The 12 Factor App¶

Platform as a Service (PaaS) has revolutionized cloud application development by abstracting the complexities of infrastructure management, thereby democratizing access to cloud technologies for developers across the globe. By providing a seamless environment for the deployment, management, and scaling of applications, PaaS platforms like Heroku, Google App Engine, and others have not only accelerated innovation but also significantly lowered the entry barrier for web application development.

This evolution has been further guided by the principles of The 12 Factor App, a methodology that outlines best practices for building scalable, maintainable, and portable applications in a cloud-native world. Together, PaaS and The 12 Factor App principles represent a pivotal shift towards more agile, efficient, and accessible cloud application development, embodying the transformation in how modern software is built and deployed.

Let’s review these two concepts in more details.

The Invention of PaaS¶

The concept of Platform as a Service (PaaS) emerged as a natural evolution in cloud computing, bridging the gap between Software as a Service (SaaS) offerings and Infrastructure as a Service (IaaS) platforms. PaaS provides developers with a framework and environment to build, deploy, and manage applications without the complexity of managing the underlying infrastructure.

The Inception of PaaS: Fotango’s Zimki (2005)¶

The inception of PaaS can be traced back to 2005 with the development of Zimki by Fotango, a London-based company. Zimki was a pioneering effort in the PaaS domain, offering a fully managed platform that allowed developers to write and deploy JavaScript code for web applications without worrying about the underlying servers, storage, or network configuration. Zimki was innovative in providing a server-side JavaScript execution environment, database storage, and application services, all accessible through a simple web interface or API. Despite its early promise and the groundbreaking concept, Zimki did not achieve commercial success and was eventually shut down in 2007. Nonetheless, Fotango’s Zimki laid the groundwork for what would become a rapidly expanding market for cloud application development platforms.

Google App Engine: Igniting the PaaS Space (2008)¶

While Zimki introduced the world to the potential of PaaS, it was Google App Engine, launched in 2008, that truly ignited the PaaS space. Google App Engine provided developers with a powerful, scalable platform for building and hosting web applications on the same systems that power Google applications. This offering democratized access to Google’s infrastructure, allowing developers to focus on code while Google managed the deployment, scaling, and infrastructure management tasks. Google App Engine’s launch marked a significant milestone in cloud computing, showcasing the viability and potential of PaaS to a global audience of developers and enterprises.

Heroku (2007)¶

Launched in 2007, Heroku has been pivotal in the evolution of Platform as a Service (PaaS), particularly in making cloud application development accessible to a global community of developers. Before platforms like Heroku, deploying and scaling web applications required significant operational expertise and resources. Heroku’s abstraction of these complexities and its pay-as-you-go pricing model have enabled startups, independent developers, and small teams to engage in cloud computing, thus accelerating innovation and reducing the barriers to web application development. As one of the first cloud platforms to simplify application deployment and management, Heroku has played a pivotal role in shaping early PaaS offerings by improving the developer experience for those without extensive infrastructure expertise.

Heroku’s Impact on PaaS¶

Simplifying Deployment: Heroku revolutionized the way developers deploy applications. With its simple “git push” deployment model, Heroku made it possible for developers to deploy applications directly from their Git repositories with a single command. This ease of use significantly lowered the barrier to cloud application deployment and management.

Support for Multiple Programming Languages: Heroku began with support for Ruby but quickly expanded to support a wide range of programming languages, including Python, Java, PHP, Node.js, Scala, and Go. This inclusivity fostered a diverse developer ecosystem and made Heroku a versatile platform for a wide variety of web applications.

Add-on Ecosystem: Heroku introduced an add-on marketplace, offering third-party cloud services that could be easily integrated into applications. This ecosystem included databases, monitoring tools, email services, and more, allowing developers to extend their applications with powerful capabilities without manual setup or configuration.

Focus on Developer Experience: Heroku’s design philosophy centered around making developers’ lives easier. By abstracting away the complexities of hardware and servers, Heroku allowed developers to focus on writing code and building features. The platform managed scaling, load balancing, and server maintenance, enabling developers to deliver applications more quickly and efficiently.

The Need for PaaS: Beyond IaaS and SaaS¶

The emergence and growth of PaaS have been fueled by several trends that extend beyond the foundational services provided by IaaS and the application-focused offerings of SaaS. These trends include:

Mobile Development: The explosive growth of mobile applications increased the demand for platforms that could simplify backend development and scaling challenges, making PaaS an attractive option for mobile app developers.
Agile Methodologies: The adoption of Agile development practices emphasized rapid iteration, continuous feedback, and flexibility. PaaS environments cater to these needs by enabling quick deployments and simplifying application lifecycle management.
DevOps Culture: The rise of DevOps, which emphasizes collaboration between development and operations teams, benefited from PaaS offerings. PaaS supports DevOps practices by automating infrastructure management tasks, thereby accelerating development cycles and improving deployment reliability.
Continuous Integration/Continuous Deployment (CI/CD): CI/CD practices require automated tools and processes to manage the frequent integration and deployment of code changes. PaaS platforms integrate with CI/CD tools and workflows, facilitating automated testing, builds, and deployments.

