Cloud Computing

Efficient Cloud Storage with Automated Scaling: A Step-by-Step Guide Research Disclaimer: This guide is based on AWS SDK for Python (boto3) v1.34+, Azure Storage SDK v12.19+, and Google Cloud Storage Python Client v2.14+ official documentation. All code examples use production-tested patterns from official provider documentation. Cloud storage services automatically scale capacity, but cost optimization requires proactive lifecycle management, intelligent tiering, and monitoring. Cloud storage services like AWS S3, Azure Blob Storage, and Google Cloud Storage automatically scale to petabyte levels, but without proper management, costs can spiral out of control. This guide focuses on automated cost optimization through lifecycle policies, intelligent tiering, and monitoring—not capacity scaling (which cloud providers handle transparently). ...

Scalable Serverless AI/ML Pipelines: A Production Guide Research Disclaimer: This guide is based on AWS SDK for Python (boto3) v1.34+, SageMaker Python SDK v2.200+, and AWS Step Functions State Language (Amazon States Language) official documentation. All code examples follow AWS Well-Architected Framework for ML workloads and include production-tested patterns for serverless deployment, monitoring, and cost optimization. Serverless ML pipelines eliminate infrastructure management while providing automatic scaling, pay-per-use pricing, and high availability. This guide covers production-ready patterns for deploying ML models using AWS Lambda, SageMaker, Step Functions, and EventBridge, with complete working examples that you can deploy immediately. ...