Cloud-Native Python, DevOps & LLMOps. Containerization, Kubernetes, and Serving AI Models at Scale

Your Code Works Locally. Now, Make It Run for the World.Cloud-Native Python, DevOps & LLMOps moves beyond the IDE to the data center. It is a comprehensive guide to architecting, deploying, and scaling Python applications in the modern cloud. This book bridges the gap between Software Development and Operations, with a specialized focus on the exploding field of LLMOps (Large Language Model Operations).What You Will Build:- The Container Engine: Master Docker to create immutable, lightweight Python environments. Use Multi-Stage Builds to strip bloat and secure your supply chain.- The Orchestrator: Conquer Kubernetes. Learn the physics of Pods, Deployments, and Services. Package complex apps with Helm Charts and implement Horizontal Pod Autoscaling (HPA).- Infrastructure as Software: Stop writing YAML. Use Pulumi and Boto3 to provision AWS VPCs, EKS clusters, and S3 buckets using pure Python code.- Serverless Architecture: Build event-driven microservices using AWS Lambda, SQS, and SNS. Decouple your systems to handle infinite scale.- LLMOps & AI Serving: Deploy the heavy artillery. Configure the NVIDIA Container Toolkit for GPU passthrough. Serve 70B+ parameter models using vLLM with PagedAttention and TorchServe for enterprise-grade inference.- Self-Healing Infrastructure: Implement AIOps pipelines that use Machine Learning to analyze logs, detect anomalies via AWS X-Ray, and automatically repair the system.Who This Book Is For:Written for Python developers, ML Engineers, and aspiring Cloud Architects who want to stop "e;just writing code"e; and start building resilient, global platforms. If you want to know how to take a raw Python script and turn it into a scalable, GPU-accelerated cloud service, this is your blueprint.Don't just write software. Architect it.