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11 Goals of High Functioning SQL Developers


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This session focuses on what it takes to be high-functioning SQL developers in a world of continuous delivery and continuous integration.

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11 Goals of High Functioning SQL Developers

  1. 1. 11 Goals A portrait of a highly functioning SQL Server development shop Ike Ellis, MVP Crafting Bytes A San Diego Software Studio #SQLintheCityUS
  2. 2. Two pairs of eye on all SQL code, minimum – sometimes 3 or 4 • They pair minimum • Sometimes they mob • This allows for someone to do the right thing • And they can slack and work
  3. 3. They don’t give estimates • They work off of a prioritized list and deliver a piece of value every day to the organization • They let the organization change anything on the list, except the first three things • You get it when it’s ready
  4. 4. They test all of the time…mostly test first Write a line of code Deliver Code to Users #SQLintheCityUS
  5. 5. #SQLintheCityUS
  6. 6. They never code with production data on a dev server 1. Save Schema 2. Restore Database 3. Reset security 4. Restore Schema #SQLintheCityUS
  7. 7. Why do they do this? • Bugs in production are not reproducible in development • They like seeing mock data because it gives them better testing of user interfaces and other things • They like to be able to quickly answer questions #SQLintheCityUS
  8. 8. What’s the downside? • Break tests because of old data • Production data shouldn’t be seen by developers • If development environments are on laptops, laptops get stolen and the company has lost production data • Development servers are not usually backed up or secured properly --And the development database is way too large--- #SQLintheCityUS
  9. 9. What do they do instead? • All development data is mocked – Tests are repeatable – They use MOQ/Xunit – But you can easily use tSQLt/RedGate SQL Test, instead • Thread the buggy data, back through the development process • Write a test that will fail with the new data • Solve the issue • Watch the test pass • Check the test into source control • Run the tests all the time • Bug never happens again I’m mocking your data #SQLintheCityUS
  10. 10. The dev environment database is stays very small • Why is it large? • 15 years of data • 75% of blob storage – (PDFs, DOCs, AVIs) • Lots of temp files, ETL imports, etc Huge Bloated Database #SQLintheCityUS Tiny Dev Database
  11. 11. What’s wrong with data bloat? • Database is not portable • Multiple database environments are difficult to setup • Hard to backup • Hard to restore • Hard to rebuild • Hard to obfuscate • Hard to query • Development takes a really long time • Big data costs money to store – big SANs – big developer laptops #SQLintheCityUS
  12. 12. They never update production outside of their development pipeline • Changes are fast • Bugs are fixed quickly • All because they’re release pipeline is very fast #SQLintheCityUS
  13. 13. What’s wrong with updating production servers? • Changes don’t get tested • Changes don’t go back into the development environment • Changes can cause table and schema locks and cause unexpected downtime • These changes are often not peer reviewed #SQLintheCityUS
  14. 14. They avoid three part database names I like to reference you! Oooo, I like to reference you, too! #SQLintheCityUS
  15. 15. Let’s get married! #SQLintheCityUS
  16. 16. But not all marriages are happy… • Creates a tight coupling • Moved together – To a new server • Have to be tested together • Have to be integrated together • Have to change together • Have to be upgraded to a new version • Have to be backed up together • Have to be restored together #SQLintheCityUS
  17. 17. They avoid four part database names I like to reference you! Oooo, I like to reference you, too! #SQLintheCityUS
  18. 18. Why is this bad? • Servers are now anchored together • It complicates building a test, QA, integration, or canary environment • Security concerns #SQLintheCityUS
  19. 19. Developers have their own database • Source control history – Generation 0 – Visual Source Safe – Generation 1 – Subversion, TFS – Generation 2- GIT, Mercurial • Sharing databases is like going back to generation 0. #SQLintheCityUS
  20. 20. They avoid rollback plans. Instead, they keep changes inside of their development pipeline • You can’t unbake this turkey • You have to fix it • Those fixes need to be tested – run it through again! #SQLintheCityUS
  21. 21. They obfuscate production data in all of their environments I was your data, but now you don’t recognize me
  22. 22. They use a canary If I die, you better not deploy! #SQLintheCityUS
  23. 23. They never let more than one application touch a transactional database • Microservices • One application to one database • Change together in the same pipeline • Decouple everything, and I mean everything, else
  24. 24. They build their databases and they fix compile errors • Lots of processes, including RedGate CI Server, will do this • Show bad bindings • Show bad columns • Show sprocs that just won’t run • Show tight-coupling #SQLintheCityUS
  25. 25. They write never write SQL Statements against tables • More coupling #SQLintheCityUS
  26. 26. Ike Ellis • Crafting Bytes – Small San Diego Software Studio – Modern web, mobile, Azure, SQL Server – Looking for future teammates! • Book: Developing Azure Solutions • Podcast Guest: – Talk Python to Me – Dec 2015 – .NET Rocks – Sept 2015 • • • • SDTIG – Ike Ellis, MVP @ike_ellis 619.922.9801 #SQLintheCityUS