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DevOps Flow Series, part 2 of 4
Simple database deployments with GitHub, Azure DevOps Services and SSDT
For many of us, database deployments are time consuming, painful and risky.
The automated deployment of applications, and even servers, is now ubiquitous
- but most of us have not applied the same principles to our databases.
In this demo heavy session, we'll script out our database source code locally
using SSDT and commit it to GitHub. Then we'll build it automatically upon
commit, and deploy it to Azure at the click of a button with Azure DevOps
We'll also discuss some of the common blockers and how they can be resolved.
For example, we'll discuss shared development databases, branching plans and
masking production data for development.
You'll leave this session with a better understanding of how to deliver
working software more regularly and more reliably, enabling you to respond
better to business demands.
Simple Abstract:
100% demos: We will create a new public repository in GitHub, script out a
database using SSDT, and set up an automated Azure DevOps Services Release
Pipeline to deploy our source code to Azure.
More from the DevOps Flow series:
1. DevOps 101 for Data Folks:
2. Simple database deployments with GitHub, Azure DevOps Services and SSDT:
3. Solving the dev database problem with GitHub, Docker and dbaclone:
4. Zero downtime database deployments
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