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A Full Shutdown

I have the opportunity to work with a variety of customers on their database systems, often with the focus on how they can build and deploy changes to their databases. Often, they have formal processes around how and when they make changes. Some have maintenance windows, though often these are approved times for changes rather than a true window during which a system is shut down.

I ran into a customer recently who scheduled a system shutdown for their deployments. This was a surprise to me in 2026, as I thought most people would have learned to deploy changes to live systems. However, I know that lots of teams make changes that would render portions of the database inaccessible for a period of time, so maybe that's not true.

I wanted to ask this question today: Do you shut down your system completely for a deployment? Not all systems, but the one you're patching and possibly a few related ones, while preventing client access?

Or do you have to make changes while the system is still in use?

A lot of DevOps analogies revolve around the idea of cars and performing maintenance or improving them. One that I like is learning to replace all the parts of the car while it's still running and in use. That can be hard in the real world, but we can often find ways to do this in software, including with databases. A little creativity can do a long way.

I love watching the evolution of Formula 1 Pit Stops as a way of visualizing the problem. This video is kind of amazing, but it shows the power of thinking about a problem and finding ways to improve it. In the 50s, pit stops could take 45-60 seconds or longer. If you look at the video, in 1990, they dropped this to less than 9 seconds. That seems amazing, but the power of continuous improvement shows this dropping to 7s in 2000. In 2020, 4 seconds. Then in 2020, 1.82 seconds for 4 tires changed.

This is still a full shutdown, albeit a few short one.

I constantly deal with people who think that they cannot find a way to make deployments easier, faster, or less impactful. I know that car racing teams used to feel that way about their pit stops. Once they tried to creatively work on their challenges, they found solutions that are truly amazing. Using new ideas and tools, they reached speeds no one could have imagined a decade ago.

I bet many of you can do the same thing to your databases with an open mind and a little tooling.

Steve Jones - SSC Editor

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 Featured Contents
SQLServerCentral Article

Going Native with Fabric Spark Pools: The Fabric Modern Data Platform

John Miner from SQLServerCentral

The next installment of the Fabric Modern Data Platform looks at Spark pools for executing code.

External Article

Getting Started with mssql-python for Data Developers

Additional Articles from MSSQLTips.com

rogrammatic interaction with SQL Server or Azure SQL from a Python script is possible using a driver. A popular driver has been pyodbc that can be used standalone or with a SQLAlchemy wrapper. SQLAlchemy on its own is the Python SQL toolkit and Object Relational Mapper for developers. In the end of 2025 Microsoft released v1 of their own Python SQL driver called mssql-python. How do you get started using mssql-python for programmatic access to your SQL Server?

Blog Post

From the SQL Server Central Blogs - How to Parameterize Fabric Linked Services in Azure Data Factory for Azure Devops Deployment

Koen Verbeeck from Koen Verbeeck

Quite the title, so let me set the stage first. You have an Azure Data Factory instance (or Azure Synapse Pipelines) and you have a couple of linked services...

Blog Post

From the SQL Server Central Blogs - Deployment Pipelines in Fabric – What Are They?

HamishWatson from The Hybrid DBA's Blog

In the realm of software development and content creation, the deployment pipeline serves as a crucial bridge between innovation and implementation. Whether you are fine-tuning code, testing new features,...

Deciphering Data Architectures

Deciphering Data Architectures

Additional Articles from SQLServerCentral

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.

 

 Question of the Day

Today's question (by Steve Jones - SSC Editor):

 

OPENQUERY Flexibility

Which of these are valid OPENQUERY() uses?

Think you know the answer? Click here, and find out if you are right.

 

 

 Yesterday's Question of the Day (by Steve Jones - SSC Editor)

Restoring On Top I

I am doing development work on a database and want to keep a backup so I can reset my database. I make some changes and want to restore over top of my changes. When I run this code, what happens?

USE Master
BACKUP DATABASE DNRTest TO DISK = 'dnrtest.bak'
GO

USE DNRTest
GO
CREATE TABLE MyTest(myid INT)
GO
USE master
RESTORE DATABASE DNRTest FROM DISK = 'dnrtest.bak' WITH REPLACE

Answer: This restore the database from the old backup, over the top of the existing database

Explanation: There is no warning with REPLACE. The database is overwritten by the restore. Ref: RESTORE - https://learn.microsoft.com/en-us/sql/t-sql/statements/restore-statements-transact-sql?view=sql-server-ver17

Discuss this question and answer on the forums

 

 

 

Database Pros Who Need Your Help

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Editorials
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Guarding Against SQL Injection at the Database Layer (SQL Server) - Comments posted to this topic are about the item Guarding Against SQL Injection at the Database Layer (SQL Server)
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SQL Server 2022 - Development
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