compiler.build.productionServerArchive - Create an archive for deployment to MATLAB
Production Server or Docker - MATLAB ([original](https://in.mathworks.com/help/compiler%5Fsdk/mps%5Fdev%5Ftest/compiler.build.productionserverarchive.html)) ([raw](?raw))
Create an archive for deployment to MATLAB Production Server or Docker
Since R2020b
Syntax
Description
compiler.build.productionServerArchive([FunctionFiles](#mw%5Fe45688cc-431e-44ac-a892-f5e6c88a1d77))
creates a deployable archive using the MATLAB® functions specified by FunctionFiles
.
compiler.build.productionServerArchive([FunctionFiles](#mw%5Fe45688cc-431e-44ac-a892-f5e6c88a1d77),[Name,Value](#namevaluepairarguments))
creates a deployable archive with additional options specified using one or more name-value arguments. Options include the archive name, JSON function signatures, and output directory.
compiler.build.productionServerArchive([opts](#mw%5F77e1e057-b522-462a-ab87-bdb9aa5ea6af))
creates a deployable archive with options specified using acompiler.build.ProductionServerArchiveOptions
objectopts
. You cannot specify any other options using name-value arguments.
[results](#mw%5F18d7ac43-69fc-4fc9-90a7-4ed36f6b4e8a) = compiler.build.productionServerArchive(___)
returns build information as a compiler.build.Results
object using any of the input argument combinations in previous syntaxes. The build information consists of the build type, the path to the compiled archive, and build options.
Examples
Create a deployable server archive.
In MATLAB, locate the MATLAB function that you want to deploy as an archive. For this example, use the file magicsquare.m
located in_`matlabroot`_\extern\examples\compiler
.
appFile = which('magicsquare.m');
Build a production server archive using thecompiler.build.productionServerArchive
command.
compiler.build.productionServerArchive(appFile);
This syntax generates the following files within a folder namedmymagicproductionServerArchive
in your current working directory:
includedSupportPackages.txt
— Text file that lists all support files included in the archive.mymagic.ctf
— Deployable production server archive file.mccExcludedFiles.log
— Log file that contains a list of any toolbox functions that were not included in the application. For information on non-supported functions, see MATLAB Compiler Limitations.readme.txt
— Readme file that contains information on deployment prerequisites and the list of files to package for deployment.requiredMCRProducts.txt
— Text file that contains product IDs of products required by MATLAB Runtime to run the application.
Create a production server archive and customize it using name-value arguments.
For this example, use the files addmatrix.m
andsubtractmatrix.mat
located in_`matlabroot`_\extern\examples\compiler
.
addFile = fullfile(matlabroot,'extern','examples','compilersdk','c_cpp','matrix','addmatrix.m'); subFile = fullfile(matlabroot,'extern','examples','compilersdk','c_cpp','matrix','subtractmatrix.m');
Build a production server archive using thecompiler.build.productionServerArchive
command. Use name-value arguments to specify the archive name and enable verbose output.
compiler.build.productionServerArchive({addFile,subFile}, ... 'ArchiveName','MatrixArchive', ... 'Verbose','on');
This syntax generates the following files within a folder namedMatrixArchiveproductionServerArchive
in your current working directory:
includedSupportPackages.txt
— Text file that lists all support files included in the archive.MatrixArchive.ctf
— Deployable production server archive file.mccExcludedFiles.log
— Log file that contains a list of any toolbox functions that were not included in the application. For information on non-supported functions, see MATLAB Compiler Limitations.readme.txt
— Readme file that contains information on deployment prerequisites and the list of files to package for deployment.requiredMCRProducts.txt
— Text file that contains product IDs of products required by MATLAB Runtime to run the application.
Customize multiple production server archives using a compiler.build.ProductionServerArchiveOptions object.
For this example, use the file hello.m
located in_`matlabroot`_\extern\examples\compiler
.
functionFile = which('hello.m');
Create a ProductionServerArchiveOptions
object. Use name-value arguments to specify a common output directory, disable the automatic inclusion of data files, and enable verbose output.
opts = compiler.build.ProductionServerArchiveOptions(functionFile, ...
'OutputDir','D:\Documents\MATLAB\work\ProductionServerBatch', ...
'AutoDetectDataFiles','off', ...
'Verbose','on')
opts =
ProductionServerArchiveOptions with properties:
ArchiveName: 'hello'
FunctionFiles: {'C:\Program Files\MATLAB\R2025a\extern\examples\compiler\hello.m'}
FunctionSignatures: ''
RoutesFile: ''
AdditionalFiles: {}
AutoDetectDataFiles: off
ExternalEncryptionKey: [0×0 struct]
ObfuscateArchive: off
SecretsManifest: ''
SupportPackages: {'autodetect'}
Verbose: on
OutputDir: 'D:\Documents\MATLAB\work\ProductionServerBatch'
Build the production server archive using theProductionServerArchiveOptions
object.
compiler.build.productionServerArchive(opts);
To compile using the function file houdini.m
with the same options, use dot notation to modify the FunctionFiles
of the existingProductionServerArchiveOptions
object before running the build function again.
opts.FunctionFiles = which('houdini.m'); compiler.build.productionServerArchive(opts);
By modifying the FunctionFiles
argument and recompiling, you can compile multiple archives using the same options object.
