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Category: Cloud

Testing with Databricks

Published 2024-03-26 by Kevin Feasel

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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Azure SQL DB Watcher and Azure Data Explorer Integration

Published 2024-03-26 by Kevin Feasel

Guy Reginiano gets chocolate in my peanut butter:

Azure SQL family users can now take advantage of an enhanced monitoring solution for their databases and leverage Azure Data Explorer or the Microsoft Fabric integration. With the introduction of the new Database Watcher for Azure SQL (preview), users gain access to advanced monitoring capabilities. 

Database watcher is a new managed monitoring solution for database services in the Azure SQL family. It supports Azure SQL Database and Azure SQL Managed Instance.

Read on to see how you can analyze results with Azure Data Explorer.

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Regex Support in Azure SQL DB

Published 2024-03-25 by Kevin Feasel

Abhiman Tiwari has a big announcement:

We are pleased to announce the private preview of regular expressions (regex) support in Azure SQL Database. Regex is a powerful tool that allows you to search, manipulate, and validate text data in flexible ways. With regex support, you can enhance your SQL queries with pattern matching, extraction, replacement, and more. You can also combine them with other SQL functions and operators to create complex expressions and logic.

This is something I’ve wanted to see in SQL Server for years, and I’m excited that there’s official support now. Prior to that, you could use SQL# to perform some regular expression operations using the CLR, but as long as performance is reasonable on these, it’s a huge feature to include.

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Copilot in Azure SQL Database

Published 2024-03-22 by Kevin Feasel

Joe Sack gets in the cockpit:

We are excited to announce that Copilot in Azure SQL Database is now in limited public preview! Copilot in Azure SQL Database experiences are designed to streamline the design, operation, optimization, and health of Azure SQL Database-driven applications. It improves productivity in the Azure portal by offering natural language to SQL conversion and self-help for database administration.

Click through to see what you can do with it right now. I’d expect there will be more capabilities over time, too.

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Using Runbooks in Azure Automation

Published 2024-03-21 by Kevin Feasel

Rod Edwards has a process for that:

Nobody likes to do the same monontonous task over and over again. Well, saying that, maybe some out there do in order to look and feel busy…but I don’t, as I nearly always have something else more pressing or fun or interesting to do. By automating those repeatable tasks, it reduces boredom, chance of errors, and stress if you’re already a busy bunny.

This is where Automation comes into play, and in Azure we have a few options. This post focuses in Azure automation.

Read on to see how Azure Automation works and how to build a Powershell runbook in it.

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Database Watcher for Azure SQL

Published 2024-03-21 by Kevin Feasel

Dimitry Furman has a new announcement:

Reliable, in-depth, and at-scale monitoring of database performance has been a long-standing top priority for SQL customers. Today, we are pleased to announce the public preview of database watcher for Azure SQL, a managed database monitoring solution to help our customers use Azure SQL reliably and efficiently.

Click through to see what it offers and what’s on the roadmap for this product.

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Using Key Vault in SQL Server on Linux

Published 2024-03-21 by Kevin Feasel

Aravind Mahadevan shares information on a new bit of functionality:

We’re excited to announce that Extensible Key Management (EKM) using Azure Key Vault in SQL Server on Linux is now generally available from SQL Server 2022 CU12 onwards, which allows you to manage encryption keys outside of SQL Server using Azure Key Vaults.

In this blog post, we’ll explore how to leverage Azure Key Vault as an EKM provider for SQL Server on Linux.

Read on to see how to set this up.

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Restorable Dropped Databases Naming in Azure SQL DB

Published 2024-03-19 by Kevin Feasel

Tanayankar Chakraborty asks, what’s in a name?:

An issue was reported recently where the customer complained that in their cost analysis report of their Azure SQL DBs, the db name appears appended with a comma(,) and a number. While they agreed with the DB name in the report, they didn’t understand the number after the comma and its significance. This is how the cost analysis report looks like:

Click through for a redacted version of the report, showing an example of the database in question, as well as an explanation of what this number means.

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Feature Engineering with Azure ML and Microsoft Fabric

Published 2024-03-18 by Kevin Feasel

Siliang Jiao, et al, talk architecture:

Feature engineering is the process of using domain knowledge to extract features (characteristics, properties, attributes) from raw data. The extracted features are used for training the models that can predict values for relevant business scenarios. A feature engineering system provides the tools, processes, and techniques used to perform feature engineering consistently and efficiently. 

This article elaborates on how to build a feature engineering system based on Azure Machine Learning managed feature store and Microsoft Fabric. 

Click through to see how the pieces fit together.

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Tips for Using Powershell in Azure

Published 2024-03-12 by Kevin Feasel

Paul Harrison shares a few tips with us:

When I’m working with a new object in Azure I often don’t know where the information I care about is actually found in output. PowerShell makes it easy to navigate through objects, however it isn’t easy to get an overview of all properties available if they’re nested 5 levels deep. I like to use ConvertTo-JSON to help me get a general understanding for a new object and which properties are available and how to find them.

Read on for more information about converting to JSON and four other tips.

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