Continuous Integration and Deployment

Automation

• "Everything that can be automated should be automated"

  • Compare and contrast with "We value people over tools"

  • Automation always comes with costs

• "Continuous" (on every relevant change)…

  • Integration — build and test

  • Delivery — system test in "native" environment

  • Deployment — make new release available

Systems Are Not Just Code

• Assets

• Databases

• Build infrastructure

• Configuration

• Tests

Case Study: Enabling Rust Compiler Feature

• Finish up with old Issue

• Literally change a symbol from Warn to Forbid in the compiler source — about a week

• Make the change, watch the compiler fail to compile during CI

• Fix the problems introduced by the change iteratively

  • Relying on CI too slow, so got local build / test infrastructure working

• Pull request edited many times

• "Crater" run to check for problems across many, many open source Rust projects: found two significant ones that were quickly fixed

• Finally, pull request accepted: success

• Feature becomes part of "nightly" (dev) release, later stable release

• Happens literally dozens of times a week on this project

CI/CD Using Cloud Containers

• Typically Github Actions + Docker on Github (Travis CI etc available)

• Before each release, system is automatically built and "realistically" tested

• For services, running service is auto-updated once testing is complete

• Software can be auto-deployed across many systems using tools like Puppet or Chef

First Steps: Github Actions

Recommend the first two Github "Learning Labs": "Github Actions: Hello World" and "Github Actions: Continuous Integration". Both are quite good.