[2017.06 Meetup #14] [TALK #1] Eduardo Piairo - DevOps for Databases

This talk is the combination of the different moments of the agile journey through Scrum and Kanban and the operations scope at different levels: database and application (and even infrastructure).

With the Scrum adoption, database started to represent a bottleneck in the development process. To solve this problem the techniques: SC, CI and CD were applied to database development allowing to narrow gap between application and databases development. Additionally, allowed to management to understand the developing software is not enough, you need to deliver it.

This journey also represents my DevOps definition evolution from just “relieve the delivery pain” to a more rich, complex, technical and human definition.

Eduardo Piairo is a deployment pipeline craftsman always ready to learn new ways to implement Source Control, Continuous Integration and Continuous Delivery for applications, databases and infrastructure. Eduardo is also the main organizer of the DevOps Porto meetup.

Transcript

1. OPERATIONS FOR DATABASES Eduardo Piairo The Agile/DevOps Journey
2. OPERATIONS FOR DATABASES Eduardo Piairo Operations Engineer DevOps Porto Founder About me @EdPiairo https://pt.linkedin.com/in/jesuspiairo eduardopiairo@gmail.com http://www.eduardopiairo.com/
3. OPERATIONS FOR DATABASES Agile journey Scrum Kanban DevOps This presentation Database operations Automation Source Control Continuous Integration Continuous Delivery The definition and the interpretation of the covered concepts are attached to the cultural context of a specific organization on a certain period!
4. OPERATIONS FOR DATABASES 1.Before Scrum 2.Scrum 3.Kanban 4.Scrum + Kanban Agile journey
5. OPERATIONS FOR DATABASES 1.Before Scrum 2.Scrum 3.Kanban 4.Scrum + Kanban Agile journey
6. OPERATIONS FOR DATABASES Before Scrum • Before Scrum - The “real agile” method • Centralized decision mechanism • Growing phase • Size (5 to 15) • Complexity (more and more components)
7. OPERATIONS FOR DATABASES Before Scrum Application #1 Application #2 Application #3 Shared database(s) “Team” #1 “Team” #2 “Team” #3 “Team” #T-SQL
8. OPERATIONS FOR DATABASES 1.Before Scrum 2.Scrum 3.Kanban 4.Scrum + Kanban Agile journey
9. OPERATIONS FOR DATABASES Scrum • Scrum - The “magic” scrum • Scrum for the masses (>20) • Pure Scrum approach – operations as development team • 2 week sprint, sprint goal • The team was “too reactive”
10. OPERATIONS FOR DATABASES DevOps for databases - The beginning Application #1 Application #2 Application #3 Shared database(s) Team #1 Team #2 Team #3 Team #T-SQL
11. OPERATIONS FOR DATABASES DevOps for databases - Building a deployment pipeline (value stream) Source Control Continuous Integration Continuous Delivery Database + Application
12. OPERATIONS FOR DATABASES What’s so special about databases? DevOps for databases - The special case of the database
13. OPERATIONS FOR DATABASES DevOps for databases - Problems to fix • Databases are out of pace with application development • Synchronization between development and DBA teams • No traceability of database changes (changes history) • What changed? Who? When? Why? • Manual databases processes prevent the CI and CD utilization in their full extent • Time consuming and error prone • Releases are less frequent and risky
14. OPERATIONS FOR DATABASES DevOps for databases - Problems to fix • Bugs in production environment • Database related bugs are only discovered after deployment to production • Manual or inexistent tests • Fixes and hotfixes have time cost, what can lead to delay a release • Database setup time of a new environment • Expensive process for new clients
15. OPERATIONS FOR DATABASES DevOps for databases - Problems to fix Databases became a bottleneck in an agile delivery process
16. OPERATIONS FOR DATABASES DevOps for databases - The solution Source Control Continuous Integration Continuous Delivery Automation + Change control
17. OPERATIONS FOR DATABASES Decision #1 Let’s automate Let’s do source control DevOps for databases - The solution
18. OPERATIONS FOR DATABASES DevOps for databases - The value of automation • Enable control over database development • Increase speed of response to change • Keep a versioned “history” of database states • Greater reliability of the release process • Increase release frequency through repeatability of processes • Reduce time spent fixing bugs • Remove/reduce human intervention in the release process • The build step is automatic triggered by a “push” into source control repository • The deploy step is automatic triggered by a successfully build process
19. OPERATIONS FOR DATABASES DevOps for databases - The value of automation • Without automation your are working in a amnesic state • (Re)Learn and forget it vs Improve and forget it • You do not want to depend on the “best of the best”
20. OPERATIONS FOR DATABASES DevOps for databases - The 1st step: Source Control • First step in your database deployment pipeline • Traceability through change history • SQL as documentation • Shared code-base and shared process • Enforceable standards to reduce conflicts • Fundamental resource: SQL script
21. OPERATIONS FOR DATABASES Decision #2 Database source control: Migrations vs State DevOps for databases - The 1st step: Source Control
22. OPERATIONS FOR DATABASES DevOps for databases - Migrations vs State • State based solutions • Script represents the current database state • Your source of truth is how the database should be • Migrations based solutions • Script represents a migration • Migration represents how to transition to the next database version • Your source of truth is how the database should change Flyway: open source database migration tool • Simplicity: easy to setup, no need to install • Zero dependencies (java + jdbc) • Scripts are written in SQL
23. OPERATIONS FOR DATABASES DevOps for databases - Communicating through a contract • Contract – communication mechanism for change management • Set of rules and expectations • Define responsibility frontiers • Sets a common language Application #1 Application #2 Application #3 Shared database(s) Team #1 T-SQL Script Team #2 Team #3 Team #T-SQL
24. OPERATIONS FOR DATABASES DevOps for databases - Scripting rules • Scripting rules • Rule 1: Script version (timestamp) • Rule 2: Operation type • Rule 3: Object type • Rule 4: Object name Example: V20160220.1100__Create_TB_MyTable.sql • One script, one operation type, one object (small batches) • Merge conflicts management • Patterns identification • File system scripts history search
25. OPERATIONS FOR DATABASES DevOps for databases - Communicating through a contract – The pipeline • Contract – communication mechanism form change management • Should be reflected in your development pipeline • The better/clearer your pipeline, the less you need to document (your code is your documentation) • Everything is negotiable in the contract, except its application
26. OPERATIONS FOR DATABASES 1.Before Scrum 2.Scrum 3.Kanban 4.Scrum + Kanban Agile journey
27. OPERATIONS FOR DATABASES Kanban • Kanban 101 • Focus on development teams necessities • 4 week iterations • A bad choice • Different “language” from other teams • Desynchronization between operations and development teams
28. OPERATIONS FOR DATABASES DevOps for databases - Communicating through a contract • Contract – change communication management tool • Change description (Source Control) • Change validation (Continuous Integration) • Change implementation (Continuous Delivery)
29. OPERATIONS FOR DATABASES 1.Before Scrum 2.Scrum 3.Kanban 4.Scrum + Kanban Agile journey
30. OPERATIONS FOR DATABASES Scrum + Kanban • Scrum + Kanban – The best of two worlds • 2 week sprint, sprint goal • Task definition was based on teams necessities and our necessities • Team capacity < 70% (enough bandwidth to react) • Strong and disciplined team • Integration in solutions design • Operations as a service
31. OPERATIONS FOR DATABASES DevOps for databases - Communicating through a contract • Extending the Contract – communication mechanism for change management • Applications • Databases • Infrastructure
32. OPERATIONS FOR DATABASES Why DevOps? • Developing software is not enough, you have to deliver it • Communication framework for manage change • You can not stop change, but you can control it • CAMS • We change the culture (with lot of negotiation and evangelization) • We invested in automation (started with 0 automation in a never ending automation journey) • We conquer work flow visibility, so we were able to start measure • We spread the contract across the organization
33. OPERATIONS FOR DATABASES Some metrics/results • We went from 100% manual databases changes to about 98% automatic changes (100% controlled changes) • On average 200 scripts were created per day • In one year we achieved 10k scripts • We went from supporting only 1costumer to 4 costumers at the same time • Each week, costumer requests were delivered • Fixes were applied whenever necessary
34. OPERATIONS FOR DATABASES The DevOps way • DevOps: contract for collaboration and communication (change management “framework”) • Change description (Source Control) • Change validation (Continuous Integration) • Change implementation (Continuous Delivery) • Applications, databases, infrastructure
35. OPERATIONS FOR DATABASES Reading material
36. OPERATIONS FOR DATABASES Q&A @EdPiairo https://pt.linkedin.com/in/jesuspiairo eduardopiairo@gmail.com http://www.eduardopiairo.com/