Introduction to The 12 Factor App Principles¶

Since the mid-2000s, cloud computing has significantly changed how applications are designed, deployed, and scaled. A methodology known as “The 12 Factor App” has become instrumental in guiding developers and organizations to build more robust, scalable, and maintainable applications. This approach outlines twelve principles for creating software-as-a-service (SaaS) applications optimized for cloud environments, emphasizing automation, minimal divergence between development and production, and continuous deployment.

The 12 Factor App methodology addresses both technical and operational challenges in application development, combating software erosion and enabling scalable, manageable services. It marks a departure from traditional, monolithic architectures towards distributed, cloud-native solutions, drawing from real-world practices for modern application development and promoting a culture of innovation.

Understanding and applying The 12 Factor App principles is crucial for developers, operations teams, and business leaders as cloud computing keeps on expanding. This document will explore the methodology’s history, its core principles, and provide real-world examples for modernizing applications.

History and Evolution¶

The 12 Factor App methodology emerged from the early challenges of cloud computing and SaaS application growth. Adam Wiggins, Heroku’s co-founder, synthesized these principles based on successful patterns observed in SaaS applications. Officially introduced in 2011, the methodology offered solutions to common cloud development issues, such as software erosion, environment portability, and dependency management.

The methodology’s evolution reflects broader trends in cloud computing and SaaS, advocating for microservices, stateless applications, and continuous deployment. It has influenced the development of technologies like Docker and Kubernetes, aligning with their design and operations.

The 12 Factor App serves as both a practical guide and a forward-looking framework. It arose from the need to address immediate cloud computing challenges while remaining adaptable to future developments. As cloud technologies evolve, The 12 Factor App’s principles continue to offer a foundational approach for building scalable, resilient, and maintainable applications.

Core Principles¶

The 12 Factor App methodology presents a comprehensive set of principles designed for the development and deployment of scalable, maintainable, and portable cloud-native applications. These principles address various aspects of software development, from codebase management to service disposal, offering a blueprint for building applications that thrive in the dynamic and distributed environment of the cloud. Here’s an introductory overview of each of the twelve factors:

Codebase: One codebase tracked in version control, with many deployments. This principle emphasizes the importance of a single codebase for an application, which can be deployed in multiple stages (development, staging, production), ensuring consistency across environments.
Dependencies: Explicitly declare and isolate dependencies. Applications should explicitly declare their dependencies, not relying on implicit existence of system-wide packages, to avoid conflicts and ensure replicability of the environment.
Config: Store config in the environment. Configuration that varies between deployments (such as database URLs) should be stored in the environment rather than in the code, to keep the application’s configuration separate from its codebase.
Backing Services: Treat backing services as attached resources. This factor advocates for treating services used by the application (like databases, messaging systems) as attached resources, which can be replaced or attached/detached without code changes.
Build, release, run: Strictly separate build and run stages. By separating the build stage (where the code is compiled), the release stage (where build is combined with config), and the run stage (where the application is executed), applications can achieve greater consistency across environments.
Processes: Execute the app as one or more stateless processes. Applications should strive for statelessness and share-nothing architecture, ensuring scalability and resilience.
Port binding: Export services via port binding. Applications should be self-contained and should not rely on runtime injection of a web server into the execution environment to create a web-facing service.
Concurrency: Scale out via the process model. The application should be able to scale out horizontally, handling different types of work with different types of processes.
Disposability: Maximize robustness with fast startup and graceful shutdown. Applications should be designed for quick startup and graceful shutdown to maximize robustness with fast elasticity and robustness against sudden deaths.
Dev/prod parity: Keep development, staging, and production as similar as possible. By minimizing the gaps between development and production environments, teams can avoid issues related to environment discrepancies.
Logs: Treat logs as event streams. Applications should not concern themselves with routing or storage of their output stream. Instead, treat logs as event streams that can be captured and processed by external systems.
Admin processes: Run admin/management tasks as one-off processes. Maintenance and admin tasks should be run in an environment as similar as possible to the regular long-running application processes.

These twelve principles, when collectively applied, enable developers to build applications that are more scalable, portable, and resilient. They encourage practices that align closely with the realities of cloud computing, ensuring that applications can leverage the full potential of modern infrastructure platforms. In the following section, we will delve deeper into each of these principles, exploring their implications with real-world examples and discussing their relevance in today’s cloud-centric world.

Platform that implement the 12 Factor App methodology¶

Cloud Providers (PaaS)¶

The 12 Factor App methodology has significantly influenced the design and operational philosophies of a multitude of Platform as a Service (PaaS) providers. These platforms naturally encourage, and often mandate, practices that align with the 12 factors, simplifying the process for developers to build and deploy applications that adhere to these principles. Below is a curated list of prominent PaaS platforms, ordered by their impact and alignment with the 12-factor methodology:

Heroku¶

Overview: Directly co-founded by one of the authors of The 12 Factor App, Adam Wiggins, Heroku stands as the most closely aligned platform with the 12-factor principles. It simplifies application deployment in a highly abstracted environment, emphasizing disposability, portability, and minimal configuration.

