I don’t like bowling. It seems to me that a robot would be a better bowler than a person — there’s no judgment required, as it’s the same target every time, with no wind shifts, defenses to consider, or human factors that add nuance to the game. Sure, it’s hard to repeat the optimal bowl every frame to hit the perfect score of 300, but if you designed a machine with close enough tolerances to do the exact same thing every time, it would always be better than a human.
If you pay any attention to data storage, you’ve heard of files, blocks, and objects many times, but do you really know what they mean and where you would use each of them?
We are used to the notion of virtualization in our modern computing infrastructure. Virtual memory has been a fundamental concept in many operating systems for years; virtual disks, virtual machines, and virtual networks are all commonplace in today’s IT environments.
Virtualized access to networked file systems has been available for many years via Microsoft’s Distributed File System (DFS), although few IT shops take advantage of this powerful technology.
Every day I read about how a company raised “X Millions” from a VC, and it is broadcast across all media outlets. The round of funding varies depending on the stage of the company. The early-stage companies have either no revenue or minimal at best, and most of these companies are selling a vision that, in today’s marketplace, venture capitalists don’t want to miss out on. There are many VCs that may have passed on Uber or Facebook or LinkedIn and feel that they definitely don’t want to repeat that mistake.
These early-stage companies are getting valuations that are astronomical in any historical sense. I recently read an article where a company that is still pre-revenue received a $200 million dollar plus valuation. These early-stage companies are typically raising $1+ million, and lately it seems like that amount has increased to $10 million+.
Our technology partner NetApp has had a rough go over the last several weeks, starting with the announcement of lower than predicted revenues, which was followed by the firing of CEO Tom Georgens, their leader since 2009. Much of the problem revolves around the difficulty customers are having in migrating to new systems running Clustered Data ONTAP.
This is a subject that we at Data Dynamics are quite familiar with; our StorageX software platform has helped multiple customers move data from 7-mode systems to those running Clustered Data ONTAP quickly, reliably, and without the complexity and uncertainty of scripting or swing space targets.
In a previous article, I stated that StorageX is multi-threaded. I also spent quite a bit of time discussing why I consider this fact to be (mostly) irrelevant to the administrator who is using StorageX to perform his file system migrations. What the user of StorageX really wants is for StorageX to do its job as fast as possible: when he is doing a baseline copy, he wants StorageX to fill his network pipe and move the data as quickly as possible, and when he is cutting over to his shiny new NAS hardware, he wants StorageX to do the final incremental copy within his allotted cutover window.
As I mentioned in my previous article, the techniques StorageX uses to fill the network pipe during a baseline copy are very different from those used to find changed files as quickly as possible during an incremental copy. In this article, I will focus on baseline copies.
Running a start-up is considered in vogue these days, with venture firms pumping money into new ideas and innovations at record valuations. Most entrepreneurs are extremely excited and passionate about their product or solution and want to have global adoption as quickly as possible. After spending a majority of time developing a software or product, that anticipation starts to build, as we look to take our “baby” to market.
In the myriad of this excitement, we as CEOs of these companies start pushing aggressively to bring in sales and revenue, as that is the “lifeline” of any start-up. Every day we get up dreaming of how quickly can we sign up that first customer or build out a partnership which will lead us to our first major revenue milestone.
There are two essential ways to migrate a large amount of data “quickly”:
- Migrate data until the data window closes. The next time the window opens, pick up where the migration left off.
- Migrate data until the data window closes. The next time the window opens, start at the beginning again and check for changes.
There are pros and cons to both methods. It’s tempting to think the first method would be the fastest/best, since getting a “baseline” copy of all the data would be done first. The data set would then just have to go through some sync copies, and then you can change over to the new destination.
On several occasions, I have been asked a question that is straightforward to answer, but where I’m left with an uneasy feeling about why the question was being asked in the first place. For example, about a year ago I was asked, “Is StorageX multi-threaded?”
That’s a seemingly reasonable question, and a correct answer is easy to give: yes.
I suspect the person who asked the question would have been happy with that basic answer. He would have understood it (“yep, they have multiple threads in their program…that’s good, right?”) and he could easily convey the answer to whoever asked it of him. Most likely the question originated with a piece of marketing collateral for a competing product, touting how the product is “multi-threaded so that it scales to the available hardware” or some such seemingly wonderful claim.
The 2014 Red Herring Top 100 North America winners were announced in Monterey, CA. The Red Herring’s editorial staff evaluated the a number of companies on both quantitative and qualitative criteria, from financial performance to technology innovation and from intellectual property to management quality, business model, customer footprint and market penetration.