Onboarding a REST API service with the Plain Java Enabler (PJE)
This article is part of a series of onboarding guides, which outline the process of onboarding REST API services to the Zowe API Mediation Layer (API ML). As a service developer, you can onboard a REST service with the API ML with the Zowe API Mediation Layer using our Plain Java Eabler (PJE). This enabler is built without a dependency on Spring Cloud, Spring Boot, or SpringFramework.
Tip: For more information about onboarding API services with the API ML, see the Onboarding Overview.
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IntroductionZowe API ML is a lightweight API management system based on the following Netflix components:
- Eureka - a discovery service used for services registration and discovery
- Zuul - reverse proxy / API Gateway
- Ribbon - load ballancer
The API ML Discovery Service component uses Netflix/Eureka as a REST services registry. Eureka endpoints are used to register a service with the API ML Discovery Service.
The API ML provides onboarding enabler libraries. Using these libraries is the recommended approach to onboard a REST service with the API ML. While it is possible to call the Eureka registration endpoint directly, this approach requires preparing corresponding configuration data. Doing so is unnecessarily complex and time-consuming.
Additionally, while the PJE library can be used in REST API projects based on SpringFramework or the Spring Boot framework, it is not recommended to use this enabler in projects that depend on SpringCloud Netflix components. Configuration settings in the PJE and SpringCloud Eureka Client are different. Using the two configuration settings in combination makes the result state of the discovery registry unpredictable.
Tip: For more information about how to utilize another API ML enabler, see:
- Onboard a Spring Boot REST API service
- Onboard a REST service directly calling eureka with xml configuration
- Onboard an existing REST API service without code changes
- Java REST APIs service without Spring Boot
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Onboarding your REST service with API MLThe following steps outline the overall process to onboard a REST service with the API ML using the PJE. Each step is described in further detail in this article.
- (Optional) Validating your API service discoverability
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PrerequisitesEnsure that the following prerequisites are met before you begin to use the PJE to onboard your REST service with the API ML:
- Your REST API service is written in Java.
- The service is enabled to communicate with API ML Discovery Service over a TLS v1.2 secured connection.
Notes:
This documentation is valid for
ZoweApimlVersion 1.2.0
and higher. We recommend that you check the Giza Artifactory for newer versions.Following this guide enables REST services to be deployed on a z/OS environment. Deployment to a z/OS environment, however, is not required. As such, you can first develop on a local machine before you deploy on z/OS.
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Configuring your projectUse either Gradle or Maven build automation systems to configure your project. Use the appropriate configuration procedure corresponding to your build automation system.
Note: You can use either the Giza Artifactory or an Artifactory of your choice. However, if you decide to build the API ML from source, you are required to publish the enabler artifact to your Artifactory. Publish the enabler artifact by using the provided Gradle tasks provided in the source code.
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Gradle build automation systemUse the following procedure to use Gradle as your build automation system.
Follow these steps:
Create a
gradle.properties
file in the root of your project if one does not already exist.In the
gradle.properties
file, set the URL of the specific Artifactory containing the PJE artifact. Provide the corresponding credentials to gain access to the Maven repository.If you are using the Giza Artifactory, use the credentials in the following code block:
Add the following Gradle code block to the
repositories
section of yourbuild.gradle
file:In the same
build.gradle
file, add the necessary dependencies for your service. If you use the Java enabler from the Giza Artifactory, add the following code block to yourbuild.gradle
script:Note: The published artifact from the Giza Artifactory also contains the enabler dependencies from other software packages. If you are using an Artifactory other than Giza, manually provide the following dependencies in your service
build.gradle
script:Notes:
- You may need to add more dependencies as required by your service implementation.
- The information provided in this file is valid for
ZoweApimlVersion 1.1.12
and above.
In your project home directory, run the
gradle clean build
command to build your project. Alternatively, you can rungradlew
to use the specific gradle version that is working with your project.
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Maven build automation systemUse the following procedure if you use Maven as your build automation system.
Follow these steps:
Add the following XML tags within the newly created
pom.xml
file:Create a
settings.xml
file and copy the following XML code block that defines the credentials for the Artifactory:Tip: If you want to use snapshot version, set the
/servers/server/id
tolibs-snapshot
.Copy the
settings.xml
file inside the${user.home}/.m2/
directory.In the directory of your project, run the
mvn package
command to build the project.
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Configuring your serviceProvide default service configuration in the service-configuration.yml
file located in your service source tree resources directory.
Note: To externalize service onboarding configuration, see: Externalizing onboarding configuration.
The following code snippet shows an example of service-configuration.yml
. Some parameters values which are specific for your service deployment
are written in #{parameterValue}
format. For your service configuration file, provide actual values or externalize your onboarding configuration.
Example:
The onboarding configuration parameters are broken down into the following groups:
- REST service identification
- Administrative endpoints
- API info
- API routing information
- API catalog information
- API security
- Eureka Discovery Service
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REST service identificationserviceId
The
serviceId
uniquely identifies one or more instance of a microservice in the API ML and is used as part of the service URL path in the API ML gateway address space. Additionally, the API ML Gateway uses theserviceId
for routing to the API service instances. When two API services use the sameserviceId
, the API Gateway considers the services as clones of each other. An incoming API request can be routed to either of them through utilized load balancing mechanism.Important! Ensure that the
serviceId
is set properly with the following considerations:The same
servicedId
should only be set for multiple API service instances for API scalability.The
servicedId
value must only contain lowercase alphanumeric characters.The
servicedId
cannot contain more than 40 characters.Example:
If the
serviceId
issampleservice
, the service URL in the API ML Gateway address space appears as the following path:
title
This parameter specifies the human readable name of the API service instance. This value is displayed in the API Catalog when a specific API service instance is selected. This parameter can be externalized and set by the customer system administrator.
