March 18, 2021 – Solving the dev database problem with GitHub, Docker and dbaclone by Alex Yates & Sander Stad
11:30 am – 12 pm Social/Networking
12:00 – 12:05 UG Updates
12:05 – 12:55 Presentation
Solving the dev database problem with GitHub, Docker and dbaclone
DevOps promotes self-service access to usable, production-like dev/test
environments – but so many data folks are encumbered with shared
development databases which are often inconsistent with production. It’s
difficult to isolate the development of different features, so they are
rolled together into big releases. It’s no wonder database deployments
are often expensive, complicated and risky.
What if it was possible for developers to provision themselves a
disposable, masked copy of last night’s production 64 TB database on
their regular workstation, with limited storage, in a matter of seconds?
What if it was as easy as “git clone f5”?
In this session attendees will learn to use GitHub, Docker, SSDT and
dbaclone to unshackle themselves from “Wild West” dev databases
and empower them to use modern branching techniques and Azure DevOps to
continuously deliver their updates to production.
The result? Empowered developers who can deliver value in smaller
batches, through significantly more regular and reliable deployments,
delivering value to users much more quickly.
More from the DevOps Flow series:
- DevOps 101 for Data Folks:
- Simple database deployments with GitHub, Azure DevOps Services and SSDT:
- Solving the dev database problem with GitHub, Docker and dbaclone:
- Zero downtime database deployments
Alex Yates has been helping organisations to apply DevOps principles to their data since 2010. He’s most proud of helping Skyscanner develop the ability to deploy 95 times a day. Originally for Redgate, later for DLM Consultants, Alex has worked with clients on every continent except Antarctica – so he’s keen to meet anyone who researches penguins.
A keen community member, he co-organises Data Relay, is the founder of www.SpeakingMentors.com and has been recognised as a Microsoft Data Platform MVP since 2017.
Meeting ID: 303 720 7595
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