1. Thanks to our Sponsors Platinum Sponsor: Gold Sponsors:
Global Alliance Partners:

2. SQL Server DevOps Simplified with Production Database Clones
Paul Stanton, Co-founder

3. Agenda What is SQL Server Devops? Choices: production or stubbed data
Choices: containers or VMs
Architecture for use of database clones
Steps and Demo
Resources to get started

4. SQL Server DevOps begins with . .
Database environments for
Development and Test
Staging
Production DB debugging for hotfixes
Reporting and BI
ETL and Data Warehousing
Develop, test and deploy of upgrade and rollback scripts
What form of database -- production or stubbed database?
How to deliver -- SQL Server containers or virtual machines?

5. Production database clones Built DB with stubbed data (DacPac)
What form of database?
Production database clones
Built DB with stubbed data (DacPac)
Highest quality artifact, includes production data, schema and objects
Artifact limited to schema and objects, with stubbed test data
Test development is simplest possible
Test development must simulate production data
Delivery in 30 seconds
A multi-DB environment will take 20 – 60 minutes
Improved release as data and performance issues are recognized and fixed
Data and performance issues are recognized at a later point, complicating the DevOps process
Supports prod DB debug & Hot Fix, other uses NA

6. SQL containers or instances?
SQL Server Containers
Instances
20+ SQL Server environments per 4 core VM, drives ~5-10:1 reduction in VMs
Typically 1 SQL Server instance per VM
Provision and tear down in seconds
Several minutes to 30+ for multi-database environment
Maintenance dramatically reduced
On-going maintenance, configuration drift
Cloud native and Kubernetes ready NA

7. Architecture

8. Steps and Demo
1. Build an image (database snapshot) with included Git repo clone
2. Set automated image updates with Diff or Transaction Log backups
3. Self-provision SQL Server containers and cloned databases
4. Manage a multi-stage pipeline with Azure DevOps

9. Build the Image FROM mssql-2017 SETUPCLONING FULL db \\pathto\db.bak
COPY datamasking.sql .
RUN datamasking.sql
Build the Image

10. Build an image with Git repo clones
The Docker images includes a “git pull” to ensure each container include repo scripts, with run time control over scripts:
>docker create -e RUN=“scripts/upgrade.sql” gitclone1
>docker create gitclone1
>docker create -e RUN=“scripts/upgrade.sql, scripts/rollback.sql” <image>

11. 2. Set the image update schedule

12. Provision SQL Server containers w/clones
Docker clients
>docker create <imagename>
Web application
One click to deliver an environment from an image
REST API
curl, any code base
Any orchestrator - Azure devops, Jenkins

13. 4. Implement Azure DevOps pipeline
Download the Azure DevOps pipeline yaml from Windocks
Update pipeline yaml to reflect your pipeline environment variables:
Server IP address
Image name
Migration scripts for testing

14. Conclusions Speed: ~20 seconds per environment
Scales to large/complex environments
Improve release quality: identify performance and data issues earlier
Economy and efficiency (20+ containers on a 4 core VM), simplified Test development
Reliability: no configuration drift, no changes in CI pipeline
Database clones combined with containers is cloud-native and Kubernetes ready

15. Resources to get started
Database cloning with containers with a free Windocks Community Edition: ask for the Azure DevOps yaml file
Setup your own free Azure DevOps pipeline
Red Gate SQL Clone: