SQL Server Linux

If you have come from a windows background you may be curious about the world of SQL Server Linux. Yes, the operating system and the implementation of it differs to the traditional Windows environment but once installed, it’s just good old SQL server and those lovely DBCC commands and backup statements work, all your DMVs are ready for you too.

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Azure SQL Database – Greatest and Least TSQL

Being in the cloud does have many benefits, from lower administration to fast scaling but another “side effect” of operating in Azure SQL Database is the cloud first nature of changes. By this I basically mean new features always get pushed to Azure first before the classic on-premises version so some gems come to light.

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Azure SQL Database and Memory

There are many factors to consider when you are thinking about the move to Azure SQL Database (PaaS) – this could be single databases (provisioned compute or serverless) to elastic pools. Going through your head should be how many vCores do you want? What are the I/O requirements, do we need access to certain features like in-memory OLTP? But what about the memory requirements? This has always been a key requirement for SQL Server – those wonderful words – Min / Max memory settings.

How does this relate to Azure? Well it all depends on your vCore count and the generation of hardware we select during the build process.

There are currently 4 hardware generations ( each has its own purpose) :Gen4, Gen5, Fsv2-series and M-series. Each type has xGB per vCore up to a certain max. So it is important to remember this when sizing your workloads. (screen shot summarising is below) https://docs.microsoft.com/en-us/azure/azure-sql/database/service-tiers-vcore?tabs=azure-portal

So, for example I select a provisioned Azure SQL Database – 12 vCore on Gen 4 means I will have 84GB memory available for my workload.

Azure Defender for SQL

If you have been following me or generally topics around Azure SQL Database and security you would know that it is important to leverage Advanced Data Security (ADS) for Azure SQL Database, if you remember this meant having tools such as advanced threat protection, vulnerability scans at your finger tips.

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Azure Databricks – Adding Libraries

It is a really common requirement to add specific libraries to databricks. Libraries can be written in Python, Java, Scala, and R. You can upload Java, Scala, and Python libraries and point to external packages in PyPI, Maven, and CRAN repositories.

Libraries can be added in 3 scopes. Workspace, Notebook-scoped and cluster. I want to show you have easy it is to add (and search) for a library that you can add to the cluster, so that all notebooks attached to the cluster can leverage the library.

Within the Azure databricks portal – go to your cluster.

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Azure Databricks and Azure Key Vault

The key vault should always be a core component of your Azure design because we can store keys, secrets, certicates thus abstract / hide the true connection string within files. When working with databricks to mount storage to ingest your data and query it ideally you should be leveraging this to create secrets and secret scopes.

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