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Python in Production: A Comprehensive Guide to Deploying and Managing Python Web Applications: VPS, Containers, Kubernetes, PaaS, Docker, CI/CD, Cloud Platforms, Serverless & More - Softcover

 
9798289366733: Python in Production: A Comprehensive Guide to Deploying and Managing Python Web Applications: VPS, Containers, Kubernetes, PaaS, Docker, CI/CD, Cloud Platforms, Serverless & More

Synopsis

What You Will Learn in This Book

  • Master the deployment lifecycle: Understand the entire journey of a web application from local development to being live in production environments.
  • Prepare applications for production: Get your Python application ready for prime time with best practices for code structure, configuration, dependency management, logging, and serving static files.
  • Utilize essential tools: Leverage fundamental development tools like Git for version control and various task runners to streamline your daily workflow.
  • Choose and configure WSGI/ASGI servers: Make informed decisions and properly set up Gunicorn, uWSGI, Uvicorn, and Daphne for optimal application performance and stability.
  • Grasp Docker fundamentals: Understand the core concepts of containerization and Docker and effectively Dockerize your Python web applications.
  • Orchestrate with Docker Compose: Seamlessly manage multi-container development environments for your applications, including databases and caches.
  • Deploy to Virtual Private Servers (VPS): Learn the ins and outs of traditional server deployment, including server setup, hardening, reverse proxy configuration with Nginx, and process management.
  • Deploy to Platform as a Service (PaaS): Discover how to efficiently deploy Python applications to services like Heroku, AWS Elastic Beanstalk, and Google App Engine.
  • Transition Docker to production: Successfully move your Dockerized applications from development to live production environments, including using container registries.
  • Introduce Kubernetes for Python apps: Get a solid foundation in Kubernetes core concepts and learn how to deploy, manage, and scale your Python applications within a cluster.
  • Explore serverless deployment (FaaS): Understand and implement event-driven architectures using serverless functions with AWS Lambda, Google Cloud Functions, and Azure Functions.
  • Implement CI/CD pipelines: Automate your development and deployment processes with Continuous Integration and Continuous Deployment, using tools like GitHub Actions and GitLab CI/CD.
  • Establish monitoring and alerting: Set up robust systems to track application and system health, identify issues proactively, and ensure continuous operation.
  • Strategically scale your application: Learn techniques for vertical and horizontal scaling, including load balancing, autoscaling, and database optimization.
  • Apply security best practices: Implement crucial security measures throughout your deployment, from HTTPS and server hardening to dependency auditing and disaster recovery planning.
  • Manage production databases effectively: Learn how to handle database migrations, backups, restores, and performance tuning in a production setting.
  • Automate infrastructure with IaC: Utilize Infrastructure as Code (IaC) tools like Terraform to provision and manage your deployment resources reproducibly.
  • Dive into advanced Kubernetes: Explore more complex Kubernetes concepts such as Helm charts, StatefulSets, and service meshes for sophisticated deployments.
  • Understand microservices deployment: Gain insights into the unique considerations and patterns for deploying Python-based microservices.
  • Stay current with future trends: Keep up-to-date with emerging technologies and best practices in Python web deployment.
  • Troubleshoot common issues: Effectively diagnose and resolve common deployment problems, leveraging provided resources for ongoing learning.

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ISBN 13: 9798289366733
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Pythquill Publishing
Published by Independently Published, 2025
ISBN 13: 9798289366733
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Paperback. Condition: new. Paperback. What You Will Learn in This BookMaster the deployment lifecycle: Understand the entire journey of a web application from local development to being live in production environments.Prepare applications for production: Get your Python application ready for prime time with best practices for code structure, configuration, dependency management, logging, and serving static files.Utilize essential tools: Leverage fundamental development tools like Git for version control and various task runners to streamline your daily workflow.Choose and configure WSGI/ASGI servers: Make informed decisions and properly set up Gunicorn, uWSGI, Uvicorn, and Daphne for optimal application performance and stability.Grasp Docker fundamentals: Understand the core concepts of containerization and Docker and effectively Dockerize your Python web applications.Orchestrate with Docker Compose: Seamlessly manage multi-container development environments for your applications, including databases and caches.Deploy to Virtual Private Servers (VPS): Learn the ins and outs of traditional server deployment, including server setup, hardening, reverse proxy configuration with Nginx, and process management.Deploy to Platform as a Service (PaaS): Discover how to efficiently deploy Python applications to services like Heroku, AWS Elastic Beanstalk, and Google App Engine.Transition Docker to production: Successfully move your Dockerized applications from development to live production environments, including using container registries.Introduce Kubernetes for Python apps: Get a solid foundation in Kubernetes core concepts and learn how to deploy, manage, and scale your Python applications within a cluster.Explore serverless deployment (FaaS): Understand and implement event-driven architectures using serverless functions with AWS Lambda, Google Cloud Functions, and Azure Functions.Implement CI/CD pipelines: Automate your development and deployment processes with Continuous Integration and Continuous Deployment, using tools like GitHub Actions and GitLab CI/CD.Establish monitoring and alerting: Set up robust systems to track application and system health, identify issues proactively, and ensure continuous operation.Strategically scale your application: Learn techniques for vertical and horizontal scaling, including load balancing, autoscaling, and database optimization.Apply security best practices: Implement crucial security measures throughout your deployment, from HTTPS and server hardening to dependency auditing and disaster recovery planning.Manage production databases effectively: Learn how to handle database migrations, backups, restores, and performance tuning in a production setting.Automate infrastructure with IaC: Utilize Infrastructure as Code (IaC) tools like Terraform to provision and manage your deployment resources reproducibly.Dive into advanced Kubernetes: Explore more complex Kubernetes concepts such as Helm charts, StatefulSets, and service meshes for sophisticated deployments.Understand microservices deployment: Gain insights into the unique considerations and patterns for deploying Python-based microservices.Stay current with future trends: Keep up-to-date with emerging technologies and best practices in Python web deployment.Troubleshoot common issues: Effectively diagnose and resolve common deployment problems, leveraging provided resources for ongo Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798289366733

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