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Category: Cloud

Restoring Backups from S3 to Azure SQL MI

Published 2023-09-06 by Kevin Feasel

Strahinja Rodic announces a new feature going to GA:

In September last year SQL server 2022 introduced new feature – backup and restore to simple storage service (S3) – compatible object storage that grants the user the capability to back up or restore their databases using S3-compatible object storage, whether that be on-premises, or in the cloud.

To provide this integration Azure SQL MI is enriched with a new S3 connector, which uses the S3 REST API to connect to Amazon S3 storage. It extends the existing RESTORE FROM URL syntax by adding support for the new S3 connector using the REST API.

Click through to see what you need to have set up for it to work, as well as the restoration process.

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Scale-Out Read-Only Databases in Azure SQL DB

Published 2023-09-06 by Kevin Feasel

Etienne Lopes begins a new series:

“As part of High Availability architecture, each single database, elastic pool database, and managed instance in the Premium and Business Critical service tier is automatically provisioned with a primary read-write replica and one or more secondary read-only replicas.”

Read on to see how you can add support for read-only, scale-out replicas to an existing Azure SQL Database. Just know how much that bill is going to be.

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Australian Azure Downtime After-Action Report

Published 2023-09-05 by Kevin Feasel

Brent Ozar shares some thoughts:

Note that 11:34, the decision was made to shut down infrastructure without Microsoft failing your databases over elsewhere. If you were an Azure SQL DB or Cosmos DB user, and you weren’t paying for replicas in another data center, it was up to you to follow Microsoft’s disaster recovery guidance.

Controversial opinion: I actually love that and I think it’s great.

That is definitely a controversial opinion, but it’s also one I agree with. Read on for more of Brent’s thoughts.

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Advanced Scenarios for Private Endpoints to Azure SQL MI

Published 2023-08-25 by Kevin Feasel

Zoran Rilak digs in:

In the previous installment of this mini-series, we covered basic scenarios involving private endpoints. If you aren’t familiar with private endpoints and Private Link in general, it might be a good idea to quickly review them to get the feel of how they apply when Azure SQL Managed Instance is in the mix.

In this article, we’ll dive into more involved scenarios that build on those from last week:

5. Hub and spoke topology

6. Partner or ISV giving access to their customers

7. Two SQLs talking to each other: linked server, transactional replication

8. Failover group listener using private endpoints

Read on for architecture diagrams and descriptions for each of these scenarios.

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Storing Log Analytics Queries in Azure Blob Storage

Published 2023-08-24 by Kevin Feasel

Gilbert Quevauvilliers wants some long-term storage:

Following on in my series, in this blog post I am going to demonstrate how to store Log Analytics Queries in Blob Storage.

This allows me to be able to store the Power BI Queries externally from Log Analytics and to have an easy way to get the data into my Fabric Lake house in later steps. To do this I am going to use a Logic App in Azure.

In this series I am going to show you all the steps I did to have the successful outcome I had with my client.

Read on to see what Gilbert used for the task.

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TaskFactory Activation on an Azure-SSIS Integration Runtime

Published 2023-08-24 by Kevin Feasel

Andy Leonard does some sleuthing:

I regularly help customers migrate SSIS to Azure-SSIS integration runtimes, a nifty component of Azure Data Factory. I was recently stumped by an error activating TaskFactory (Task Factory for the search engines…) on an Azure-SSIS IR node. The error was:

“The system cannot find the file specified.”

Read on to figure out where the file is and how to fix this error.

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Training a Code-First Model in Azure ML

Published 2023-08-23 by Kevin Feasel

I have a new video:

In this video, we walk through the code in an Azure Machine Learning project and see how the pieces fit together.

There are a few more videos to go in this Azure ML series and I would recommend going through them in order to understand how we got to this video, but this one is what I’ve been building toward.

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Deploying Azure Resources with Terraform and GitHub Actions

Published 2023-08-23 by Kevin Feasel

Reitse Eskens sets up some new resources:

When you start out with Terraform, you’ll most likely run the code locally with terraform on your own machine. Terraform works with a so-called state-file, it saves the state of the Azure deployment it left behind and compares the (new) code with the state it encounters when it runs again. Changes are resolved by changing, deleting or adding resources that don’t match the state-file.

This works fine when you’re flying solo and don’t have co-workers who can change resources as well. Whenever you need to share code, the industry standard is to use a git solution, whether GitHub, GitLab, Azure DevOps or some other solution, as long as it has version control you should be fine (providing people adhere to the correct usage of branches).

Click through for a step-by-step walkthrough, as well as explanation of the major actors in that play.

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Text-to-Video with Azure Open AI and Semantic Kernel

Published 2023-08-22 by Kevin Feasel

Sabyasachi Samaddar continues a series on generating video from a series of text prompts:

Welcome back to the second part of our journey into the world of Azure and OpenAI! In the first part, we explored how to transform text into video using Azure’s powerful AI capabilities. This time, we’re taking a step further by orchestrating our application flow with Semantic Kernel.

Semantic Kernel is a powerful tool that allows us to understand and manipulate the meaning of text in a more nuanced way. By using Semantic Kernel, we can create more sophisticated workflows and generate more meaningful results from our text-to-video transformation process.

In this part of the series, we will focus on how Semantic Kernel can enhance our application and provide a smoother, more efficient workflow. We’ll dive deep into its features, explore its benefits, and show you how it can revolutionize your text-to-video transformation process.

Read on for an understanding of how Semantic Kernel fits in and what you can do with it.

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Index Maintenance in Azure SQL DB with Elastic Jobs

Published 2023-08-22 by Kevin Feasel

Scott Klein continues a series on index maintenance in Azure SQL Database:

It’s finally here: the third and final blog post about Azure automation. The first blog covered how to automate Azure using Runbooks, the second blog post showed how to do it using Azure Functions, and this blog post will cover how to do it using Azure Elastic jobs.

To be fair, I titled this blog “Automating Azure with Elastic Jobs”, but Elastic Jobs isn’t part of Azure Automation, so please don’t get confused. The goal with this is to demonstrate how to automate some Azure database DBA tasks.

Read on for a brief primer on elastic jobs and how to use them.

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