『S3E5: Python for MLOps, DataOps, and Infrastructure as Code』のカバーアート

S3E5: Python for MLOps, DataOps, and Infrastructure as Code

S3E5: Python for MLOps, DataOps, and Infrastructure as Code

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 Angela Andrews and Michael Jenkins continue their journey through *Hands-On Python for DevOps* with a deep dive into Chapters 11 and 12 — exploring how Python bridges the gap between data science, operations, and infrastructure management.

This episode connects the dots between MLOps, DataOps, and Infrastructure as Code (IaC) — showing how Python’s simplicity and versatility make it an essential tool for automating data workflows, deploying machine learning models, and defining infrastructure reproducibly.

Expect lively discussion, insightful quotes, and practical takeaways from real-world DevOps experience.

Book Chapters Covered

- Chapter 11: MLOps and DataOps
- Chapter 12: Python and Infrastructure as Code (IaC)

Video & Podcast Chapters

00:00 Welcome and Episode Setup
03:00 The Future Is Now – AI and Career Differentiation
06:30 Why Python Dominates DataOps and MLOps
10:45 Working with Data and the Power of Pandas
14:15 The Three V’s of Data Complexity: Velocity, Volume & Variety
19:30 Streaming Data and Real-Time Processing with Flink and Pandas
25:00 AI Evolution and How Tech Books Keep Up
32:30 Understanding Infrastructure as Code (IaC)
36:00 Salt vs Ansible vs Terraform SDK – Python in IaC Tools
43:30 Community Shout-Outs and Next Episode Preview

Key Takeaways

- Python is the universal connector between DevOps, DataOps, and MLOps — powering automation, analytics, and infrastructure.
- The Three V’s (Velocity, Volume, Variety) define modern data challenges; Python libraries like Pandas and Flink help manage them efficiently.
- Infrastructure as Code (IaC) transforms how teams manage cloud resources — codifying provisioning, replication, and scaling for AWS, Azure, and GCP.
- Tools like Terraform + Ansible deliver the perfect one-two punch for deployment and configuration.
- Even as AI-assisted coding evolves, foundational knowledge still matters. Understanding the “nuts and bolts” ensures better troubleshooting and design.
- The hosts reflect on enduring classics like "UNIX in a Nutshell" and discuss how agile digital publishing keeps technical learning relevant.

🔗 Resource Links

📘 The Book — "Hands-On Python for DevOps"

💻 The Code Repository: PacktPublishing/Hands-On-Python-for-DevOps

Conferences:


  • BITCon
  • Afrotech
  • RenderATL

🙌 Join the Conversation

Don’t forget to like, subscribe, and comment to share your own experiences with Python, MLOps, and IaC.

Follow the hashtag #CoverToCode on LinkedIn and YouTube to catch upcoming discussions — next up: “The Tools to Take Your DevOps to the Next Level.”

Find us online at covertocode.com.

Hosted by:
  • Angela A. @scooterphoenix
  • Michael J. @managedkaos ​
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