Jay from Learn Linux TV walks through Config-a-ma-jig, an Ansible pull-based automation platform capable of deploying 300+ configuration changes on a fresh Linux install. Pull architecture lets each machine configure itself independently, eliminating single points of failure. A fresh Debian server on Linode is fully configured in 14 minutes on first run, then 1-2 minutes on subsequent checks. The system uses three deployment groups — development, production, and stable (one version behind for mission-critical systems) — and per-machine variable files for flexibility. Key design principles include CI/CD with disposable reference servers to catch errors before production, consistent directory layouts and naming conventions, and treating automation as an ongoing practice rather than a finished project.
Table of contents
Ansible pull, CI/CD with reference servers, and the consistency practices that scale over years.3 key takeawaysMore from Learn Linux TVAbout the AuthorQuestions this post answers
What is the difference between Ansible pull and push architecture for infrastructure automation?
Ansible pull has each machine fetch and apply its own configuration independently from a central repository, rather than a control node pushing config outward. This eliminates the control node as a single point of failure — if the control node goes down, machines still self-configure. The trade-off is that each managed host needs the Ansible toolchain installed locally. Teams weighing Ansible pull vs push for their own infra find the real-world comparisons on daily.dev.
How should I structure deployment groups in Ansible to safely roll out changes to production servers?
Three groups work well: development (active testing of new changes), production (changes proven safe in dev), and stable (intentionally one version behind for mission-critical systems). Each machine gets its own variable file for per-host flexibility without duplicating playbooks. CI/CD with disposable reference servers validates changes before they reach production, catching bad variable values before they break live machines. Engineers managing multi-environment Ansible rollouts track patterns like these on daily.dev.