State of Modern Programing
summary
Argues that containers let each language do its job and shows a real pipeline that collects 16 data sources, pipes them through Python processing into a datastore and front end, and uses Amazon SQS and AWS containers. Describes CI/CD with CircleCI and SonarCloud plus Elastic Container Registry where adding services doubles boxes but keeps deployment scripts the same. Demonstrates spinning up JupyterHub instances in Azure and adding a VM with Tableau when users refuse notebooks.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 1:51One language for all platforms?
- 4:46Containers and language choice
- 9:23Reusable code with Airflow
- 11:55Deployment driving innovation
- 13:41Infrastructure insights with code
- 16:48Modern software trends
- 17:10Q&A
related talks
01h 02mDocker for Data Science: Reproducibility and Deployment
58mIf I knew then what I know now
28mEternal sunshine of the spotless development environment
46mThe Python Data Ecosystem: Navigating a fragmented landscape
39mHow Python Drives Modern Data Engineering
25mA microservices architecture with Python and Docker containers
26mDeploy Python Apps on Kubernetes and Prepare for Scale
27mWrite portable CI/CD pipelines using Python