Google App Engine¶

Overview: A fully managed, serverless platform that enables developers to build scalable applications. Google App Engine champions the 12-factor app principles by abstracting much of the infrastructure, promoting build, release, run processes, and integrating seamlessly with Google Cloud’s services for enhanced logging, monitoring, and configuration management.

AWS Elastic Beanstalk¶

Overview: This Amazon offering automates application deployment within the AWS Cloud, removing the need for direct infrastructure management. It abstracts much of the infrastructure complexities, supporting several 12-factor principles such as codebase, dependencies, configuration, logs, and administrative processes.

Microsoft Azure App Service¶

Overview: A fully managed platform designed for building, deploying, and scaling web applications. Azure App Service facilitates continuous deployment from various sources, manages infrastructure automatically, and aligns with 12-factor principles including codebase, dependencies, build/release/run, and logs.

IBM Cloud Foundry¶

Overview: This cloud platform abstracts underlying infrastructure complexities, allowing for serverless deployment and scaling of applications. It adheres to 12-factor principles by supporting continuous delivery, scalable application frameworks, logging, and environment-specific configuration.

Platform.sh¶

Overview: Known for its focus on continuous deployment and scalable infrastructure, Platform.sh enforces many 12-factor principles like codebase, dependencies, and configuration, through its git-driven workflow and container-based infrastructure.

DigitalOcean App Platform¶

Overview: Simplifies building, deploying, and scaling applications in the cloud. It supports the 12-factor methodology by abstracting infrastructure management, providing continuous deployment from Git, managing infrastructure automatically, and offering built-in monitoring and logging services.

Clever Cloud¶

Overview: An IT Automation platform focusing on the deployment, scaling, and management of applications. It supports key 12 Factor App principles by providing automated scaling, managed runtime environments, and abstracting much of the underlying infrastructure to focus on application development.

Railway¶

Overview: Designed to streamline the development, deployment, and scaling of applications, Railway offers a developer-friendly interface and supports CI/CD, aligning with the codebase, build, release, run, and dev/prod parity principles of the 12-factor methodology.

Fly.io¶

Overview: This platform offers globally distributed application running capabilities, emphasizing speed and scalability. Fly.io supports 12-factor principles like port binding, concurrency, and disposability, allowing applications to deploy across multiple regions with ease.

Convox¶

Overview: Simplifies cloud deployment by abstracting complex cloud services. Built on top of container technologies, it adheres to 12-factor principles such as codebase, dependencies, and build/release/run cycles, streamlining the process for development and operations.

Deta¶

Overview: Aimed at developers, Deta offers a simple interface for deploying apps and databases with zero-config deployments, aligning with principles like codebase, dependencies, and configuration, facilitating quick iterations and maintenance.

Appliku¶

Overview: This platform automates web application deployments from Git repositories, supporting several 12-factor app principles, including codebase, dependencies, and configuration, by streamlining the deployment process for ease of scalability and configurability.

Porter¶

Overview: An emerging PaaS that simplifies deploying, managing, and scaling applications in Kubernetes. Designed to lower the barrier for Kubernetes, Porter focuses on developer experience and operational simplicity, aligning with the modern needs of cloud-native application development.

These platforms underscore the vast adoption and adaptation of the 12-factor app principles, offering developers varying degrees of support and infrastructure abstraction to build scalable, resilient, and maintainable applications. By leveraging these PaaS solutions, developers can focus more on their applications, benefiting from the practices that lead to more robust software development and deployment in the cloud era.

Open Source Platforms for Self-Hosted PaaS¶

Here is a list of open-source projects that offer PaaS-like capabilities for self-hosting environments, aligning with the 12 Factor App methodology. These projects enable developers, small teams and enterprises to deploy and manage applications with ease, offering a similar experience to commercial PaaS offerings but with the added control and flexibility that comes from self-hosting.

Dokku¶

Overview: Dokku is a Docker-powered, mini-Heroku in just over 100 lines of Bash (originally). It offers a simple, single-server PaaS experience, making it ideal for small deployments or personal projects.
12 Factor Alignment: Emphasizes the 12-factor methodology by abstracting application deployment using Docker containers. Supports configuration through environment variables and process types in a Procfile, akin to Heroku.
Technology: Developed in Bash and utilizes Docker for application isolation.

Piku¶

Overview: An open-source, Heroku-like PaaS that facilitates easy self-hosting of web apps on your own server. It supports multiple programming languages and frameworks via git push deployments.
12 Factor Alignment: Encourages 12-factor app principles by allowing deployments through git, managing dependencies through declared requirements, and configuring applications via environment variables.
Technology: Developed in Python, with uWSGI for application isolation.

Nua¶

Overview: An open-source, self-hosted cloud platform aiming to cover the entire lifecycle of web applications. Nua focuses on security and supports digital autonomy strategies, particularly for SMEs, associations, and public services.
12 Factor Alignment: Aligns with the 12-factor app through declarative configuration, reliance on established technologies (Python, OCI standards, Docker), and adherence to best practices for web frameworks deployment. It emphasizes securing the software supply chain with practices like SBOM.
Technology: Developed in Python, leveraging Docker for application isolation.