Create a microservice Docker® image using the results from building a production server archive on a Linux® system.
Install and configure Docker on your system.
Create a production server archive using magicsquare.m
and save the build results to a compiler.build.Results object.
appFile = which('magicsquare.m'); buildResults = compiler.build.productionServerArchive(appFile);
Pass the Results
object as an input to thecompiler.package.microserviceDockerImage
function to build the Docker image.
compiler.package.microserviceDockerImage(buildResults);
The function generates the following files within a folder namedmagicsquaremicroserviceDockerImage
in your current working directory:
applicationFilesForMATLABCompiler/magicsquare.ctf
— Deployable archive file.Dockerfile
— Docker file that specifies Docker run time options.GettingStarted.txt
— Text file that contains deployment information.
For more details, see Create Microservice Docker Image.
Create a production server archive and save information about the build type, archive file, included support packages, and build options to acompiler.build.Results
object.
Compile using the file magicsquare.m
.
results = compiler.build.productionServerArchive('magicsquare.m')
results =
Results with properties:
BuildType: 'productionServerArchive'
Files: {'D:\Documents\MATLAB\work\magicsquareproductionServerArchive\magicsquare.ctf'}
IncludedSupportPackages: {}
Options: [1×1 compiler.build.ProductionServerArchiveOptions]
RuntimeDependencies: [1×1 compiler.runtime.Dependencies]
The Files
property contains the path to the deployable archive file magicsquare.ctf
.
Input Arguments
Files implementing MATLAB functions, specified as a character vector, a string scalar, a string array, or a cell array of character vectors. File paths can be relative to the current working directory or absolute. Files must have one of the following extensions: .m
, .p
, .mlx
, or .mexa64
.
Example: ["myfunc1.m","myfunc2.m"]
Data Types: char
| string
| cell
Name-Value Arguments
Specify optional pairs of arguments asName1=Value1,...,NameN=ValueN
, where Name
is the argument name and Value
is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose Name
in quotes.
Example: 'Verbose','on'
A list of files and folders to be included within the production server archive.
Example: 'AdditionalFiles','MyFile.txt'
Data Types: char
| string
| cellstr vector
Name of the deployable archive, specified as a character vector or a string scalar. The default name of the generated archive is the first entry of the FunctionFiles argument.
Example: 'ArchiveName','MyMagic'
Data Types: char
| string
Flag to automatically include data files, specified as 'on'
or 'off'
, or as numeric or logical 1
(true
) or 0
(false
). A value of 'on'
is equivalent to true
, and 'off'
is equivalent to false
. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.
- If you set this property to
'on'
, then data files that you provide as inputs to certain functions (such asload
andfopen
) are automatically included in the production server archive. - If you set this property to
'off'
, then you must add data files to the archive using theAdditionalFiles
property.
Example: 'AutoDetectDataFiles','off'
Data Types: logical
Since R2024b
Paths to the external AES encryption key and MEX key loader files, specified as a scalar struct with exactly two row char vector or string scalar fields named EncryptionKeyFile
andRuntimeKeyLoaderFile
, respectively. Both struct fields are required. File paths can be relative to the current working directory or absolute.
For example, specify the encryption key as encrypt.key
and loader file as loader.mexw64
using structkeyValueStruct
.
keyValueStruct.EncryptionKeyFile='encrypt.key'; keyValueStruct.RuntimeKeyLoaderFile='loader.mexw64'
The encryption key file must be in one of the following supported formats:
- Binary 256-bit AES key, with a 32 byte file size
- Hex encoded AES key, with a 64 byte file size
The MEX file loader retrieves the decryption key at runtime and must be an interface with the following arguments:
prhs[0]
— Input, char array specified as the static value'get'
prhs[1]
— Input, char array specified as the CTF component UUIDplhs[0]
— Output, 32 byte UINT8 numeric array or 64 byte hex encoded char array, depending on the key format
Avoid sharing the same key across multiple CTFs.
Example: 'ExternalEncryptionKey',keyValueStruct
Data Types: struct
Path to a JSON file that details the signatures of all functions listed in FunctionFiles, specified as a character vector or a string scalar. For information on specifying function signatures, see MATLAB Function Signatures in JSON (MATLAB Production Server).
Example: 'FunctionSignatures','D:\Documents\MATLAB\work\magicapp\signatures.json'
Data Types: char
| string
Flag to obfuscate the deployable archive, specified as'on'/1/true
or 'off'/0/false
. The value is stored as an on/off logical value of type matlab.lang.onoffSwitchState.
