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Category: Cloud

Trying out Microsoft Fabric Mirroring of Cosmos DB

Kevin Chant gives it the ol’ college try:

In this post I cover some initial testing of Mirroring Azure Cosmos DB Databases in Microsoft Fabric that I performed.

I wanted to do this post for various reasons. Including the fact that it was announced during the Microsoft Fabric Community Conference that Mirroring is now in Public Preview.

Which means that you can now mirror data from Azure SQL Database, Azure Cosmos DB and Snowflake into your own Microsoft Fabric tenant. Even trial tenants.

Kevin takes us through the process and gives it a try, sharing with us the results of some testing, including a test insertion of 100 million rows.

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Cloud Governance Guidance in the Cloud Adoption Framework

Stephen Sumner notes an addition to the Microsoft Cloud Adoption Framework (CAF) for Azure:

We are thrilled to announce the latest enhancement to Microsoft’s Cloud Adoption Framework for Azure. We comprehensively updated our cloud governance guidance in the Govern section of the Cloud Adoption Framework (CAF). The updated governance guidance represents Microsoft’s commitment to supporting your organization’s cloud journey, offering a clearer, more accessible, and comprehensive path to effective cloud governance. It encompasses identity, cost, resource, data, and AI governance among other areas of governance categories.

Whether you’re a startup looking to scale efficiently or a large enterprise aiming to refine your governance practices, we designed this governance guidance to meet your needs and guide you to where you need to be.

Read on to learn more about what cloud governance means and the tooling available.

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Failover Groups in Azure SQL Database

Josephine Bush sets up a failover group in Azure SQL Database:

In today’s fast-paced digital world, keeping your data safe and accessible is more important than ever. That’s where Azure SQL Database steps in, offering a suite of tools to ensure your information is always within reach. Among these tools, failover groups shine, ready to jump into action whenever there’s a hiccup. So, let’s explore how failover groups in Azure SQL Database work their magic, ensuring your data stays safe and sound despite unexpected challenges.

Read on for the step-by-step instructions.

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Displaying Azure Maps within a Power BI Paginated Report

Chris Webb shows a map in a paginated report:

The built-in mapping functionality in Power BI paginated reports is fairly basic. However the integration of Power Query into Power BI paginated reports gives you an interesting new way of creating maps in paginated reports: you can call the Azure Maps API using Power Query and display the image returned in an Image report item. In this blog post I’ll show you how.

Click through for the demo.

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Infrastructure as Code in GitHub

I have a new video:

In this video, we look at how to perform Infrastructure as Code in GitHub. We take a Bicep script and generate new Azure resources using it and GitHub Actions.

The video includes a very brief primer on Azure Resource Manager (ARM) and Bicep, and then gets into how you can use GitHub Actions to keep your Azure resources configured the way you expect.

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Date Calculation Bug in Power Query ODBC Code

Meagan Longoria files a report:

I was working on an imported Power BI semantic model, adding some fiscal year calculations to my date table. The date table was sourced from a view in Databricks Unity Catalog. I didn’t have access to add more fields to the view, so I was adding the fields in Power Query first, with plans to request they be added to the view in the future. I got some unexpected results, which turned into a bug being logged for the ODBC code for Power Query.

If you are only analyzing data in the last 20 years, you won’t see this bug. But if you are doing long-term analysis including years before 2000, you might just run into it.

Read on to see the bug, how you can replicate it, and three workarounds you can use to avoid it.

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Maintaining Dynamic IP Rules for Azure Network Security Groups

Daniel Hutmacher shares a couple scripts:

Recently, my home ISP has started changing my public IP address. This causes me some headache because I have a couple of Azure Network Security Group rules (think of them as firewall rules) that specifically allow my home IP access to all of my Azure resources. When my home IP changes, those rules have to be updated accordingly.

So I made a PowerShell-based solution to automatically maintain them.

Read on for the process.

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Using Azure SQL Database Elastic Pools

Josephine Bush shares some tips on using elastic pools in Azure SQL DB:

Main points about elastic pools

  • Elastic pools enable you to purchase resources for a pool shared by multiple databases to accommodate unpredictable usage periods by individual databases.
  • You can create multiple pools on a server, but you can’t add databases from different servers into the same pool.
  • Pools are well-suited for many databases with specific utilization patterns. These patterns are characterized by low average utilization with infrequent utilization spikes for a given database. Conversely, multiple databases with persistent medium-high utilization shouldn’t be placed in the same elastic pool.

All the databases in the elastic pool share the DTU and storage. This is very apparent when multiple persistent medium-high utilization databases are in the same pool, which is why Microsoft advises against it.

Read on to see information about storage, DTUs, noisy neighbors, and more.

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Mirroring an Azure SQL Database in Microsoft Fabric

Gilbert Quevuavilliers holds up a mirror:

Creating a Mirrored Azure SQL Database in Fabric

This week they announced Announcing the Public Preview of Database Mirroring in Microsoft Fabric | Microsoft Power BI Blog | Microsoft Power BI

I decided to see how easy it was to create a mirrored database in Fabric and below are my findings (PS it is AMAZING)

Click through for the demo. Though it does look like Gilbert has mirrored the contents of the blog post a few times as well, at least as of the time of my post here.

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Testing with Databricks

Anh Nguyen Viet shares some thoughts on testing in Databricks:

With diverse support and a focus on workspace uniformity, Databricks can bring many benefits to the testing process, such as the following:

  • Centralized: Databricks provides an integrated environment for many teams (including testing team also), allowing them to work focused and productive. Integrating tools and services in a single platform reduces fragmentation and increases efficiency during testing.
  • Consistency: Databricks offers integrated tools and services, allowing testers to work consistently across the entire testing process as a uniform and efficient working environment.
  • Enhanced Productivity and Cost Reduction: With the flexibility and efficiency in data processing supported by DataBricks, testers can save time and effort, thereby increasing work productivity and reducing project costs. Utilizing utilities properly helps automate the testing process and delivers better results.

Read on for a few tips around building tests using Databricks.

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