| DevOps Flow Series, part 2 of 4 | |
| Title: | |
| Simple database deployments with GitHub, Azure DevOps Services and SSDT | |
| Abstract: | |
| 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 | |
| Services. | |
| 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: | |
| https://gist.github.com/Alex-Yates/efef91357c6bd0dc1fbe63f2eb464f68 | |
| 2. Simple database deployments with GitHub, Azure DevOps Services and SSDT: | |
| https://gist.github.com/Alex-Yates/43c7f4d51a651cd8b3dcdcb48843691f | |
| 3. Solving the dev database problem with GitHub, Docker and dbaclone: | |
| https://gist.github.com/Alex-Yates/8125be587e58863ad35e0845ab6ffd5a | |
| 4. Zero downtime database deployments | |
| https://gist.github.com/Alex-Yates/ac4c791bbd98eb3269f35db59cc30f88 |
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