Hop3¶

Overview: Aims at enhancing cloud computing with a focus on sovereignty, security, sustainability, and inclusivity. Unlike Nua, Hop3 does not utilize Docker or containers, emphasizing lean isolation technologies.
12 Factor Alignment: Supports wide language and framework compatibility, simple git push deployments, automatic HTTPS, and efficient application isolation, facilitating decentralized architecture and multi-app deployment from a single repository.
Technology: Developed in Python, using uWSGI for application isolation without Docker or traditional container technologies.

Sailor¶

Overview: A fork of Piku, Sailor shares a similar scope and approach to providing PaaS capabilities.
12 Factor Alignment: Mirrors Piku’s adherence to the 12-factor methodology.
Technology: Developed in Python, with uWSGI for application isolation.

CapRover¶

Overview: An easy-to-use app/database deployment and web server manager, supporting a wide range of applications and technologies.
12 Factor Alignment: Facilitates 12-factor app compliance with a Docker-based platform, simplifying configurations and deployments through a user-friendly interface and CLI.
Technology: Developed in JavaScript, utilizing Docker for application isolation.

YunoHost¶

Overview: Designed to simplify server administration, YunoHost is well-suited for personal and small organization use, facilitating web app deployment and system services management.
12 Factor Alignment: Simplifies application deployment and service management, aligning with 12-factor principles around configuration, logging, and process management.
Technology: Developed in Python, focusing on ease of use without specific reliance on container technologies for application isolation.

Cloudron¶

Overview: Provides a complete solution for running apps securely and keeping them up-to-date. Features a marketplace of packaged apps for one-click deployment.
12 Factor Alignment: Offers isolated environments for apps, manages dependencies within app packages, and simplifies configuration through its dashboard, supporting automatic SSL, backups, and updates.
Technology: Developed in JavaScript, using Docker for application isolation.

OpenShift¶

Overview: Red Hat’s enterprise-grade Kubernetes platform that simplifies the development, deployment, and scaling of applications, offering additional features and tools for an integrated application platform.
12 Factor Alignment: Automates deployment processes, manages dependencies through container images, and ensures configurations are stored in the environment, fully embracing the 12-factor app methodology.
Technology: Extends Kubernetes with additional features for enterprise use, utilizing container technology for application isolation.

Cloud Foundry¶

Overview: A multi-cloud application platform as a service (PaaS), governed by the Cloud Foundry Foundation, providing a model for cloud-native application delivery on Kubernetes.
12 Factor Alignment: Automates the build, deploy, and manage lifecycle, supporting the codebase factor with Git integration, managing dependencies via buildpacks, and ensuring configuration is stored in the environment.
Technology: Leverages Kubernetes for orchestration, with a focus on developer efficiency and application portability.

Sandstorm¶

Overview: Sandstorm is an open-source, self-hosted web application platform designed to make it easy to install and run a wide variety of applications with minimal fuss. It emphasizes security and user control, offering a unique approach where each instance of an application runs in a separate, secure container.
12 Factor Alignment: While Sandstorm’s model is somewhat different from the typical PaaS, it aligns with several 12 Factor App principles through its application packaging and isolation model. It automates dependencies within each app’s package, and configuration can be managed through the Sandstorm interface.
Technology: Sandstorm is developed using a combination of technologies, primarily utilizing Cap’n Proto for data serialization and sandboxing techniques for application isolation. It does not rely on Docker but instead uses its own sandboxing technology to isolate applications.

Flynn (unmaintained)¶

Overview: Flynn was An open-source PaaS that provides everything needed to run an application, from databases to continuous deployment.
12 Factor Alignment: Offers isolated environments for applications, manages dependencies, and ensures that configuration is environment-stored. It includes built-in databases and backing services.
Technology: Utilizes its own layer, written in Go, atop various technologies, including Docker, for application isolation.

These open-source PaaS solutions showcase a wide range of technologies and approaches to self-hosted application deployment and management, each aligning with the 12-factor app principles to varying degrees. They offer developers the flexibility to choose a platform that best fits their specific needs and technical preferences.

In-depth Exploration of Each Factor¶

Codebase: One codebase tracked in version control, with many deployments¶

Original Statement: An application should have exactly one codebase, which is tracked in version control, that can be deployed to multiple environments.

Real-World Example: A common example is a web application hosted on GitHub or Bitbucket, where the same repository is used to deploy the application to development, staging, and production environments on a Platform as a Service (PaaS) like Heroku. Changes are made to the master branch, then deployed to a staging environment for testing. Once approved, the same changes are deployed to the production environment.

Relevance Today and Modernization: The principle of a single codebase remains highly relevant as it underpins the practice of continuous integration and delivery (CI/CD). To modernize this principle, organizations can adopt GitOps practices, where infrastructure and application configuration are also stored as code in version control, allowing the entire application, including its infrastructure, to be versioned, and reviewed, and automatically deployed.

Dependencies: Explicitly declare and isolate dependencies¶

Original Statement: A twelve-factor app never relies on implicit existence of system-wide packages. Instead, it declares all dependencies, completely and exactly, via a dependency declaration manifest.

