Deploying Secure Data Science Applications in the Cloud: From VMS to Serverless with AWS and Google Cloud
暫譯: 在雲端部署安全的數據科學應用：從 VMS 到無伺服器架構，使用 AWS 和 Google Cloud

Braga, Lucas H. Benevides E.

Deploying Secure Data Science Applications in the Cloud: From VMS to Serverless with AWS and Google Cloud
  • 出版商: Apress
  • 出版日期: 2025-10-22
  • 售價: $1,710
  • 貴賓價: 9.5 折 $1,625
  • 語言: 英文
  • 頁數: 324
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868817144
  • ISBN-13: 9798868817144
  • 相關分類: Power BI、Amazon Web Services

    • 海外代購書籍(需單獨結帳)

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商品描述

This step-by-step guide is for Data Scientists, ML engineers, and DevOps practitioners who need to turn prototypes into secure, scalable production services on AWS and Google Cloud. With step-by-step instructions and practical examples, this book bridges the gap between building Data Science applications and Machine Learning models, and deploying them effectively in real-world scenarios

The book begins with an introduction to essential cloud concepts, providing detailed guidance on setting up a virtual machine (VM) on AWS--and later on Google Cloud--to serve applications. This includes configuring security groups and establishing secure SSH (Secure Shell) connections using VSCode (Visual Studio Code). You will learn how to deploy a dummy HTTP Streamlit application as a foundational exercise before advancing to more complex setups.

Subsequent chapters dive deeper into key deployment practices, such as configuring load balancers, setting up domain and subdomain names, and securing applications with SSL (Secure Sockets Layer) certificates. The book introduces more advanced deployment strategies using Docker containers and Nginx as a reverse proxy, as well as secure serverless deployments of Jenkins, Flask, and Streamlit. You'll also learn how to train machine learning models and use Flask to build APIs that serve those models in production. In addition, the book offers hands-on demonstrations for using Jenkins as an ETL platform, Streamlit as a dashboard service, and Flask for API development. For those interested in serverless architectures, it provides detailed guidance on using AWS ECS (Elastic Container Service) Fargate and Google Cloud Run to build scalable and cost-effective solutions.

By the end of this book, you will possess the skills to deploy and manage data science applications on the cloud with confidence. Whether you are scaling a personal project or deploying enterprise-level solutions, this book is your go-to resource for secure and seamless cloud deployments.

What You Will Learn

    Deploy end-to-end data science applications with a strong foundation in cloud infrastructure setup, including VM provisioning, SSH access, security groups, SSL configuration, load balancers, and domain management for secure, real-world deployments Use industry-known tools such as Docker, Nginx, Flask, Streamlit, and Jenkins to build secure, scalable services Understand how to structure and expose machine learning models via APIs for production use Explore modern serverless architectures with AWS Fargate and Google Cloud Run to scale efficiently with minimal overhead Develop a cloud deployment mindset grounded in doing things from scratch--before adopting abstracted solutions

Who This Book Is For

Beginning to intermediate professionals with a basic understanding of Python, including Data Scientists, ML Engineers, Data Engineers, and Data Analysts who aim to securely deploy their projects in production environments, and individuals working on both personal projects and enterprise-level solutions, leveraging AWS and Google Cloud setups

商品描述(中文翻譯)

這本逐步指南是為數據科學家、機器學習工程師和DevOps從業者而設，幫助他們將原型轉換為在AWS和Google Cloud上安全、可擴展的生產服務。透過逐步的指導和實用的範例，本書彌補了構建數據科學應用程序和機器學習模型與在現實場景中有效部署之間的差距。

本書首先介紹了基本的雲端概念，提供了在AWS上設置虛擬機（VM）的詳細指導，隨後在Google Cloud上也會進行相應的設置，以便提供應用程序服務。這包括配置安全組和使用VSCode（Visual Studio Code）建立安全的SSH（安全外殼）連接。您將學習如何部署一個虛擬的HTTP Streamlit應用程序，作為基礎練習，然後再進入更複雜的設置。

隨後的章節深入探討關鍵的部署實踐，例如配置負載均衡器、設置域名和子域名，以及使用SSL（安全套接層）證書來保護應用程序。本書介紹了使用Docker容器和Nginx作為反向代理的更高級部署策略，以及Jenkins、Flask和Streamlit的安全無伺服器部署。您還將學習如何訓練機器學習模型，並使用Flask構建API，以便在生產環境中提供這些模型。此外，本書提供了使用Jenkins作為ETL平台、Streamlit作為儀表板服務以及Flask進行API開發的實作示範。對於有興趣於無伺服器架構的人，本書提供了使用AWS ECS（彈性容器服務）Fargate和Google Cloud Run來構建可擴展且具成本效益解決方案的詳細指導。

在本書結束時，您將具備在雲端自信地部署和管理數據科學應用程序的技能。無論您是在擴展個人項目還是部署企業級解決方案，本書都是您進行安全且無縫雲端部署的首選資源。

您將學到的內容：

- 部署端到端的數據科學應用程序，並在雲端基礎設施設置方面打下堅實基礎，包括VM配置、SSH訪問、安全組、SSL配置、負載均衡器和域名管理，以實現安全的現實部署
- 使用行業知名工具如Docker、Nginx、Flask、Streamlit和Jenkins來構建安全、可擴展的服務
- 理解如何結構和暴露機器學習模型，通過API進行生產使用
- 探索現代無伺服器架構，使用AWS Fargate和Google Cloud Run以最小的開銷高效擴展
- 培養從零開始進行雲端部署的思維方式——在採用抽象解決方案之前

本書適合對象：

對Python有基本了解的初學者到中級專業人士，包括數據科學家、機器學習工程師、數據工程師和數據分析師，旨在安全地在生產環境中部署他們的項目，以及從事個人項目和企業級解決方案的人，利用AWS和Google Cloud的設置。

作者簡介

Lucas Braga is a Lead Data Scientist and AI Cloud Engineer with more than 10 years of experience. He served as Senior Data Scientist, Staff Data Scientist, and Manager at leading organizations such as DHL, Delivery Hero, and Wolt (a subsidiary of DoorDash).

He holds a master's degree in Applied Statistics and Data Science from Kansas University, along with a Google Cloud certification and extensive experience with AWS. His expertise spans Data Science, Software Engineering, DevOps, Data Engineering, and Business Analytics, enabling him to deploy machine learning models securely and efficiently in production environments. Recognizing a critical industry gap in deploying applications that meet corporate security standards, Lucas combined his deep technical knowledge and teaching skills to create this book. It provides practical, security-focused guidance for Data Scientists and Software Engineers looking to enhance their deployment skills.

作者簡介(中文翻譯)

盧卡斯 布拉加 是一位資深數據科學家和人工智慧雲端工程師，擁有超過10年的經驗。他曾在DHL、Delivery Hero和Wolt（DoorDash的子公司）等領先組織擔任高級數據科學家、資深數據科學家和經理職位。

他擁有堪薩斯大學的應用統計與數據科學碩士學位，以及Google Cloud認證，並在AWS方面擁有豐富的經驗。他的專業領域涵蓋數據科學、軟體工程、DevOps、數據工程和商業分析，使他能夠在生產環境中安全且高效地部署機器學習模型。盧卡斯認識到在部署符合企業安全標準的應用程式方面存在一個關鍵的行業缺口，因此他結合了深厚的技術知識和教學技能，創作了這本書。這本書為希望提升部署技能的數據科學家和軟體工程師提供了實用且以安全為重點的指導。

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