Infrastructure Python
summary
Explains practical uses of Python for infrastructure engineering, distinguishing general-purpose Python from specific tools like Ansible and Fabric. Covers which infrastructure tasks Python itself is useful for and clarifies when dedicated tools are more appropriate.
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chapters (37)
- 0:00Introduction
- 1:51Python for infrastructure
- 6:15Version control systems in Python
- 8:32Git sanity check
- 9:29Code formatting and linting
- 10:12Project templates and directory structure
- 12:15Project sync with scate
- 13:00App configuration
- 14:06Hydra for config management
- 15:55Dynaconf alternative
- 16:59NPT for config standardization
- 18:03CI/CD systems in Python
- 19:09Buildbot for builds
- 20:32Email sending and SMTP servers
- 21:41Delayed tasks and queues
- 22:47Celery and Flower for tasks
- 23:52Airflow for orchestration
- 25:20Async task managers
- 26:01Schedule for periodic tasks
- 26:44Dodo for task execution
- 28:54Tool selection for tasks
- 29:56Messenger bot creation
- 31:46Chatbots with Chats and PyTelegramBotAPI
- 32:09System and app monitoring
- 33:11Prometheus and Grafana monitoring
- 34:14Insourcing in Python apps
- 36:25Ansible for infrastructure
- 37:30Infrastructure scripts with Pytest
- 38:13Logging in Python
- 38:36Cloud infrastructure management
- 39:40Fabric for infrastructure
- 40:47Terraform vs Python for infra
- 41:07BCC for kernel monitoring
- 42:32Python learning recommendations
- 43:16Books on open source architecture
- 43:58Factorio as infrastructure example
- 44:19Python for games and entertainment
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