The Bit Bucket

Logic Apps are closely related to Power Automate, but they’re designed for enterprise IT teams that need more control, scalability, and governance.

Like Power Automate, Logic Apps let you automate workflows across systems using a visual, low-code designer.

However, Logic Apps are built on Azure, which gives them access to more advanced capabilities — such as higher throughput, better integration with on-premises systems, and enterprise-grade reliability.

You can think of Power Automate as being focused on business users and citizen developers, while Logic Apps are aimed at IT professionals and developers who build and maintain enterprise integrations.

2026-07-30

Database mirroring was added way in SQL Server 2005. One of the features added to it later in SQL Server 2008 was auto page repair. When SQL Server 2012 was released, Availability Groups also offered auto page repair.

Just how useful is this feature though ?

I’ll start by saying that it can’t hurt.

When SQL Server is reading a page on the primary replica and receives an unrecoverable I/O error (typically but not always, an error 823 for a checksum error), it will try to repair the page when:

2026-07-29

Power Automate is Microsoft’s no-code workflow automation platform, and it integrates directly with Activator to help turn events into business actions.

When a rule in Activator is met — for example, when a sensor crosses a threshold or a transaction fails multiple times — that event can automatically trigger a Power Automate flow.

A Power Automate flow is a sequence of steps that perform an operation, often involving multiple systems. For example, a trigger from Activator could:

2026-07-28

I work with a lot of SQL Server databases that are poorly normalized. One of my pet dislikes is the column to rule them all.

Here are simple tests:

• If I ask you what’s stored in a column and you can’t tell me a single answer, then you’ve got a problem.
• If you need to refer to another column to work out what’s in the first column, then you’ve got a problem.

Here are some examples:

2026-07-27

After Activator detects that a condition or pattern has been met, the next step is to trigger an action.

Actions are what turn analytics into operational responses — they ensure that insight leads directly to something happening.

Actions can be either internal or external:

Internal actions occur within Fabric — for example, updating a dataset, refreshing a Power BI report, or writing a new event back into an Eventstream.

2026-07-26

Intrusions into computer systems are happening all the time now. We need to address this issue as an industry, but it’s important to understand that the way we design databases plays a big role in the impacts that occur during intrusions.

If you don’t accept that you could have an intrusion, you are living in La La Land. (See https://en.wikipedia.org/wiki/Fantasy_prone_personality )

A bug in any one of the frameworks that you use, the code that you write, the protocols that you use, the operating system or hosting services that you use can potentially expose you to an intrusion.

2026-07-25

In many real-time systems, a single event on its own doesn’t tell the full story. Pattern detection allows you to identify sequences or combinations of events that together indicate something meaningful.

For example, a single failed login attempt is rarely an issue, but multiple failed logins within five minutes could suggest a security concern. Similarly, a single temperature reading above normal might not matter, but a rising trend over time could signal equipment failure.

2026-07-24

I had the pleasure of recording a new PG Down Under podcast today. It was great to have Charles Feddersen from Microsoft back on the show.

Charles is the Partner Director of Product Management, Postgres & MySQL on Azure at Microsoft.

He leads the product management teams for the Postgres and MySQL managed services on Azure including Azure Database for PostgreSQL, Azure Database for MySQL, and Azure HorizonDB, which is why I wanted to talk to him today.

2026-07-23

In Activator, rules are the core element that make automation possible. A rule defines the condition you want the system to look for in your data — the point at which something should happen.

Rules can be simple or complex.

A simple example might be: temperature > 90°C or error rate exceeds 5%. These are fixed thresholds — clear, measurable values that indicate when a limit has been crossed.

2026-07-22

I recently received a review copy of Python Data Analysis: Master Python Analytics with Machine Learning, Deep Learning, GenAI, LLMs, and Data Engineering by Avinash Navlani and Cornellius Yudha Wijaya from my friends at PackT. This is the fourth edition of this book.

Authors

Avinash Navlani is a senior data scientist, researcher, and educator with a PhD in data science and many years in both the industry and in academia.

Cornellius Yudha Wijaya is a data science manager leading AI initiatives and driving the development of practical data and AI solutions.

2026-07-21