The following page is a reference for how to create a Runtime by implementing the Runtime API interface. It's a way to add support for a new programming language to Vercel.
Note: If you're the author of a web framework, please use the Build Output API instead to make your framework compatible with Vercel.
A Runtime is an npm module that implements the following interface:
interface Runtime {
version: number;
build: (options: BuildOptions) => Promise<BuildResult>;
prepareCache?: (options: PrepareCacheOptions) => Promise<CacheOutputs>;
shouldServe?: (options: ShouldServeOptions) => Promise<boolean>;
startDevServer?: (
options: StartDevServerOptions
) => Promise<StartDevServerResult>;
}
The version
property and the build()
function are the only required fields.
The rest are optional extensions that a Runtime may implement in order to
enhance functionality. These functions are documented in more detail below.
Official Runtimes are published to the npm registry as a package and referenced in the use
property of the vercel.json
configuration file.
Note: The
use
property in thebuilds
array will work with any npm install argument such as a git repo URL, which is useful for testing your Runtime. Alternatively, thefunctions
property requires that you specify a specific tag published to npm, for stability purposes.
See the Runtimes Documentation to view example usage.
A required exported constant that decides which version of the Runtime API to use.
The latest and suggested version is 3
.
Example:
export const version = 3;
A required exported function that returns a Serverless Function.
What's a Serverless Function? Read about Serverless Functions to learn more.
Example:
import { BuildOptions, createLambda } from '@vercel/build-utils';
export async function build(options: BuildOptions) {
// Build the code here…
const lambda = createLambda(/* … */);
return {
output: lambda,
routes: [
// If your Runtime needs to define additional routing, define it here…
],
};
}
An optional exported function that is executed after build()
is
completed. The implementation should return an object of File
s that will be
pre-populated in the working directory for the next build run in the user's
project. An example use-case is that @vercel/node
uses this function to cache
the node_modules
directory, making it faster to install npm dependencies for
future builds.
Example:
import { PrepareCacheOptions } from '@vercel/build-utils';
export async function prepareCache(options: PrepareCacheOptions) {
// Create a mapping of file names and `File` object instances to cache here…
return {
'path-to-file': File,
};
}
An optional exported function that is only used by vercel dev
in Vercel
CLI and indicates whether a
Runtime wants to be responsible for responding
to a certain request path.
Example:
import { ShouldServeOptions } from '@vercel/build-utils';
export async function shouldServe(options: ShouldServeOptions) {
// Determine whether or not the Runtime should respond to the request path here…
return options.requestPath === options.entrypoint;
}
If this function is not defined, Vercel CLI will use the default implementation.
An optional exported function that is only used by vercel dev
in Vercel
CLI. If this function is defined, Vercel CLI will
not invoke the build()
function, and instead invoke this function for every
HTTP request. It is an opportunity to provide an optimized development experience
rather than going through the entire build()
process that is used in production.
This function is invoked once per HTTP request and is expected to spawn a child
process which creates an HTTP server that will execute the entrypoint code when
an HTTP request is received. This child process is single-serve (only used for
a single HTTP request). After the HTTP response is complete, vercel dev
sends
a shut down signal to the child process.
The startDevServer()
function returns an object with the port
number that the
child process' HTTP server is listening on (which should be an ephemeral
port) as well as the child process'
Process ID, which vercel dev
uses to send the shut down signal to.
Hint: To determine which ephemeral port the child process is listening on, some form of IPC is required. For example, in
@vercel/go
the child process writes the port number to file descriptor 3, which is read by thestartDevServer()
function implementation.
It may also return null
to opt-out of this behavior for a particular request
path or entrypoint.
Example:
import { spawn } from 'child_process';
import { StartDevServerOptions } from '@vercel/build-utils';
export async function startDevServer(options: StartDevServerOptions) {
// Create a child process which will create an HTTP server.
//
// Note: `my-runtime-dev-server` is an example dev server program name.
