A Fine Slice Of SQL Server
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.
Comments closedIn 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.
Comments closedReitse 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.
Comments closedSabyasachi 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.
Comments closedScott 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.
Comments closedZoran Rilak begins a new series:
Last week we announced the general availability (GA) of private endpoints for Azure SQL Managed Instance. Today, we bring you examples of private endpoints in practical scenarios, starting from the basics and building to the more complex ones to follow in the second installment of this mini-series.
In this post, we’ll cover the following scenarios:
- Accessing SQL MI from another virtual network
- A more secure kind of public access
- Accessing SQL MI from your premises
- Making SQL MI available to managed Azure services
Click through to see these four scenarios at the architecture diagram level.
Comments closedGilbert Quevauvilliers begins a new series:
As with most of my blog posts it involves a client from a customer where I am consulting, which I think will help others.
The requirement was to analyse the Power BI Query usage patterns of the users. The initial requirement was to find out how many users were using Excel to gain access to the Power BI Dataset.
I knew that I could get this using Azure Log Analytics. Not only could I find out how many users are using Excel, but I could also find out what queries they are running, how long they took.
Read on for the first part in this series, which details setting up Azure Log Analytics.
Comments closedKevin Chant checks the burndown:
In this post I want to cover using Azure DevOps Analytics views and Microsoft Fabric to create Sprint review dashboards.
I consider this post to be a sequel to one of my post popular posts that covered using Azure DevOps Analytics views and Power BI to create Sprint review dashboards. For four very good reasons.
Read on for those reasons, along with the steps Kevin took.
Comments closedTeo Lachev shares some thoughts:
I’ve done a few BI integration projects extracting data from ERPs running on IBM Db2. Most of the implementations would use a hybrid architecture where the ERP would be running on an on-prem mainframe while the data was loaded in Microsoft Azure. Here are a few tips if you’re facing this challenge:
Click through for five major points. Surprisingly, one of them isn’t “Avoid DB/2 like the plague.”
Comments closedHasan Savran does some looking:
In my previous post, I discussed the process of establishing a Free-text search for Azure Cosmos DB. Towards the end, I demonstrated how to carry out a free-text search using the Azure Portal. Now, I will guide you on how to perform this search using code. To perform this search by code, I created a basic console application and added Azure.Search.Documents and Microsoft.Azure.Cosmos.
Click through for that demonstration.
Comments closed