Real-World Example: An application developed in Node.js might use a package.json file to declare its dependencies, ensuring that anyone who clones the repository can run npm install to fetch and install the exact versions of required libraries. This approach is especially useful on platforms like AWS Elastic Beanstalk, where the application’s environment can be precisely replicated based on the dependencies file.

Relevance Today and Modernization: This factor is fundamental for containerization technologies like Docker. To modernize, developers can use containerization to encapsulate their application along with its dependencies into a container, making the application even more portable and its environment more replicable across different systems and platforms.

Config: Store config in the environment¶

Original Statement: Store configuration that varies between deployments (credentials, resource handles, etc.) in the environment, not in the code.

Real-World Example: An application deployed on Microsoft Azure might use Azure App Configuration to manage and access application settings. Configuration values like database connection strings are stored in Azure’s managed service and accessed by the application at runtime, ensuring that sensitive information is not hard-coded into the application’s source code.

Relevance Today and Modernization: With the rise of microservices and distributed systems, managing configuration across many services has become more complex. Modernizing this principle involves using centralized configuration services that support dynamic changes and can propagate updates in real-time without needing to redeploy services. Tools like HashiCorp Vault for secrets management or Spring Cloud Config for distributed configuration can be used to manage application configuration securely and efficiently.

Backing Services: Treat backing services as attached resources¶

Original Statement: A twelve-factor app treats backing services (databases, messaging/queueing systems, caching systems, etc.) as attached resources, which can be swapped out or connected without any changes to the app’s code.

Real-World Example: Consider an application deployed on Google Cloud Platform (GCP) that uses Google Cloud SQL as a database service. If the development team decides to switch to MongoDB Atlas for its flexible document model, the change can be made by updating the application’s environment variables to point to the new database service, without needing to alter the application’s code. This illustrates the application’s ability to treat these services as attached resources, facilitating flexibility and scalability.

Relevance Today and Modernization: In today’s cloud-native environment, the concept of backing services as attached resources is more relevant than ever, especially with the proliferation of managed services and APIs. Modern applications can further embrace this principle by leveraging service mesh technologies like Istio or Linkerd, which abstract the communication between services, making it easier to manage, secure, and swap out services without impacting application logic.

Build, Release, Run: Strictly separate build and run stages¶

Original Statement: The twelve-factor app strictly separates the build stage (transforming code into executable bundle), the release stage (combining the build with the current config), and the run stage (running the application in the execution environment).

Real-World Example: A project hosted on GitHub uses GitHub Actions for continuous integration. Once code is pushed to the repository, a new build is automatically created. This build is then combined with the appropriate environment-specific configuration to create a release, which is then deployed to a PaaS like Heroku. This clear separation ensures that the build step is only done once, and the same build can be deployed across different environments.

Relevance Today and Modernization: With the advent of container orchestration tools like Kubernetes, the separation of build, release, and run stages has become even more critical. Modern practices could include using Docker for building container images (build), Helm charts for packaging these images with configuration for deployment (release), and Kubernetes for orchestrating the deployment and management of these containers (run). This enhances reproducibility, scalability, and manageability.

Processes: Execute the app as one or more stateless processes¶

Original Statement: Execute the application as one or more stateless processes with shared-nothing. Any data that needs to persist must be stored in a stateful backing service, typically a database.

Real-World Example: A RESTful API service designed for cloud deployment, for instance, on Amazon Web Services (AWS), operates without maintaining any session state within the process. If it needs to store user sessions or other temporary state information, it uses Amazon DynamoDB, a managed NoSQL database, ensuring that each instance of the service is stateless and can be easily scaled up or down.

Relevance Today and Modernization: The principle of stateless processes is fundamental to the development of microservices architectures, ensuring services are loosely coupled and scalable. Modernization of this principle can involve leveraging cloud-native technologies like Kubernetes, which supports stateless workloads natively and provides patterns for managing stateful applications through Persistent Volumes (PV) and StatefulSets for those cases where state needs to be maintained.

Port binding: Export services via port binding¶

Original Statement: The app is completely self-contained and does not rely on runtime injection of a webserver into the execution environment to create a web-facing service. Instead, the web app exports HTTP as a service by binding to a port, and listening to requests coming in on that port.

Real-World Example: An application written in Python using the Flask framework is designed to run as a containerized service on Docker. Instead of relying on an external web server, the Flask app itself binds to a port that Docker exposes to the network. This setup allows the application to be accessible via the designated port, making it easy to deploy on any cloud platform, such as Kubernetes on Google Cloud Platform, by simply mapping the container port to a service.

Relevance Today and Modernization: The principle of port binding remains highly relevant, particularly with the rise of containerization and microservices architectures. Modern applications can enhance this principle by utilizing container orchestrators like Kubernetes, which manage service discovery and port binding dynamically, allowing applications to communicate internally and externally with minimal configuration.

Concurrency: Scale out via the process model¶

Original Statement: The app’s processes are a first-class citizen. The app can be scaled out horizontally via the process model. Different types of work within the app should be able to scale independently.

