In the modern era, software is commonly delivered as a service: called web apps, or software-as-a-service. The twelve-factor app is a methodology for building software-as-a-service apps proposed by Heroku PaaS.
One-to-one correlation between the codebase and the app:
2. Dependencies. Explicitly declare and isolate dependencies.
Declare all dependencies completely and exactly via a dependency declaration manifest and use dependency isolation tool during execution.
3. Config. Store config in the environment.
An app's config is everything that is likely to vary between deploys:
4. Backing Services. Treat backing services as attached resources.
It's an any service which app consumes over the network as part of its normal operation. The code of app makes no distinction between local (means deployed to localhost) and third party services.
5. Build, release, run. Strictly separate build and run stages.
For example, it is impossible to make changes to the code in the runtime. Release can not mutate once it is created and any changes must create a new release.
6. Processes. Execute the app as one or more stateless processes.
Twelve-factor processes are stateless and share-nothing. Any data that needs to persist must be stored in a stateful backing service, typically a database. Sticky sessions are violation of twelve-factor and should never be used or relied upon. Session state data is a good candidate for a datastore that offers time-expiration, such as Memcached or Redis.
7. Port binding. Export services via port binding.
The twelve-factor app is completely self-contained and does not rely on runtime injection of a webserver into the execution environment. The web app exports HTTP as a service by binding to a port, and listening to requests coming in on that port.
8. Concurrency. Scale out via the process model.
In the twelve-factor app, processes are a first class citizen. Developer can architect their app to handle diverse workloads by assigning each type of work to a process type. This does not exclude individual processes from handling their own internal multiplexing, via threads inside the runtime VM, or the async/evented model. But an individual VM can only grow so large (vertical scale), so the application must also be able to span multiple processes running on multiple physical machines.
The share-nothing, horizontally partitionable nature of twelve-factor app processes means that adding more concurrency is a simple and reliable operation.
9. Disposability. Maximize robustness with fast startup and graceful shutdown.
The twelve-factor app's processes are disposable, meaning they can be started or stopped at a moment's notice. Processes should strive to minimize startup time.
10. Dev/prod parity. Keep development, staging, and production as similar as possible.
Minimize gaps between development and production environments:
11. Logs. Treat logs as event streams.
Logs are the stream of aggregated, time-ordered events collected from the output streams of all running processes and backing services.
A twelve-factor app never concerns itself with routing or storage of its output stream. Most significantly, the stream can be sent to a log indexing and analysis system, or a general-purpose data warehousing system such as Hadoop/Hive.
12. Admin Processes. Run admin/management tasks as one-off processes.
In a local deploy, developers invoke one-off admin processes by a direct shell command inside the app’s checkout directory. In a production deploy, developers can use ssh or other remote command execution mechanism provided by that deploy’s execution environment to run such a process.
References:
1. Codebase. One codebase tracked in revision control, many deploys.
One-to-one correlation between the codebase and the app:
- If multiple codebases - it's not an app but distributed system. And each component in a distributed system is an app.
- Multiple apps sharing the same code is violation of this principle. The solution is to factor code into libraries and include them via dependency management.
2. Dependencies. Explicitly declare and isolate dependencies.
Declare all dependencies completely and exactly via a dependency declaration manifest and use dependency isolation tool during execution.
3. Config. Store config in the environment.
An app's config is everything that is likely to vary between deploys:
- Resource handles to the database, Memcached, and other backing services
- Credentials to external services such as Amazon S3 or Twitter
- Per-deploy values such as canonical hostname for the deploy
4. Backing Services. Treat backing services as attached resources.
It's an any service which app consumes over the network as part of its normal operation. The code of app makes no distinction between local (means deployed to localhost) and third party services.
5. Build, release, run. Strictly separate build and run stages.
For example, it is impossible to make changes to the code in the runtime. Release can not mutate once it is created and any changes must create a new release.
6. Processes. Execute the app as one or more stateless processes.
Twelve-factor processes are stateless and share-nothing. Any data that needs to persist must be stored in a stateful backing service, typically a database. Sticky sessions are violation of twelve-factor and should never be used or relied upon. Session state data is a good candidate for a datastore that offers time-expiration, such as Memcached or Redis.
7. Port binding. Export services via port binding.
The twelve-factor app is completely self-contained and does not rely on runtime injection of a webserver into the execution environment. The web app exports HTTP as a service by binding to a port, and listening to requests coming in on that port.
8. Concurrency. Scale out via the process model.
In the twelve-factor app, processes are a first class citizen. Developer can architect their app to handle diverse workloads by assigning each type of work to a process type. This does not exclude individual processes from handling their own internal multiplexing, via threads inside the runtime VM, or the async/evented model. But an individual VM can only grow so large (vertical scale), so the application must also be able to span multiple processes running on multiple physical machines.
The share-nothing, horizontally partitionable nature of twelve-factor app processes means that adding more concurrency is a simple and reliable operation.
9. Disposability. Maximize robustness with fast startup and graceful shutdown.
The twelve-factor app's processes are disposable, meaning they can be started or stopped at a moment's notice. Processes should strive to minimize startup time.
10. Dev/prod parity. Keep development, staging, and production as similar as possible.
Minimize gaps between development and production environments:
- Make time gap small. A developer may write code and have it deployed hours or even just minutes later.
- Make personnel gap small: developers involved in deploying app and watching its behavior in production.
- Make the tools gap small: keep dev and prod as similar as possible.
11. Logs. Treat logs as event streams.
Logs are the stream of aggregated, time-ordered events collected from the output streams of all running processes and backing services.
A twelve-factor app never concerns itself with routing or storage of its output stream. Most significantly, the stream can be sent to a log indexing and analysis system, or a general-purpose data warehousing system such as Hadoop/Hive.
12. Admin Processes. Run admin/management tasks as one-off processes.
In a local deploy, developers invoke one-off admin processes by a direct shell command inside the app’s checkout directory. In a production deploy, developers can use ssh or other remote command execution mechanism provided by that deploy’s execution environment to run such a process.
References:
