The presentation discusses the journey from a traditional development process to adopting Agile and DevOps practices for database operations. It covers moving from siloed teams to Scrum and then combining Scrum and Kanban. Key aspects included establishing source control for database scripts, implementing continuous integration and delivery pipelines for databases, and defining a "contract" to facilitate collaboration and communication around database changes. Automating processes, tracking changes, and integrating databases into feature development helped increase delivery speed, reliability, and number of supported customers.
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!
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)
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
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
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
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)
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