Real-World Example: An e-commerce platform deployed on AWS Elastic Beanstalk uses multiple types of worker processes: one for handling web requests, another for processing background jobs like email notifications, and another for batch processing. Each worker type scales independently based on demand — web request handlers scale with incoming traffic, while background job processors scale based on the queue length of jobs waiting to be processed.

Relevance Today and Modernization: In the context of modern cloud-native applications, this principle guides the design towards microservices and serverless architectures, where components can be scaled independently based on demand. Utilizing serverless functions (e.g., AWS Lambda, Azure Functions) for specific tasks within an application can provide even more granular scaling, automatically adjusting resources in response to real-time demand without manual intervention.

Disposability: Maximize robustness with fast startup and graceful shutdown¶

Original Statement: The twelve-factor app’s processes are disposable, meaning they can be started or stopped at a moment’s notice. This facilitates fast elastic scaling, rapid deployment of code or config changes, and robustness of production deploys.

Real-World Example: A video processing service running on Kubernetes has been designed for disposability. Each pod processes a video upload task. Once a task is completed, the pod is terminated. Kubernetes automatically scales the number of pods based on the queue length, ensuring fast startup for new tasks and graceful shutdown for completed ones. This setup enhances the service’s robustness by ensuring that any system can quickly recover from failures by spawning new instances.

Relevance Today and Modernization: Disposability is crucial for building resilient systems, especially in a microservices architecture where services frequently start and stop. Modernizing this principle involves leveraging cloud-native patterns and tools that support health checks, graceful shutdowns, and automatic recovery. Implementing Kubernetes liveness and readiness probes ensures that services are only available when fully functional, and auto-scaling rules can adjust resources efficiently in response to workload changes, embodying the disposability principle in a cloud-native context.

Dev/prod parity: Keep development, staging, and production as similar as possible¶

Original Statement: The twelve-factor app is designed for continuous deployment by keeping the gap between development and production small. Developers should be able to see their changes in production in a few hours or even minutes.

Real-World Example: A team developing a social media application uses Docker containers to keep their development, staging, and production environments as identical as possible. By using the same Docker images across these environments, the team ensures that any software running on a developer’s machine behaves the same way in production. Continuous Integration and Continuous Deployment (CI/CD) pipelines, facilitated by Jenkins or GitHub Actions, automate the testing and deployment process, further ensuring that changes can move quickly and safely from development to production.

Relevance Today and Modernization: The principle of dev/prod parity is increasingly relevant in a cloud-native world where infrastructure as code (IaC) and containerization are commonplace. Modern approaches to enhance this principle include using Kubernetes for orchestration across environments and Terraform for IaC to manage cloud resources, ensuring that the entire application stack, from the infrastructure to application runtime, is consistent across all environments. This minimizes “it works on my machine” problems and streamlines the path from development to production.

Logs: Treat logs as event streams¶

Original Statement: A twelve-factor app never concerns itself with routing or storage of its output stream. It should not attempt to write or manage log files. Instead, logs are treated as a continuous stream of events, emitted to stdout, and captured by the execution environment.

Real-World Example: An application deployed on Heroku writes all its logs to stdout, following the twelve-factor principles. Heroku captures these logs and provides a platform feature, Heroku Logs, which aggregates these streams from all running instances of the application. Developers can then use third-party log management services like Splunk or Loggly, integrated with Heroku, to analyze the log data, set up alerts, and monitor their application in real-time.

Relevance Today and Modernization: In today’s distributed, microservices-oriented architectures, the principle of treating logs as event streams is more crucial than ever. Modernizing this principle involves adopting centralized logging solutions like ELK Stack (Elasticsearch, Logstash, Kibana) or Grafana Loki, which can aggregate logs from various sources, making it easier to monitor, search, and analyze logs at scale. Additionally, employing cloud-native technologies like Fluentd or Prometheus for log collection and monitoring can further enhance observability and operational insights.

Admin processes: Run admin/management tasks as one-off processes¶

Original Statement: Run administrative tasks as one-off processes in an environment identical to the application’s regular long-running processes. These tasks should run against a release, using the same codebase and config as any process running in that release.

Real-World Example: An online marketplace platform uses AWS Elastic Beanstalk for its application deployment. When the development team needs to perform database migrations or cleanup tasks, they do so by executing scripts as one-off processes through AWS Elastic Beanstalk’s command line interface (CLI) or management console. These tasks run in an environment that mirrors the live application, using the same database configuration and access credentials, ensuring consistency and reducing the risk of errors.

Relevance Today and Modernization: With the advent of container orchestration and serverless architectures, the execution of admin tasks as one-off processes has become even more streamlined. Modern practices involve using Kubernetes Jobs and CronJobs for tasks that need to run once or at scheduled times, respectively. Serverless functions (e.g., AWS Lambda, Google Cloud Functions) offer another avenue for running administrative tasks, providing the benefits of scalability, cost-effectiveness, and isolation. These modern tools and practices ensure that admin processes are executed in a controlled, consistent environment, minimizing side effects and maximizing efficiency.

Beyond the Twelve-Factor App (2016)¶

Kevin Hoffman’s book, Beyond the Twelve-Factor App, published in 2016, expanded upon Adam Wiggins’ original twelve factors by introducing additional insights and principles, especially considering the advancements in cloud computing and microservices architectures.

