Adopting DLM at Greentube
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The document discusses Greentube's adoption of Database Lifecycle Management (DLM). Manoj Lona and Alex Yates presented on how Greentube implemented DLM to have a single source of truth for database deployments across multiple data centers. They used filters and post-deploy scripts to deploy different versions based on data center customization needs from a single source. This improved their development process by reducing bugs and conflicts between developers.
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Adopting DLM at Greentube
- 1. @ManojLona @_AlexYates_ #SQLSatVienna Manoj Lona and AlexYates Adopting Database Lifecycle Management (DLM) at Greentube
- 2. @ManojLona @_AlexYates_ #SQLSatVienna Founder of DLM Consultants Microsoft Data Platform MVP workingwithdevs.com alex.yates@dlmconsultants.com AlexYates @_AlexYates_ DB Admin & DevTeam Lead at GreenTube linkedin.com/in/manoj-lona/ mlona@greentube.com Manoj Lona youtube.com/c/lonatunes
- 3. @ManojLona @_AlexYates_ #SQLSatVienna DB Admin & DevTeam Lead at GreenTube linkedin.com/in/manoj-lona/ mlona@greentube.com Manoj Lona youtube.com/c/lonatunes
- 8. @ManojLona @_AlexYates_ #SQLSatVienna Founder of DLM Consultants Microsoft Data Platform MVP workingwithdevs.com alex.yates@dlmconsultants.com AlexYates @_AlexYates_ 2010 2014 2016 2017 2012 2018 2001
- 9. @ManojLona @_AlexYates_ #SQLSatVienna Objective 1 “We want a single source of truth that can deploy to all data centres, taking into account data centre specific customizations”
- 10. @ManojLona @_AlexYates_ #SQLSatVienna 2 versions = 1 relationship
- 11. @ManojLona @_AlexYates_ #SQLSatVienna 3 versions = 3 relationships
- 12. @ManojLona @_AlexYates_ #SQLSatVienna 6 versions = 15 relationships
- 13. @ManojLona @_AlexYates_ #SQLSatVienna 2 - 1 3 - 3 4 - 6 5 - 10 6 - 15 7 - 21 8 - 28 9 - 36 10 - 45 15 - 105 << Greentube in 2016
- 14. @ManojLona @_AlexYates_ #SQLSatVienna 2 - 1 3 - 3 4 - 6 5 - 10 6 - 15 7 - 21 8 - 28 9 - 36 10 - 45 15 - 105 << Greentube in 2016 << Greentube in 2017?
- 15. @ManojLona @_AlexYates_ #SQLSatVienna 2 - 1 3 - 3 4 - 6 5 - 10 6 - 15 7 - 21 8 - 28 9 - 36 10 - 45 15 - 105 << Greentube in 2016 << Greentube in 2017? << Greentube in 2018???
- 24. @ManojLona @_AlexYates_ #SQLSatVienna DC 6 DC1 DC2 DC 3DC 5 DC 4 DC1 = DC2 DC 3 = DC 4 = DC 5
- 29. @ManojLona @_AlexYates_ #SQLSatVienna How it works The principle: One single version in source control, from which you can build DC1, DC2+3 and DC4+5+6 The implementation: Clever use of filters and post deploy scripts
- 30. @ManojLona @_AlexYates_ #SQLSatVienna DC1 How it works DC2 Stuff on both, but different Stuff on one or the other Stuff that’s consistent Stuff on both, but different Stuff on one or the other Stuff that’s consistent
- 31. @ManojLona @_AlexYates_ #SQLSatVienna How it works DC1 DC2 Filter for DC1 - exclude: Filter for DC2 - exclude: DC2 post deploy to update modified objectsStuff that’s consistent Stuff on one or the other Stuff on both, but different Simple case
- 35. @ManojLona @_AlexYates_ #SQLSatVienna But it was a lot of avoidable work
- 37. @ManojLona @_AlexYates_ #SQLSatVienna STAGING PRODUCTION TEST/INTEGRATION SERVERS RELEASE SERVERS
- 39. @ManojLona @_AlexYates_ #SQLSatVienna What we did • Provisioning • (Auto-linking databases) • Training
- 40. @ManojLona @_AlexYates_ #SQLSatVienna Problems along the way • CLR (post-deploy script) • Out Of Memory exceptions • Test Data
- 42. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 43. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 44. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 45. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 46. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 47. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 48. @ManojLona @_AlexYates_ #SQLSatVienna Possible solutions 1. Create subset of data, small enough to go on every dev box 2. Re-write tests to initialise their own data (e.g. tSQLt) 3. Hybrid of 1 and 2 4. In-house application 5. Virtualisation technique (e.g. SQL Clone) 6. Do nothing
- 51. @ManojLona @_AlexYates_ #SQLSatVienna Suitability, cost and effort Solution Suitability Cost Effort 1. Subset of data 2. Re-write tests 3. Hybrid of 1 + 2 4. In-house app 5. Virtualisation 6. Do nothing 7. …
- 52. @ManojLona @_AlexYates_ #SQLSatVienna Respectful debate… Solution Suitability Cost Effort 1. Subset of data 5. Virtualisation
- 53. @ManojLona @_AlexYates_ #SQLSatVienna Respectful debate… Solution Suitability Cost Effort 1. Subset of data 5. Virtualisation Subset of data
- 56. @ManojLona @_AlexYates_ #SQLSatVienna #winning • Automated database builds upon commit • Automated database deployments to various environments • Semi-automated deployments to production with approval being looked into
- 57. @ManojLona @_AlexYates_ #SQLSatVienna #winning • Benefits Builds catch bugs at an early stage Developers no longer step on each other’s toes Static/Enum data can be checked into source control • Downside Development process a bit slower (but throughput is higher :-)
- 62. Our Partners
Editor's Notes
- Was all hunky-dory with two data centres Feature deployment only where needed Troubles started brewing on the horizon with the 3rd DC and more in the pipeline Various attempts to find a solution on our own With the 5th DC we got in touch with Redgate
- Was all hunky-dory with two data centres Feature deployment only where needed Troubles started brewing on the horizon with the 3rd DC and more in the pipeline Various attempts to find a solution on our own With the 5th DC we got in touch with Redgate
- Was all hunky-dory with two data centres Feature deployment only where needed Troubles started brewing on the horizon with the 3rd DC and more in the pipeline Various attempts to find a solution on our own With the 5th DC we got in touch with Redgate
- Was all hunky-dory with two data centres Feature deployment only where needed Troubles started brewing on the horizon with the 3rd DC and more in the pipeline Various attempts to find a solution on our own With the 5th DC we got in touch with Redgate
- Was all hunky-dory with two data centres Feature deployment only where needed Troubles started brewing on the horizon with the 3rd DC and more in the pipeline Various attempts to find a solution on our own With the 5th DC we got in touch with Redgate
- After seeing the solution, we didn’t like it. We were making life more complicated for ourselves. We understood it was much simpler to standardise our databases.
- - - - Synchronized tables across all data centers - - - Introduced new feature flags to standardize code base >>> New deployment regime to deploy standardized code to all data centers
- All our resources can be found at
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