Advice I Like: Failure

If it fails where you thought it would fail that is not a failure. – from Excellent Advice for Living

This is a great quote, especially for those of us working in computer systems. We often design things like HA (which I wrote about this past week), circuit breakers, and other techniques to handle problems we know about.

When those things occur, we’ve planned for them, so I get that these are not a failure. In fact, they are a known case we’ve designed for.

The same thing for me, if I am building something on the ranch. If I put in a post and don’t cement it, and then need to add a wheel to a gate (ask me how I know this), then if the gate leans over, it’s expected.

On the other hand, if the piece of metal holding the wheel on fails, that’s a failure. I expected it would keep the wheel on, but apparently, it isn’t engineered well enough to handle a load from a slight slope. Sad smile

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.

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Internal Staff Growth

Imagine that you are about to tackle a new project that will take more than a year. This might be a new system, perhaps a cloud migration, or maybe it’s rewriting something that doesn’t work well. You don’t have enough employees to undertake the project without overloading everyone. Your team needs to grow.

Would you rather hire a more senior person from outside the organization or pick a junior person that’s already inside your company and teach them what they need to know? Think about this as if you were the one making the decision about the future direction of your software team. Philosophically, do you want to buy experienced people or train/build new ones from your internal staff.

It’s an interesting idea and for a lot of companies, I see them looking outside the company first, rather than investing in, and training, their internal staffers to grow. It takes time to train and grow people, for sure, and it’s a constant investment that never goes away. At the same time, bringing people in from the outside also requires some level of training on how the current systems and org work, even if the new hire has a lot of experience.

I think there are good reasons to look at both of these, but my view is that I want to have people on a team that know how to work together. The tech skills (or design, modeling, etc.) can be taught, and I would rather have a good cultural fit, already knowing how a person fits with others. That assumes I’ve got good employees who fit together and believe in our culture. That’s hard enough to do, which is why I want to hire people who can work as a team and keep them. Part of the “keeping” them is investing in them.

This also means that if people don’t fit in, I want to help them move on to a better fit.

This doesn’t mean I want everyone to think the same. It is important to have a variety of views on how to design and build applications. A variety of people is important, but we have to be a team.

I prefer to train and invest in the people I have over bringing in more experienced staffers. A big part of why I feel this way is that hiring is always a gamble, and it seems we make no shortage of mistakes. If I do get it right, then I want to grow and keep those people around for the long term.

Steve Jones

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SQL Server 2025 RegEx and AI

One of the language changes in SQL Server 2025 that I’ve seen a lot of people mention is the addition of RegEx functions to T-SQL. I decided to take a few minutes and try to examine how this feature works, and how I might use it. And more importantly, can AI help?

This is part of a series of experiments with AI systems.

Data with a Bit of a Pattern

One of the common things people use Regex for is validating email addresses.

I created a basic table in a database that looks like this:

CREATE TABLE customer
(
     customerid INT NOT NULL
         CONSTRAINT CustomerPK PRIMARY KEY,
     customeremail VARCHAR(200),
     validated TINYINT
)
GO

I then asked PromptAI to get me some test data like this:

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I wasn’t connected to a database, but I still got code generated with insert statements. The AI also noted I had a “validated” column, and it populated that appropriately: 1 for good email, 0 for bad ones.

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Once I run the inserts, I have data.

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Now, can I check that the AI did this correctly?

REGEXP_LIKE

In SQL Server 2025, there are a number of regular expression functions, and REGEXP_LIKE is one of these. This function is designed to return a boolean if the string_expression matches the pattern_expression, where the latter is the regular expression.

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Prompt sees this as a valid function for SQL Server 2025, which is great. I want to use the customeremail from the table as my string to check. For the regex, I need to create a regular expression, something I am not good at doing. I learned to do this at a very rudimentary level when writing Perl, but I’ve lost whatever little skill I used to have.

I saw an expression on StackOverflow for validating email. Let’s check if an AI can help.

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In a few seconds, even on airport wi-fi (SFO as I write this), I get a response.

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This looks like the expression from the SO answer, though much shorter. If you read SO, you know that the format isn’t as set and stable as we’d like. In any case, let’s see what this shows.

This is interesting. I get an error.

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If I look at the docs, this says it returns a true/false, which I’d assume would convert to a 1/0, but let’s try an explicit case. When I do this, it works.

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I can also do this in the WHERE clause, where the true/false thing just works. Let me move the function to the WHERE clause. If I do that, I have this code:

SELECT customerid,
        customeremail,
        validated
FROM dbo.customer
WHERE REGEXP_LIKE(customeremail, '^[A-Za-z0-9._%-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$')

When I run this, I see what I expect:

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Not a bad enhancement to the T-SQL language.

Summary

There’s a lot written on RegEx, so this post isn’t intended to delve deeply into what RegEx expressions you choose. Rather, I wanted to show the basics of this REGEXP_LIKE() function, and showcase one of the weird things I found when including this in the column list. I also haven’t looked at performance yet, though that certainly is something to be concerned about with larger datasets

There are other changes in SQL Server 2025, and I’ll try to examine some in the coming weeks.

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T-SQL Tuesday #192: SQL Server 2025 Backup Changes


I hosted this month, but I decided to put my own entry in as well. There are more things in this release than I expected, probably because of the overwhelming focus on Fabric from Microsoft that has drowned out other changes.

I’ve been a DBA (or Ops manager) for quite a bit of my career, and one of the things I’ve thought was top priority was backups. I always want to be sure I have a recovery strategy, because if I don’t, nothing matters. Things go wrong and systems fail and I need to protect systems.

Security is a close second, but backups really matter.

I was excited to see that full and differential backups can be set on secondary replicas in AGs. To be fair, I had assumed this would be working by SQL Server 2022, but I hadn’t checked. Glad it’s been added. I know, I know, I questioned if you need HA, but that’s more a staffing question than one of whether HA makes sense in general.

Backups, especially on larger systems, can be a load on the server. We’ve seen this with compressed backups natively, or with something like SQL Backup. As a result, offloading this to another system is something I’d want to do.

Of course, there’s still the challenge of making sure you get these all organized in one place (don’t have the 1 copy of your diff only on one secondary), but that’s a separate post.

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