1. The Hard Problems
of Continuous Deployment
Timothy Fitz (.com)

2. “Continuous deployment involves
deploying early and often, so as to
avoid the pitfalls of "deployment hell".
The practice aims to reduce timely rework and thus
reduce cost and development time.”

3. “Our highest priority is to satisfy
the customer through early
and continuous delivery of
valuable software.”
- Principles behind the Agile Manifesto (2001)

4. The Hard Problems
(The ones I’m going to cover)
• Data
• Mobile
• Scale

5. Data makes CD harder
• Updating data is slow
• Moving data is slow
• Schemas live outside code deploy process
• Rollbacks are often hard or impossible

6. Schema rev. N, N+1 compatible
• Add the column in production
• Push the code that writes to that column
• Optionally, run a data migration to populate
the existing rows with data
• Push the code that reads from that column.

7. Apply only cheap changes
• Only apply changes that are cheap enough to
not affect live traffic
• More complex changes split into tiny steps:
– Create new table
– Write to both
– Cut over eventually
– Drop old table

8. Apply change to standby
• Run two DB instances
• Apply change to standby
• Failover if successfully applied
• Might run 3rd db instance for availability

9. Blue/Green Deploy
• Run two copies of entire cluster
• All databases are replicated
• Lets you test, update and rollback both code
and schema in one step

10. Schemaless NoSQL
• “Schemaless” really means schema is in your
source code
– Which is great! We can CD schema changes

11. Schemaless-style SQL
• Benefits of existing SQL databases while still
being pseudoschemaless
• (thing_id, key, value) table
• (guid, blob) table

12. Recap
• Apply only cheap changes
• Apply changes to standby
• Blue/Green Deploy
• Schemaless NoSQL
• Schemaless-style SQL

13. Mobile
• Users must opt-in to every update
• iOS submissions take a week to be approved
• Luckily, lots of tools aimed at the space

14. Remember the basics
• CI server / automated tests are critical
• Can’t fallback on production alarms / rollback
• Hosted options: http://cisimple.com

15. Data-drive everything
• Build your views / content from data files
• Ping server for updates
• Hosted: http://appgrok.com/
– Lets you deploy txt, png and xib dynamically!

16. 99% HTML
• Entire app is a single UIWebView
• Glue native code to allow access to APIs
• Clutch.io is awesome (and FOSS now)
– Live reloading for local dev
– Streamlined deploys
– https://github.com/clutchio

17. Hybrid HTML/Native
• Core app is native
• Sections can be replaced by HTML
– i.e. Facebook stream entries fallback to HTML
• Infrequently used sections are 100% HTML

18. Recap
• Remember the basics
• Data-drive everything
• 99% HTML
• Hybrid HTML/Native

19. Scalability
• Maintaining availability, performance and
happiness
• As a function of # of people
• As a function of # of tests

20. Availability
• The build must always be green
• Set a “green SLA”
– 99% green
– Never red for > 15m
• Measure, track and report on these numbers

21. Performance
• Measure (intent to) commit to time of deploy
– Goal: < 5 minutes
• Measure local development test loop
– Goal: < 2s

22. Happiness
• CI/CD System is a product
• Software Engineers are the customer
• Keep your customer happy!

23. Testing Pyramid

24. How do you make tests fast?
• Tests can exercise large amounts of code
without being slow
• Minimize system calls (no I/O, no disk)
• Minimize test data size
• Make sure all systems are cheap to
instantiate/teardown
• No external state makes tests more reliable

25. Run Tests in Parallel
• Multiprocess
• Multimachine
• Multi-VM
• Instant multi-VM: http://circleci.com

26. Hardware Scale
• CI Cluster will get huge
– Function of cumulative engineering man-months
– Rule of thumb: 10% of your cluster size
• You will need a CI/CD DevOps person
– CI cluster monitoring / alerting
– Configuration Management critical

27. Scale testing infrastructure recap
• Write the right kind of tests
• Make those tests as fast as possible
• Run those tests in parallel

28. People / Roles
• Sheriff
– Designated reverter / problem troubleshooter
– Common pattern (IMVU, Chromium, Firefox)
• CD “Product Owner”
– Held accountable for SLA / Performance
– Manage infrastructure backlog

29. Single trunk
• Do this until it doesn’t work for you
• Gets painful in the 16 – 32 developer range
• Faster commit->deploy reduces the pain
– But effort becomes prohibitive

30. “Try” pipeline
• Conceptually, a second tree that “doesn’t
matter” but still gets tested for feedback
• Buildbot implements a patch-pushing version
• Takes a significant amount of pressure off of
trunk builds

31. CI Server takes active role
• Server automatically reverts red commits
• Server merges green commits to trunk

32. Feature branches
• All incremental development happens on
branches, branches land when feature is
“ready”
• If “feature” is kept small, can be 2-3 per
engineer per week on average
• Less continuous, but scales much better
– Feature branches tested before merge

33. Merge tree
• Tree per team / feature
• Trees merged into trunk daily (if green)
• Scale up via tree of trees (of trees…)
• Again, less continuous

34. Federation
• Each team gets their own deploy pipeline
• Requires SOA / component architecture
• Each team can set their own CD pace
• “Enterprise Ready”

35. Recap
• Single trunk + Try pipeline / Autorevert
• Feature Branches
• Merge Tree
• Federation

36. Questions?
Timothy Fitz (.com)