12 Factor Applications with Docker and Go (Engineer)
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12 Factor Applications with Docker and Go

A book filled with examples on how to use Docker and Go to create the ultimate 12 Factor applications

About the Book

Using Docker to solve scaling issues, ideally before they occur. Scale your Go service from the start!

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    • Computers and Programming
    • Web Development
    • Docker
    • DevOps
    • Software Engineering
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About the Author

Tit Petric
Tit Petric

I'm a seasoned veteran of software engineering. Interested in performance optimization and problem solving. High traffic, high availability, virtualization, docker - these are the categories in which I live.

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Table of Contents

  • Introduction
    • About me
    • Who is this book for?
    • How should I study it?
  • Requirements
    • Linux and Docker
    • Additional requirements
  • I. Codebase - One codebase tracked in revision control, many deploys
    • Gogs
    • Multiple deploys
    • Structuring your code
    • Improving deployments
  • II. Dependencies - Explicitly declare and isolate dependencies
    • Vendoring
    • Caveats about vendoring
    • System dependencies
  • III. Config - Store config in the environment
    • Flags
    • godotenv
    • Viper
  • IV. Backing services - Treat backing services as attached resources
    • Data resources
    • Example backing services
  • V. Build, release, run - Strictly separate build and run stages
    • Building Go applications
    • Building Docker images
    • Continuous integration with Codeship
  • VI. Processes - Execute the app as one or more stateless processes
    • Data caching
    • Share-nothing
    • Backing service: Running a highly available Redis instance
    • Realistic example of a stateless application
  • VII. Port binding - Export services via port binding
    • The none network
    • The bridge network
    • Custom bridge network
    • Multi-host network
    • Host networking
    • Exposing your service ports
    • Debugging docker network connectivity
    • Using your own DNS
    • Sending e-mails from docker
  • VIII. Concurrency - Scale out via the process model
    • Basic process management
    • Advanced process management
    • Docker swarm
    • Scaling our service with Docker Swarm
    • Rolling updates for our service
    • Scaling to a 1000 containers!
  • IX. Disposability - Maximize robustness with fast startup and graceful shutdown
    • Disposing of containers
    • Docker Chaos Monkey
    • Health checks
  • X. Dev/prod parity - Keep development, staging, and production as similar as possible
    • It worked on my machine
    • Upgrades and testing
    • Many moving parts
  • XI. Logs - Treat logs as event streams
    • A note on backing services
    • Logging Docker to Papertrail
    • Logging as a backing service
  • XII. Admin processes - Run admin/management tasks as one-off processes
    • Running backups
    • Console access to your containers
    • Orchestrating your management tasks

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