// Your implementation will spawn a different program specific to your runtime.
const child = spawn('my-runtime-dev-server', [options.entrypoint], {
stdio: ['ignore', 'inherit', 'inherit', 'pipe'],
});
// In this example, the child process will write the port number to FD 3…
const portPipe = child.stdio[3];
const childPort = await new Promise(resolve => {
portPipe.setEncoding('utf8');
portPipe.once('data', data => {
resolve(Number(data));
});
});
return { pid: child.pid, port: childPort };
}
- Runtimes are executed in a Linux container that closely matches the Servereless Function runtime environment.
- The Runtime code is executed using Node.js version 12.x.
- A brand new sandbox is created for each deployment, for security reasons.
- The sandbox is cleaned up between executions to ensure no lingering temporary files are shared from build to build.
All the APIs you export (analyze()
, build()
,
prepareCache()
, etc.) are not guaranteed to be run in the
same process, but the filesystem we expose (e.g.: workPath
and the results
of calling getWritableDirectory
) is retained.
If you need to share state between those steps, use the filesystem.
When a new build is created, we pre-populate the workPath
supplied to analyze
with the results of the prepareCache
step of the
previous build.
The analyze
step can modify that directory, and it will not be re-created when it's supplied to build
and prepareCache
.
The env and secrets specified by the user as build.env
are passed to the Runtime process. This means you can access user env via process.env
in Node.js.
We provide the ability to support more than 4KB of environment (up to 64KB) by way of a Lambda runtime wrapper that is added to every Lambda function we create. These are supported by many of the existing Lambda runtimes, but custom runtimes may require additional work.
The following Lambda runtime families have built-in support for the runtime wrapper:
nodejs
python
(>= 3.8)ruby
java11
java8.al2
(notjava8
)dotnetcore
If a custom runtime is based on one of these Lambda runtimes, large environment
support will be available without further configuration. Custom runtimes based on
other Lambda runtimes, including those that provide the runtime via provided
and
provided.al2
, must implement runtime wrapper support and indicate it via the
supportsWrapper
flag when calling createLambda
.
To add support for runtime wrappers to a custom runtime, first check the value of the
AWS_LAMBDA_EXEC_WRAPPER
environment variable in the bootstrap script. Its value is
the path to the wrapper executable.
The wrapper must be passed the path to the runtime as well as any parameters that the
runtime requires. This is most easily done in a small bootstrap
script.
In this simple bash
example, the runtime is called directly if
AWS_LAMBDA_EXEC_WRAPPER
has no value, otherwise the wrapper is called with the
runtime command as parameters.
#!/bin/bash
exec $AWS_LAMBDA_EXEC_WRAPPER path/to/runtime param1 param2
If the bootstrap
file is not a launcher script, but the entrypoint of the runtime
itself, replace the bootstrap process with the wrapper. Pass the path and parameters
of the executing file, ensuring the AWS_LAMBDA_EXEC_WRAPPER
environment variable is
set to blank.
This bash
example uses exec
to replace the running bootstrap process with the
wrapper, passing its own path and parameters.
#!/bin/bash
if [[ -n $AWS_LAMBDA_EXEC_WRAPPER ]]
__WRAPPER=$AWS_LAMBDA_EXEC_WRAPPER
AWS_LAMBDA_EXEC_WRAPPER=""
exec $__WRAPPER "$0" "${@}"
fi
# start the actual runtime functionality
Note that unsetting the variable may not have the desired effect due to the way Lambda spawns runtime processes. It is better to explicitly set it to blank.
The best way to replace the existing bootstrap process is with the
execve
syscall.
This is achieved by using exec
in bash
to replace the running process with the wrapper,
maintaining the same PID and environment.
Once support for runtime wrappers is included, ensure supportsWrapper
is set to
true
in the call to createLambda
. This will inform the build
process to enable large environment support for this runtime.
When you publish your Runtime to npm, make sure to not specify @vercel/build-utils
(as seen below in the API definitions) as a dependency, but rather as part of peerDependencies
.
import { File } from '@vercel/build-utils';
type Files = { [filePath: string]: File };
This is an abstract type that is implemented as a plain JavaScript Object. It's helpful to think of it as a virtual filesystem representation.
When used as an input, the Files
object will only contain FileRefs
. When Files
is an output, it may consist of Lambda
(Serverless Functions) types as well as FileRefs
.
