With the release of the Sun Storage 7000 line of storage appliances, Sun has included a new “Analytics” toolkit. These analytics are based on DTrace (http://en.wikipedia.org/wiki/DTrace), but essentially hide the DTrace complexity in a cloak of Ajax-based browser graphics. Through the GUI, a storage administrator can determine which clients are causing which files on the server to be “hot”, or resource use-intensive. Also the administrator can see the latency of each request to the blocks of that file, or how many request of each protocol are being processed, or how many cache hits a file had. In this blog I’ll explore the basics of Analytics.

The analytics component of the Sun Storage 7000 line can provide useful information to a storage administrator who is trying to manage and monitor the appliance and the files and blocks stored there. Just like DTrace, the analytics run in real time, and allow quick progression from hypothesis through data gathering to new hypothesis, data and conclusions. Unlike DTrace, the analytics component has a very complete and useful graphical interface and visualization engine.

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Hierarchical Storage Managementement (HSM), Information Lifecycle Management (ILM), and Data Lifecycle Management (DLM). Everyone wants to manage their data intelligently to reduce their spending on storage infrastructure. The storage vendors and the trade rags would like to convince us that there are magic tools to solve this challenge. The truth is there is no magic tool to manage unstructured data. (I am not talking about the archiving tools that integrate with application here, I am only talking about unstructured data.) I have tried many tools over the years and they are simply not cost effective. Don’t panic though, in most cases, the solution is far simpler and far less expensive than HSM.

File services is a huge consumer of storage capacity. For the purposes of this conversation, let’s consider file services as NFS or CIFS storage whether they be integrated appliances or a servers leveraging back end storage devices. In most environments I visit, the file serving infrastructure is using tier 1 disk drives (fibre channel, SCSI, or SAS). These disk drives are populated with data that is mostly idle and the storage managers want to get that idle data onto a less expensive disk tier. The most common request is to transparently move the idle data to a SATA based devices.

Let’s walk through this the scenarios for an environment with 20TB of unstructured data.

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