A Fine Slice Of SQL Server
Atisha Shaurya shows how to set up a site-to-site VPN via the Azure portal:
Similar to how you set up and connect to a remote branch office, Azure VPN Gateway uses Site-to-Site VPNs to link your on-premises networks to Azure.
In Search bar, type virtual network gateway and select the create option as shown in the below image of virtual network gateway page.
Click through for the instructions.
Comments closedReza Rad explains why the Power BI Service is useful:
The Power BI toolset comes in many shapes and forms. There is a Power BI Desktop, Power BI Mobile app, Power BI Report Server, and Power BI Service (and some other applications and components too). The questions I hear from the new users of Power BI are; Do I need to have an account for Power BI? do I need to use the Power BI website for creating visualization etc.? What is the Power BI website or service, and what is its usage? If I can do the reporting using Power BI Desktop for free, then why would I need the service? In this article and video, I will answer all of that.
Click through for a video or for the article explaining the purpose behind the Power BI Service. Having done work with places using Power BI Report Server and places using the Power BI Service, I will say that the latter takes more work to get corporate-compliant but offers a whole lot more.
Comments closedKevin Chant does a bit of CI/CD:
In this post I want to show how a GitHub CI/CD experience for Azure Synapse Link for SQL Server 2022 can look. Which uses GitHub Actions. Including how to automatically stop and start it in the pipeline.
In my last post I showed a complete CI/CD experience for Azure Synapse Link for SQL Server 2022 using Azure DevOps.
With this in mind, in this post I show an alternative GitHub CI/CD experience for Azure Synapse Link for SQL Server 2022 which uses GitHub Actions. Which includes automatically stopping the link before the database update and starting it again after the update has completed.
Read on to learn how.
Comments closedMeagan Longoria explains an important part of source control repositories:
I’ve seen a few people start Azure Data Factory (ADF) projects assuming that we would have one source control repo per environment, meaning that you would attach a Git repo to Dev, and another Git repo to Test and another to Prod.
Microsoft recommends against this, saying:
Read on for the citation as well as the practical reason why we don’t want multiple repos. This is true not only for Azure Data Factory but for every development project. You have one repository with branches. Certain branches represent checkpoints where code goes out to a specific environment via use of a release tool (e.g., Azure DevOps release pipelines, GitHub actions, etc.).
Comments closedReitse Eskens continues a series on performance testing Azure SQL DB tiers:
So far, my blogs have been on the different Azure SQL DB offerings where there are differences between DTU and CPU based. But in general, the design is recognizable. With the hyperscale tier, many things change. There are still cores and memory of course, but the rest of the design is totally different. I won’t go into all the details, you’re better off reading them here [https://learn.microsoft.com/en-us/azure/azure-sql/database/service-tier-hyperscale?view=azuresql] and here [https://learn.microsoft.com/en-us/azure/azure-sql/database/hyperscale-architecture?view=azuresql] , but the main differences are the support of up to 100 TB of data in one database (all the other tiers max out at 40 TB), fast database restores based on file snapshots, rapid scale out and rapid scale up.
There are differences in testing this one versus the others, so buyer beware.
Comments closedPaloma Garcia Martin asks, Are we there yet? Are we there yet? Are we there yet?
When you start a PITR restore in your Managed Instance, is very useful be able to track how it progresses. Azure Portal does not show too many details about it, but we can use Managed Instance logs to track it.
The way to do it, is quite simple.
Click through for one way to track restore progress.
Comments closedOn-premises applications are mostly single-tenant. They support a single organization. We do occasionally see multi-tenant databases. They hold the same types of information for many organizations.
But what about SaaS based applications? By default, you’ll want to store data for many client organizations. Should you create a large single database that holds data for everyone? Should you create a separate database for each client? Or should you create something in-between.
As with most things in computing, there is no one simple answer to this. Here are the main decision points that I look at:
Click through for Greg’s thoughts on the matter. Most of these factors are also relevant for on-premises SQL Server installations, not just Azure SQL DB/Managed Instance.
Comments closedArun Sirpal doesn’t have time to create indexes:
I will use a clone of the table to compare it to when search optimisation is on. I will make sure no caching in on which could affect the test.
I activate the feature via:
ALTER TABLE data_staging ADD SEARCH OPTIMIZATION;This takes time! If you run something like the below to confirm 100% completion. This is because there is a maintenance service that runs in the background responsible for creating and maintaining the search access path:
Click through to see what happens and the kinds of performance gains Arun realized.
Comments closedBalmukund Lakhani has an announcement:
Approximate query processing was introduced to enable operations across large data sets where responsiveness is more critical than absolute precision. Approximate operations can be used effectively for scenarios such as KPI and telemetry dashboards, data science exploration, anomaly detection, and big data analysis and visualization. Approximate query processing family has enabled a new market of big data HTAP customer scenarios, including fast-performing dashboard and data science exploration requirements.
Today, we are announcing preview of native implementation of APPROX_PERCENTILE in Azure SQL Database and Azure SQL Managed Instance. This function will calculate the approximated value at a provided percentile from a distribution of numeric values.
This is way faster than using the PERCENTILE_CONT() or PERCENTILE_DISC() window functions. For a decent-sized query, I was getting anywhere from 5-20x performance improvements, and the larger the dataset, the bigger the gains. It is important to note that the approximate percentiles are not window functions, so you don’t get one row back per row of input.
Sidney Cirqueira shows how to monitor SQL requests in Azure Synapse Analytics:
Today I would like to share a scenario that I was working on one of my serverless SQL Pool support cases. The customer asked for an advice on how to monitor serverless SQL requests by using log analytics.
The intention of this guide is to help you with choosing the configuration required to easily setup the Synapse Analytics Workspace monitoring and all other considerations about how to monitor serverless SQL requests with Azure Monitor. Spoiler: At the end of this article, I will share the latest version of the serverless workbook posted on the Azure_Synapse_Tool_Box. This includes a really cool way to see query execution information.
Read on for that and definitely check out the Azure Synapse Toolbox if you’re a Synapse user.
Comments closed