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Adding unit tests to the database deployment pipeline
This talk will address how to add the unit testing framework tSQLt to the database deployment pipeline. The purpose is to reduce the cost of validate every change in the database with a fully automated pipeline.
DB Engineering: Shall we test the code before we hit prod?
Deploying untested code to production isn't ideal, manual testing can be slow and unreliable. In this talk we will look at the different types of automated testing we can use for our databases to give us confidence in the quality of the code.
Disposable Dev environments with Azure DevOps and AzureRM
Using Azure DevOps and Azure RM templates to created isolated environments for testing PaaS solutions.
Lets go deep in SQL Server Unit Testing with Visual Studio
Everyone that has been involved in Software Development can notice how huge the impact of a bug can be, and Databases are not the exception. In this session, you will learn how to test your SQL Server projects using Visual Studio and SQLUnitTesting.
Making Managed Instance Perform, a dive into storage.
Moving to the cloud means that we need to take a different approach when it comes to how we design and tune databases. Managed Instance included, get the storage configuration wrong and it will not perform. We'll look at the storage options and architecture for Managed Instance before demonstrating how to get tune the storage layer to get the performance we need
Power BI Premium on a budget
Power BI Premium has many features that organisations desire yet the price makes it impractical for most. In this talk you will learn how Power BI Embedded can be used to enable many of these features at a much lower cost.
SentryOne Tools for Productivity and Performance
This quick vendor session demonstrates the spectrum of SentryOne's best-of-breed products for the Microsoft Data Platform, from Task Factory, to Plan Explorer, to DOC xPress, to the SentryOne monitoring platform, and beyond.
Would you run production SQL Server on Docker?
Should you run SQL Server on physical machines, virtualised, in the cloud or do you run it on Docker? It may sound crazy to run your data tier in ephemeral containers, but I'll discuss the reasons why this might be a good idea.
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