer specializing in storage and other computer issues.
Dig Deeper on Data management tools