Voice of the DBA

Author: way0utwest

SQL Clone at Scale with Striped Backups

I had a customer recently reach out to ask if SQL Clone would work with 20 backup files. I decided to test this.

This is part of a series of posts on SQL Clone, which is a virtualization product from Redgate Software.

The Scenario

A customer asked about SQL Clone working with a lot of backup files (striped), like 20. Our support org said this should work and handle the max number of files, which is 64 for the backup command.

I know SQL Clone works with striped backups because I wrote an article on it, but I only tested 7 files. How to test more than that?

First, get the backups. To do this, I used a GenAI to quickly get me a command. Once I had this, I ran it and got a lot of files.

Now to get the SQL Clone image.

Image Creation

I decided to start with the GUI. This has changed since I wrote the article in that it now puts each file in a separate text box. By default you get two. I pasted in my file path and file, and then copy/pasted in the 2nd box. I continued adding them, clicking the “Add another file” at the bottom each time (see the image).

It was tedious, but it was a quick way of testing this. I likely would have taken longer than the 3-4 minutes of copy/pasting to write a PoSh script (though I need to do that). You can see most of my files below.

Once I had 32 of them, I clicked “Continue” and entered the name and location for my image. Then clicked “Create”.

It worked. The image shows my SQL Clone image being created successfully and a clone from this image.

These were small files, so the restore time was quick. Each is about 3MB, so we’re not looking at much.

Summary

This shows that SQL Clone can work with 32 files. I assume it works with 64, but that will have to wait until I have time to mess around with the PoSh to make the image command creation easy.

If you are looking to save storage space for multiple copies of databases, or give each user a consistent copy in seconds, check out SQL Clone.

Video Walkthrough

See this article in video below.

October 27, 2025
Can/Can’t Do/Don’t

The other day, I asked my daughter if she wanted me to make her some eggs. She responded with a “Yes!” in text and came to sit up at the counter while I cooked for us both. We chatted a bit, and at one point she said, “Thanks for cooking, but it’s not that I can’t cook.”

I laughed a bit and responded with “this isn’t a can/can’t situation, it’s a do/don’t or will/won’t one.” I know my girl can cook; I made sure all my kids learned how to cook. It’s that they often choose not to, hunting for leftovers, going for takeout, or skipping meals.

I’ve never been one who likes to hear “can’t” from anyone. Even today, when I coach kids and one say “I can’t do that,” my response is “yet. You can’t yet.”

It’s easy to think that because you don’t know how to do something, or don’t have confidence, or you’ve not done it well (or right) in the past, that you can’t do it now. That could be true, but often I find people default to “can’t” when they really mean they don’t want to do something or won’t do something. Easy to confuse those, and easy to brainwash yourself when using the wrong words too often.

There are things I can’t do. For example, I can’t run a 10.0s 100m dash. I can’t dunk a basketball, though there was a time I could. However, on the ranch or at work, I rarely find that I can’t do something if I apply myself with a little curiosity, effort, and experimentation. I can learn most things and do them well enough to meet a goal. Someone else might do them better, but I can learndo them.

I see too few people in the world who aren’t curious at work, aren’t willing to put in extra effort to get a task completed, or don’t feel an urge to tackle tasks outside of their comfort zone. I see fewer people dedicated to making an effort to learn outside of work time, whether on their own or at an event like a SQL Saturday.

Most of the people I see succeed and thrive in jobs aren’t smarter than others. They just do the work. And if they don’t know something, they teach themselves what they need in order to get the job done. They drive themselves forward.

Life is hard, but it gets easier when you want to put in effort to make it better.

Steve Jones

Listen to the podcast at Libsyn, Spotify, or iTunes.

Note, podcasts are only available for a limited time online.

October 24, 2025
Advice I Like: Training Employees

Train employees well enough that they could get another job but treat them well enough that they never want to. – from Excellent Advice for Living

This one is close to my heart. I firmly believe that you need to find good employees and invest in them. Employees can make a big difference in how well you succeed as well as how efficiently you can run an organization. If you trust employees, you can get a lot done, but takes work.

There’s an old joke that expresses a similar sentiment. Here it is as a quote attributed to Peter Drucker, a well known management consultant.

Perhaps one of the best reasons to train people is time. Time is a valuable resource, and the more it’s wasted, the less you get done, the less competitive you are, and the less your employers earn their pay.

Train them and benefit more.

If you worry about training those that might not be worth investing in, that’s hard to know. Train everyone, but hold them accountable to use that training and improve. If not, cut them loose and move on.

I’ve been posting New Words on Fridays from a book I was reading, however, a friend thought they were a little depressing. They should be as they are obscure sorrows. I like them because they make me think.

To counter-balance those, I’m adding in thoughts on advice, mostly from Kevin Kelley’s book. You can read all these posts under the advice tag.

October 24, 2025
Be Wary of Data

I fly a lot, as you might have guessed if you read my blog regularly. In 2025, I’ve been on 56 United planes as I write this, with about 10 left to go before the end of the year. One of the things United does is sometimes send out a quick “survey” after a flight, checking to see if everything went smoothly. I don’t always fill these out, but recently I decided to give some feedback as I had a great experience.

I really wanted to just complement the onboard crew, but the survey was quite a few pages (10?) and a lot of questions. I started to try and fill it out, but lost focus after a few pages. This felt like a chore, and I started to just randomly click some of the selections asking me to rate things 1-10. I wasn’t really rating the items; I was trying to get done. Eventually, I bailed on the survey and didn’t complete it, but that got me thinking about the data from these surveys.

I’m somewhat detail-oriented and I try to do a good job, but I couldn’t finish the survey. How many others just click through things and don’t really give an accurate picture of their feelings?

A similar situation occurs at work, where we have an HR rating system (Thymometrics), which I really like. Over time, it helps me to keep an eye on how I feel about my job, the company, and my general attitude about work. We get quarterly reminders to fill this out, but I know quite a few people who don’t fill it out at all, or just click on it and save the ratings without thinking about them. Another place data might be suspect.

At work we get feedback on various product metrics, in addition to uninstall feedback and product feedback, sometimes with a rating that people click. Is that what they really think about their experience or did they just click the first thing they saw? Or did they mis-click the wrong thing, and they can’t change their rating (clicking 2 when they meant 9).

There is a lot of data that organizations collect from people that is very subjective. Across a large group of users, this should provide some sort of indication of how people feel, but if the sample sizes are small, can you really use this data? I think it’s easy for people in product management, marketing, and sales to view this data as much more accurate than it might be. I know I’m always wary of any outliers when I see feedback, and often I want to know how many people contributed.

Unless it’s a decently large number (100s at least) and there is a clear trend from many people (> 5%), I tend to discount the data as an outlier and not representative.

I’m not sure how many of you do this, but critically examine data and be wary of drawing conclusions. Especially when you are getting impressions, feelings, and opinions from others.

Steve Jones

Listen to the podcast at Libsyn, Spotify, or iTunes.

Note, podcasts are only available for a limited time online.

October 22, 2025