Hoffman’s book acknowledges the significance of the original twelve factors but also recognizes areas where the technology and practices have evolved or where new emphases are needed to address modern development and operational challenges. Here are some key areas and insights Hoffman added to the discussion:

API-First: Hoffman emphasizes designing with APIs in mind from the start, ensuring that applications are built for integration and interaction with other services. This approach facilitates modularity and service reuse.
Telemetry: Extending the concept of logs, Hoffman discusses the importance of telemetry - metrics, logging, and tracing - for observing and understanding the behavior of applications in production environments. This enables better decision-making and more effective troubleshooting.
Authentication and Authorization: With security concerns paramount in modern application development, Hoffman highlights the need for robust authentication and authorization mechanisms to protect resources and data, especially in distributed and microservices-based architectures.
Backward Compatibility: As applications and services evolve, maintaining backward compatibility becomes crucial for ensuring uninterrupted service and minimizing the impact of changes on consumers.
Disposable Infrastructure: Building upon the idea of disposability in the original twelve factors, Hoffman discusses the concept of disposable infrastructure, where entire environments can be spun up and torn down with ease, further enabling agility and resilience.
Idempotency: Hoffman stresses the importance of idempotent operations, especially in distributed systems where operations may be retried or occur multiple times. Ensuring that repeating an operation does not change the outcome beyond the initial application is crucial for system consistency and reliability.
Dependency Management: While the original twelve factors discuss declaring and isolating dependencies, Hoffman delves deeper into the strategies for managing dependencies effectively, especially in complex, distributed systems.

Seven Additional Factors for Production-Ready Applications¶

In 2019, Shikha Srivastava, an IBM engineer, wrote in a blog post “While the 12-factor application guidelines are spot-on, there are another 7 factors are equally essential for a production environment”.

Here are here additional 7 factors:

Factor XIII: Observable¶

In a production environment, applications need to provide comprehensive visibility into their current health and operational metrics. Observability involves tracking application-specific metrics, such as transaction rates, error rates, and response times, in addition to basic system health checks. Monitoring tools such as Prometheus and Grafana are commonly used to collect and visualize these metrics. By exposing health metrics through endpoints and ensuring that failures are automatically detected and handled, teams can prevent potential issues before they affect the system’s overall functionality.

Factor XIV: Schedulable¶

Production applications should clearly define their resource requirements to avoid contention or resource starvation. This factor involves setting limits on memory and CPU usage to ensure that each container or service receives the appropriate resources. Defining resource requests and limits allows for effective resource allocation, ensuring that the application can handle workloads without causing performance degradation. Properly managed resource allocation also prevents issues when multiple applications share the same environment, maintaining system stability and performance.

Factor XV: Upgradable¶

Applications in production environments need to support seamless upgrades, whether for feature releases or critical security patches. The ability to perform rolling updates—where parts of the application are upgraded without downtime—is key to maintaining availability while ensuring the system remains up to date. By gradually replacing instances of the application during the upgrade process, it is possible to minimize disruption, ensuring that users experience a seamless transition to new versions.

Factor XVI: Least Privilege¶

Security is a paramount concern in production environments. Applications should run with the minimum set of privileges required to perform their tasks, reducing the attack surface in the event of a breach. Containers should be configured to run with non-root privileges, and access to sensitive resources should be restricted. Implementing the principle of least privilege ensures that applications are protected against exploitation, especially in shared environments where multiple services coexist.

Factor XVII: Auditable¶

Auditability is critical in environments where regulatory compliance or security is a concern. Production systems must keep detailed logs of all critical operations, including who performed actions, what actions were taken, and when they occurred. This allows for traceability, ensuring that any unauthorized or suspicious activity can be identified and investigated. Keeping audit trails is especially important in financial services, healthcare, or any sector that handles sensitive data, where legal and regulatory requirements demand transparency and accountability.

Factor XVIII: Securable¶

Securing applications in production requires robust measures to protect both the application itself and its resources. This includes ensuring proper authentication and authorization mechanisms, managing digital certificates for secure communication, and protecting data both in transit and at rest. Network security and isolation are also important, as they prevent unauthorized access to the application’s internal components. In addition, automated vulnerability assessments can identify potential security issues in the application’s dependencies and infrastructure, ensuring that the system remains secure over time.

Factor XIX: Measurable¶

For effective resource management and cost optimization, production systems need to be measurable. This involves tracking the compute resources consumed by each service or application, allowing for proper cost allocation and chargeback mechanisms. Metering tools can collect usage data at the container or namespace level, helping organizations ensure that their infrastructure is used efficiently and that individual teams are accountable for the resources they consume.

