This morning Hitachi Data Systems announced the addition of the Hitachi Data Replicator to our portfolio of replication and data protection software. This product is the result of a partnership with InMage Systems which was founded by our good friend Kumar Malavalli, founder and CTO for Brocade Communications and Rajeev Atluri from Gadoox. The Hitachi Data Replicator is a software replication solution that is targeted at the midrange market where a simple, cost effective, disaster recovery solution is required for a heterogeneous server and storage environments.
What do we mean by scale up versus scale out? If you go to Wikipedia you will find a section under the definition for scalability for “Scale vertically vs. horizontally”.
SearchStorage ANZ’s Simon Sharwood posted an article referencing a NetApp presentation which was posted on a public RSS feed that NetApp provides for its user community.
I visited a customer last week who was trying to run four 6 node ESX clusters with 200 to 240 instances per cluster on a large modular storage system. It was not surprising that the modular storage system could not support that workload. That type of workload needs to be run on a monolithic storage array that can scale up.
In April I wrote about our “Switch IT On” program, which provides free software licenses to help current and new USP V customers leverage virtualization across their existing HDS and third party storage assets. The program has proven to be so successful that HDS decided to add Switch IT On II, and both programs will run through the end of March 2010. For details on both programs please visit here.
Monolithic Storage Systems Developed for Mainframe Virtualization
Having been in the storage industry for some time now, I have the benefit of historical perspective. I started out when mainframe storage was the only external storage available. Mainframes were the original virtual server, built for running multiple partitions of concurrent applications which drove tremendous I/O loads across special processors called channels. In order to support this type of workload, storage vendors had to build monolithic storage systems, that had multiple processors on the front ports to match the I/O load of the channels, a large global cache that could serve a consistent cached data image to multiple, load balancing, storage port processors, back end processors that could write the data to backend storage, and still other processors that could move data for business continuity. EMC developed the Symmetrix; IBM developed the Shark; and Hitachi developed the Freedom 7700 built around these features to address the I/O requirements of mainframe virtual servers. With a global cache, monolithic storage systems can scale up and out by adding front end processors, back end processors, and cache modules.
Hitachi Data Systems announced a new portfolio of cloud technologies that delivers an integrated set of storage services across block, files and content storage to support cloud computing and enable organizations to implement cloud services at their own pace.
On my previous post, which was titled, I Agree With Chuck on Data Dedupe” I received a fair number of comments. Some were from Jered Floyd of Permabit and even one from Steve Duplessie . My post was intended to point out that while dedupe was an excellent tool for reducing storage bloat, it was addressing the symptom and not the cause which was stale data and over allocation at the source.
Chuck Hollis had an interesting observation on deduplication of primary data and I/O density. He points out that while deduplication is great for backup, archive, and large file repositories, it might not be as great for primary data. His reasoning is that dedupe can cause an increase in I/O density which may impact the performance of primary data and negate the value of space savings that dedupe could bring. He goes on to say that the current work arounds for the I/O density problem, more disks and/or faster disks, defeat the premise of using dedupe for saving disks and reducing costs.
ILM Revisited: Intelligent Tiered Storage for File and Content Data
By: Hu Yoshida on September 28, 2009
I am taking a break from the blogging wars over virtualization to plug a Webcast that I will be doing on The economic Benefits of Intelligent File Tiering. It will be on Wednesday, September 30 from 9:00 am to 10:00 am. You can go to this website to register.
