A Pythonic Approach to Continuous Delivery
summary
Claims that each commit goes to production and demonstrates a working pipeline that uses Ansible, Devpi, Jenkins with a one‑button deploy from Jenkins. Builds uniquely versioned Python artifacts via pscaffold per commit, runs fast CI (feedback in minutes), automated acceptance tests in production‑like environments, and emphasizes starting with a tiny fully automated skeleton. Reports that the pipeline runs, catches deploy and packaging pain points, and that simplification and continuous maintenance (refactor block time, cloud APIs) are necessary to keep it reliable.
AI-written summary · about
chapters (19)
- 0:00Start
- 3:42The "DevOps" thing...
- 4:14Continuous Delivery
- 6:12Poka-yoke (†)
- 7:09Automated Software Production Line
- 7:53It's up to you!
- 9:59A Typical Pipeline
- 11:20The Stages
- 13:26A Proper Deployment Artifact
- 15:51Continuous Integration
- 20:05Fill up the Artifact Repository
- 21:42Automated Deploy
- 25:00Use Configuration Management
- 26:06Example Ansible Playbook
- 27:55Acceptance Tests
- 28:46Last step to Production
- 32:46Traps, Tips & Tricks, Dangers...
- 35:22The not so perfect parts...
- 37:23Summary
related talks
37mAutomated deployment of Python packages for development
24mWhy, What, and How of Continuous Delivery
01h 01mA team's transition to Continuous Delivery
01h 12mPitfalls of Continuous Deployment
41mAll Things Continuous
28mContinuous Integration and Continuous Delivery Pipelines for Beginners and Managers
55mThe Rationale for Continuous Delivery
01h 21mSecure Python Packaging & Release Using Continuous Deployment