If you set this property to 'on'
, then folder structures and file names in the deployable archive are obfuscated from the end user, and user code and data contained in .m
,.mlapp
, .p
, .mat
, MLX, SFX, and MEX files are placed into a user package within the archive. Additionally, all .m
files are converted to P-files before packaging.
During runtime, MATLAB code and data is decrypted and loaded directly from the user package rather than extracted to the file system. MEX files are temporarily extracted from the user package before being loaded.
To manually include additional file types in the user package, add each file type in a separate extension tag to the file_`matlabroot`_/toolbox/compiler/advanced_package_supported_files.xml
.
The following are not supported:
ver
function- Calling external libraries such as DLLs
- Out-of-process MATLAB Runtime (C++ shared library for MATLAB Data Array)
- Out-of-process MEX file execution (
mexhost
,feval
,matlab.mex.MexHost
) - Before R2023b:
.mat
files other than v7.3
Enabling this option is equivalent to using mcc
with-j
and -s
specified.
If you set this property to 'off'
, then the deployable archive is not obfuscated. This is the default behavior.
Example: 'ObfuscateArchive','on'
Data Types: logical
Path to the output directory where the build files are saved, specified as a character vector or a string scalar. The path can be relative to the current working directory or absolute.
The default name of the build folder is the archive name appended with productionServerArchive
.
Example: 'OutputDir','D:\Documents\MATLAB\work\MyMagicproductionServerArchive'
Since R2024a
Path to a JSON file that specifies custom URL routes on the server, specified as a character vector or a string scalar.
Example: RoutesFile,'routes.json'
Data Types: char
| string
Since R2024b
Path to a secret manifest JSON file that specifies the secret keys to be embedded in the deployable archive, specified as a character vector or a string scalar. The path can be relative to the current working directory or absolute.
If your MATLAB code calls the getSecret, getSecretMetadata, or isSecret function, you must specify the secret keys to embed in the deployable archive in a JSON secret manifest file. If your code callsgetSecret
and you do not specify theSecretsManifest
option, MATLAB Compiler™ issues a warning and generates a template JSON file in the output folder named_`<componentname>`__secrets_manifest.json
. Modify this file by specifying the secret key names in the Embedded field.
The setSecret function is not deployable. To embed secret keys in a deployable archive, you must call setSecret in MATLAB before you build the archive.
For more information on deployment using secrets, see Handle Sensitive Information in Deployed Applications.
Example: 'SecretsManifest','D:\Documents\MATLAB\work\mycomponent\mycomponent_secrets_manifest.json'
Data Types: char
| string
Support packages to include, specified as one of the following options:
'autodetect'
(default) — The dependency analysis process detects and includes the required support packages automatically.'none'
— No support packages are included. Using this option can cause runtime errors.- A string scalar, character vector, or cell array of character vectors — Only the specified support packages are included. To list installed support packages or those used by a specific file, see compiler.codetools.deployableSupportPackages
Example: 'SupportPackages',{'Deep Learning Toolbox Converter for TensorFlow Models','Deep Learning Toolbox Model for Places365-GoogLeNet Network'}
Data Types: char
| string
| cell
Build verbosity, specified as 'on'
or 'off'
, or as numeric or logical 1
(true
) or 0
(false
). A value of 'on'
is equivalent to true
, and 'off'
is equivalent to false
. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.
- If you set this property to
'on'
, then the MATLAB command window displays progress information indicating compiler output during the build process. - If you set this property to
'off'
, then the command window does not display progress information.
Example: 'Verbose','off'
Data Types: logical
Output Arguments
Build results, returned as a compiler.build.Results object. The Results
object consists of:
- The build type, which is
'productionServerArchive'
- Path to the deployable archive file
- A list of included support packages
- Build options, specified as a
ProductionServerArchiveOptions
object - A list of required and optional dependencies, specified as a
Dependencies
object
Limitations
- In releases before R2024a,
compiler.build.ProductionServerArchive
does not support packaging of an archive-specific routes JSON file for mapping of URL requests to web handler functions within the archive. Either define routes in the JSON file specified by the routes-file (MATLAB Production Server) configuration property or use mcc to package a routes JSON file into the archive.
Version History
Introduced in R2020b
Use the ExternalEncryptionKey
option to specify a 256-bit AES encryption key and a MEX-file loader interface to retrieve the decryption key at runtime. This option is equivalent to the mcc -k option.
Use the SecretsManifest
option to include a JSON file that specifies secrets to embed within your deployable code archive. This option is equivalent to themcc -J option.
Use the ObfuscateArchive
option to obfuscate folder structures and file names, and place MATLAB file data and user code into a user package within the archive. Additionally, all .m
files are converted to P-files before packaging. This option is equivalent to using mcc
with -j and-s specified.
Use the SupportPackages
option to specify support packages to include in the deployable code archive.