References¶

Additional “Factors”¶

Since the publication of Beyond the Twelve-Factor App by Kevin Hoffman in 2016, and considering the rapid evolution of software development practices, several emerging principles have gained prominence, complementing and extending the insights from Adam Wiggins’ original manifesto and Hoffman’s expansions. We have identified the following noteworthy principles that have become prevalent in recent years:

Security by Design: As security threats have become more sophisticated, integrating security practices throughout the software development lifecycle (SDLC) — from planning to deployment — has become critical. This principle emphasizes the importance of incorporating security measures early in the development process, rather than treating them as an afterthought.
Site Reliability Engineering (SRE) Practices: Originating from practices developed by Google, SRE has become a key framework for managing and operating scalable and reliable systems. It introduces concepts like error budgets and service level objectives (SLOs) to balance the need for reliability with the pace of innovation.
GitOps and Infrastructure as Code (IaC): While GitOps was briefly touched upon, its significance has grown, especially with the widespread adoption of Kubernetes. GitOps extends IaC for operational practices, using Git as a single source of truth for declarative infrastructure and applications, thereby improving the automation, reproducibility, and traceability of infrastructure changes.
Observability and Service Mesh: Beyond logging and monitoring, observability has emerged as a crucial capability for understanding the state of systems through metrics, logs, and traces. Service mesh technologies, like Istio and Linkerd, have become instrumental in providing observability, security, and network control within microservices architectures.
Sustainability in Software Design: With increasing awareness of climate change, there’s a growing emphasis on designing software that is efficient in terms of resource usage — compute, memory, and storage — to minimize environmental impact. This includes considerations for energy-efficient coding practices, selecting energy-efficient infrastructure, and optimizing data processing and storage.
Chaos Engineering: As systems become more complex, testing their reliability under stress or failure conditions has become important. Chaos engineering involves intentionally introducing failures into systems to test their resilience and the effectiveness of their recovery mechanisms.
Edge Computing: With the proliferation of IoT devices and the need for low-latency processing, edge computing has become a significant area of focus. It involves processing data closer to the source of data generation rather than in a centralized cloud-based location, thereby improving response times and reducing bandwidth usage.
Data Sovereignty and Privacy: With the implementation of regulations like GDPR and CCPA, handling data in a way that respects user privacy and compliance has become a principle of its own. This involves designing systems that can accommodate these requirements without significant rework.

These principles rare a response to new challenges and opportunities presented by advances in technology, regulatory changes, and societal expectations. They also underscore the need for agile, secure, and sustainable approaches to software development, ensuring that applications are not only functional and efficient but also resilient, compliant, and responsible in their use of resources and handling of data.

Conclusion: Adapting Software Development Principles for Modern Challenges¶

The evolution from Adam Wiggins’ 12 Factor App methodology to Kevin Hoffman’s extensions, Shikha Srivastava’s blog post, etc., and the subsequent emergence of several new ideas and principles, reflects the ongoing adaptation in software development practices in response to technological advancements and changing requirements. Cloud architects and developers should also maintain a focus on simplicity - a core motivation for cloud adoption often overlooked by overzealous architects or developers focused on trendy technologies.

The original 12 factors laid the foundation for building scalable and maintainable SaaS applications. In recent years, however, developments in cloud-native architectures, such as API-first designs, enhanced observability, and continuous integration and deployment (CI/CD), have further expanded the framework to address modern operational challenges. These new factors bring greater focus on security, sustainability, and operational efficiency, addressing the real-world demands of running production applications.

Key modern additions include:

Security by design: Integrating security from the start to ensure robust protection throughout the application lifecycle.
Observability: Enabling better insight into system health and performance, essential for managing complex distributed systems.
Sustainability: Designing applications that are efficient in resource use, mindful of environmental and operational costs.
Containerization and orchestration: Leveraging containers to enhance portability, scalability, and efficiency in deployments.
Continuous Integration/Continuous Deployment (CI/CD): Automating the development pipeline to improve development speed, testing, and reliability.

However, while these advancements are essential for modern cloud-native development, the primary goal of cloud adoption and methodologies like the 12-Factor App should remain simplifying development and operations. Over-complication, driven by unnecessary adoption of complex tools or methods, risks diluting the benefits of cloud-native approaches. It’s critical to strike a balance between leveraging advanced features and maintaining a manageable, efficient architecture.

For developers, architects, and technology leaders, the following takeaways are vital:

Stay informed and adaptable: Continuously learn and embrace emerging technologies and practices that add value.
Principles-driven development: Ensure that development remains rooted in foundational principles, adapting only where necessary.
Simplicity as a guiding value: Avoid unnecessary complexity by focusing on clear, simple, and maintainable design.
Evaluate before adoption: Critically assess the relevance and benefit of new technologies and methodologies before implementation.
Maintain operational efficiency: Balance new features with the need to keep systems maintainable and cost-efficient.

By applying these principles judiciously, and with a clear focus on simplicity and operational efficiency, development teams can:

Build high-quality, maintainable software.
Enhance system reliability and performance.
Strengthen security and data protection.
Optimize resource utilization and cost-effectiveness.
Accelerate development and deployment cycles.
Avoid the pitfalls of over-engineered solutions that add unnecessary complexity, increase costs, and reduce agility.

Ultimately, the combination of foundational practices and modern enhancements ensures that development processes remain agile, secure, and efficient, while keeping operational complexity in check.

#paas #devops #containerization #microservices

Page last modified: 2024-11-14 22:26:00