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Category: Cloud

Restoring SQL Server Backups from Azure Blob Storage

Niko Neugebauer walks us through special considerations when using Azure Blob Storage as your backup location:

If you are using Azure Blob Storage for SQL Server Backups, you need to know a couple of important details before you start with some significant project and as you should know (and in my head I am keep on hearing Grant Fritchey angrily declaring that there is no backup strategy that exists, if there is no restore strategy to be found in the plan).

The ACL permissions required by the Restore From URL operation in SQL Server (any SQL Server right now, starting with SQL Server 2012 page blobs and including SQL Server 2019 blob storage support that was started with SQL Server 2014) will require … [drumroll] … exclusive WRITE-permissions on the de underlying file(s).

Niko explains some of the pain around that requirement, as well as a few other bees in your bonnet.

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Connecting to Cosmos DB via Linked Server

Frank Solomon takes us through communicating with Cosmos DB from SQL Server:

Every source table column becomes an expression in the SELECT clause. If needed, JSONLint, for example, can validate the output JSON format. In this query, the FOR XML PATH clause places each row into a formatted JSON row, with key/value pairs that match the column/value pairs of the original rows. To get the data ready, the empty (”) value in the FOR XML PATH() clause at line 10 separates each XML row with a default comma. At line 11, the STUFF function arguments format the result set as a string and remove the leading “.” in the original data. Save the finished result XML-format result set as a JSON file. This file will become the data we’ll import.

Cosmos DB database has zero or more collections, which correspond to SQL Server tables. A collection has zero or more documents, which correspond to SQL Server table rows. In the Cosmos DB

With SQL Server 2019, PolyBase also allows connections to Cosmos DB if (and only if) you are using the MongoDB API for Cosmos. But if that’s how your collection is set up, querying it becomes pretty easy.

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Retrieving Secrets from Azure DevOps Pipelines

Gavin Campbell shows how you can pull secrets out of an Azure DevOps Pipeline:

For secrets created in the Azure DevOps UI, whether pipeline-scoped or in a variable group, it is not so simple to retrieve the variables after creation. This might be required for a number of reasons, most often troubleshooting. The need to do this is often an indicator that the project should have been using an Azure Key Vault in the first place.

Previously it was necessary to jump through some hoops to access secret variables, but it turns out this is no longer required. It also appears the recommended approach of mapping secrets to environment variables is currently not working for secret variables from variable groups.

I second the notion of using Key Vault for secrets management.

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Postgres Change Data Capture into Kafka

Abhishek Gupta walks us through an example of change data capture to track events:

Change Data Capture (CDC) is a technique used to track row-level changes in database tables in response to create, update and delete operations. Different databases use different techniques to expose these change data events – for example, logical decoding in PostgreSQLMySQL binary log (binlog) etc. This is a powerful capability, but useful only if there is a way to tap into these event logs and make it available to other services which depend on that information.

Debezium does just that! It is a distributed platform that builds on top of Change Data Capture features available in different databases. It provides a set of Kafka Connect connectors which tap into row-level changes (using CDC) in database table(s) and convert them into event streams. These event streams are sent to Apache Kafka which is a scalable event streaming platform – a perfect fit! Once the change log events are in Kafka, they will be available to all the downstream applications.

Click through for the demo, using Azure components.

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Storing SQL Server Database Files in Blob Storage

Tomaz Kastrun has a wacky idea:

Storing SQL Server database files in Azure blob storage is a great solution for all the databases that are often migrated between instances, servers, virtual machines, or would have been divided between instances. This scenario also has the positive aspect to it, since the ability to create snapshot backups to Azure is seamless.

Following the steps, we will create a Azure Blob storage, where MSSQL Server database files will reside with MSSQL Server running on-prem. Assuming, that you already have the Azure account (if not, you can get a free Azure account), let’s proceed by opening the Windows Terminal in PowerShell mode.

I’m impressed that it worked and could see it being an option for small demo databases, but I can’t imagine performance would be good enough for a production scenario.

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Loading Data from S3 into Power BI

Gilbert Quevauvilliers loves a challenge:

I really enjoy a good challenge, and with my customer they have all their data stored in AWS S3. Whilst there is no native connector, I thought there must be a way for me to get the data from AWS S3 into Power BI.

I did a bit of Googling and could not find any suitable solution. I also found and learnt that I could use AWS Athena to query the data living in S3. (I am definitely an expert of have a lot of knowledge in the AWS space. I am fortunate that I have other people who know AWS and were able to setup, configure and give me the details to connect to S3 via AWS Athena)

Below are the steps on how I got this working.

Why they don’t have a proper connector is a bit of a head-scratcher to me given the sheer amount of data stored in S3 and the sheer number of connectors in Power BI.

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Transforming JSON to CSV: ADF vs Databricks

Rayis Imayev compares two methods of transforming a JSON-structured data set into a CSV:

There is a well known and broadly advertised message from Microsoft that Azure Data Factory (ADF) is a code-free environment to help you to create your data integration solutions – https://azure.microsoft.com/en-us/resources/videos/microsoft-azure-data-factory-code-free-cloud-data-integration-at-scale/. I agree and support this approach of using drag and drop visual UI to build and automate data pipelines without writing code. However, I’m also interested to try if I can recreate certain ADF operations by writing code, just out of my curiosity.

Rayis includes a link to the Azure Data Factory step-by-step demonstration and then kicks it up a notch with Databricks. Read on to see how the two compare.

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Calculating Cloud App Availability

Dave Bermingham gives you a way to calculate how available you should expect your application to be given SLAs:

When deploying business critical applications in the cloud you want to make sure they are highly available. The good news is that if you plan properly, you can achieve 99.99% (4-nines) of availability or more. However, calculating your true availability may not be as straightforward as it seems.

When considering availability you must consider the key components that make access to your application possible, which I’ll call the availability chain. Component of the availability chain are:

– Compute
– Network 
– Storage
– Application
– Dependent services

Your application is only as available as your weakest link, and your downtime increases exponentially with each additional link you add to the chain.  Let’s examine each of the links. 

Read on for a breakdown of these items.

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Understanding Digital Twins in IoT Hub

Paul Hernandez explains the concept of digital twins in the IoT space:

Azure Digital Twins Service offers a way to build next generation IoT solutions. There are other approaches on the market to describe IoT devices and build digital twins. Without making a formal comparison I can say with the Azure Digital Twins is possible to build a powerful semantic layer on top of your connected devices using domain specific models.

To show you how this work let’s create a kind of “hello world” example. An end-to-end solution is out-of-scope of this post. Instead I will create some hands-on tutorial to demonstrate some of the functionalities.

Click through to see an example.

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Assuming a Role with AWS Powershell Tools

Sheldon Hull solves a problem:

I’ve had some issues in the past working with AWS.Tools PowerShell SDK and correctly assuming credentials.

By default, most of the time it was easier to use a dedicated IAM credential setup for the purpose.

However, as I’ve wanted to run some scripts across multiple accounts, the need to simplify by assuming a role has been more important.

It’s also a better practice than having to manage multiple key rotations in all accounts.

Read on to see how far Sheldon has been able to take this, but also how much more work is left to do.

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