An example of a valid output Files
object is:
{
"index.html": FileRef,
"api/index.js": Lambda
}
This is an abstract type that can be imported if you are using TypeScript.
import { File } from '@vercel/build-utils';
Valid File
types include:
import { FileRef } from '@vercel/build-utils';
This is a class that represents an abstract file instance stored in our platform, based on the file identifier string (its checksum). When a Files
object is passed as an input to analyze
or build
, all its values will be instances of FileRef
.
Properties:
mode: Number
file modedigest: String
a checksum that represents the file
Methods:
toStream(): Stream
creates a Stream of the file body
import { FileFsRef } from '@vercel/build-utils';
This is a class that represents an abstract instance of a file present in the filesystem that the build process is executing in.
Properties:
mode: Number
file modefsPath: String
the absolute path of the file in file system
Methods:
static async fromStream({ mode: Number, stream: Stream, fsPath: String }): FileFsRef
creates an instance of a FileFsRef fromStream
, placing file atfsPath
withmode
toStream(): Stream
creates a Stream of the file body
import { FileBlob } from '@vercel/build-utils';
This is a class that represents an abstract instance of a file present in memory.
Properties:
mode: Number
file modedata: String | Buffer
the body of the file
Methods:
static async fromStream({ mode: Number, stream: Stream }): FileBlob
creates an instance of a FileBlob fromStream
withmode
toStream(): Stream
creates a Stream of the file body
import { Lambda } from '@vercel/build-utils';
This is a class that represents a Serverless Function. An instance can be created by supplying files
, handler
, runtime
, and environment
as an object to the createLambda
helper. The instances of this class should not be created directly. Instead, invoke the createLambda
helper function.
Properties:
files: Files
the internal filesystem of the lambdahandler: String
path to handler file and (optionally) a function name it exportsruntime: LambdaRuntime
the name of the lambda runtimeenvironment: Object
key-value map of handler-related (aside of those passed by user) environment variablessupportsWrapper: Boolean
set to true to indicate that Lambda runtime wrappers are supported by this runtime
This is an abstract enumeration type that is implemented by one of the following possible String
values:
nodejs18.x
nodejs16.x
nodejs14.x
go1.x
java11
python3.9
dotnet6
dotnetcore3.1
ruby2.7
provided.al2
The following is exposed by @vercel/build-utils
to simplify the process of writing Runtimes, manipulating the file system, using the above types, etc.
Signature: createLambda(Object spec): Lambda
import { createLambda } from '@vercel/build-utils';
Constructor for the Lambda
type.
const { createLambda, FileBlob } = require('@vercel/build-utils');
await createLambda({
runtime: 'nodejs8.10',
handler: 'index.main',
files: {
'index.js': new FileBlob({ data: 'exports.main = () => {}' }),
},
});
Signature: download(): Files
import { download } from '@vercel/build-utils';
This utility allows you to download the contents of a Files
data
structure, therefore creating the filesystem represented in it.
Since Files
is an abstract way of representing files, you can think of
download()
as a way of making that virtual filesystem real.
If the optional meta
property is passed (the argument for
build()
), only the files that have changed are downloaded.
This is decided using filesRemoved
and filesChanged
inside that object.
await download(files, workPath, meta);
Signature: glob(): Files
import { glob } from '@vercel/build-utils';
This utility allows you to scan the filesystem and return a Files
representation of the matched glob search string. It can be thought of as the reverse of download
.
The following trivial example downloads everything to the filesystem, only to return it back (therefore just re-creating the passed-in Files
):
const { glob, download } = require('@vercel/build-utils');
exports.build = ({ files, workPath }) => {
await download(files, workPath);
return glob('**', workPath);
};
Signature: getWritableDirectory(): String
import { getWritableDirectory } from '@vercel/build-utils';
In some occasions, you might want to write to a temporary directory.
Signature: rename(Files, Function): Files
import { rename } from '@vercel/build-utils';
Renames the keys of the Files
object, which represent the paths. For example, to remove the *.go
suffix you can use:
const rename = require('@vercel/build-utils')
const originalFiles = { 'one.go': fileFsRef1, 'two.go': fileFsRef2 }
const renamedFiles = rename(originalFiles, path => path.replace(/\.go$/, '')