Tip: We recommend that service developer provides a default value of the
title
. Use a title that describes the service instance so that the end user knows the specific purpose of the service instance.description
This parameter is a short description of the API service. This value is displayed in the API Catalog when a specific API service instance is selected. This parameter can be externalized and set by the customer system administrator.
Tip: Describe the service so that the end user understands the function of the service.
baseUrl
This parameter specifies the base URL for the following administrative endpoints:
homePageRelativeUrl
statusPageRelativeUrl
healthCheckRelativeUrl
Use the following format to include your service name in the URL path:
protocol://host:port/servicename
serviceIpAddress (Optional)
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Administrative endpointsThe following snippet presents the format of the administrative endpoint properties:
where:
homePageRelativeUrl
specifies the relative path to the home page of your service. The path should start with
/
. If your service has no home page, leave this parameter blank.Examples:
homePageRelativeUrl:
This service has no home pagehomePageRelativeUrl: /
This service has a home page with URL${baseUrl}/
statusPageRelativeUrl
specifies the relative path to the status page of your service.
Start this path with
/
.Example:
statusPageRelativeUrl: /application/info
This results in the URL:
${baseUrl}/application/info
healthCheckRelativeUrl
specifies the relative path to the health check endpoint of your service.
Start this URL with
/
.Example:
healthCheckRelativeUrl: /application/health
This results in the URL:
${baseUrl}/application/health
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API infoREST services can provide multiple APIs. Add API info parameters for each API that your service wants to expose on the API ML.
The following snippet presents the information properties of a single API:
where:
apiInfo.apiId
specifies the API identifier that is registered in the API ML installation. The API ID uniquely identifies the API in the API ML. The
apiId
can be used to locate the same APIs that are provided by different service instances. The API developer defines this ID. TheapiId
must be a string of up to 64 characters that uses lowercase alphanumeric characters and a dot:.
.apiInfo.version
specifies the api
version
. This parameter is used to correctly retrieve the API documentation according to requested version of the API.apiInfo.gatewayUrl
specifies the base path at the API Gateway where the API is available. Ensure that this value is the same path as the
gatewayUrl
value in theroutes
sections that apply to this API.apiInfo.swaggerUrl (Optional)
specifies the Http or Https address where the Swagger JSON document is available.
apiInfo.documentationUrl (Optional)
specifies the link to the external documentation. A link to the external documentation can be included along with the Swagger documentation.
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API routing informationThe API routing group provides the required routing information used by the API ML Gateway when routing incoming requests to the corresponding REST API service.
A single route can be used to direct REST calls to multiple resources or API endpoints. The route definition provides rules used by the API ML Gateway to rewrite the URL
in the Gateway address space. Currently, the routing information consists of two parameters per route: The gatewayUrl
and serviceUrl
. These two parameters together specify a rule for how the API service endpoints are mapped to the API Gateway endpoints.
The following snippet is an example of the API routing information properties.
Example:
where:
routes
specifies the container element for the routes.
routes.gatewayUrl
The gatewayUrl parameter specifies the portion of the gateway URL which is replaced by the serviceUrl path part.
routes.serviceUrl
The serviceUrl parameter provides a portion of the service instance URL path which replaces the gatewayUrl part.
Note: The routes configuration contains a prefix before the gatewayUrl
and serviceUrl
.
This prefix is used to differentiate the routes. It is automatically calculated by the API ML enabler.
Tip: For more information about API ML routing, see: API Gateway Routing.
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API Catalog informationThe API ML Catalog UI displays information about discoverable REST services registered with the API ML Discovery Service.
Information displayed in the Catalog is defined by the metadata provided by your service during registration.
The Catalog groups correlated services in the same tile, if these services are configured with the same catalog.tile.id
metadata parameter.
The following code block is an example of configuration of a service tile in the Catalog:
Example:
where:
catalog.tile.id
specifies the unique identifier for the product family of API services. This is a value used by the API ML to group multiple API services into a single tile. Each unique identifier represents a single API dashboard tile in the Catalog.
Tip: Specify a value that does not interfere with API services from other products. We recommend that you use your company and product name as part of the ID.
catalog.tile.title
specifies the title of the product family of the API service. This value is displayed in the API Catalog dashboard as the tile title.
catalog.tile.description
is the detailed description of the API services product family. This value is displayed in the API Catalog UI dashboard as the tile description.
catalog.tile.version
specifies the semantic version of this API Catalog tile.
Note: Ensure that you increase the version number when you introduce changes to the API service product family details.
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API SecurityREST services onboarded with the API ML act as both a client and a server. When communicating to API ML Discovery service, a REST service acts as a client. When the API ML Gateway is routing requests to a service, the REST service acts as a server. These two roles have different requirements. The Zowe API ML Discovery Service communicates with its clients in secure Https mode. As such, TLS/SSL configuration setup is required when a service is acting as a server. In this case, the system administrator decides if the service will communicate with its clients securely or not.
Client services need to configure several TLS/SSL parameters in order to communicate with the API ML Discovery service.
When an enabler is used to onboard a service, the configuration is provided in the ssl
section/group in the same YAML file that is used to configure the Eureka paramaters and the service metadata.
For more information about API ML security see: API ML security
TLS/SSL configuration consists of the following parameters:
verifySslCertificatesOfServices
This parameter makes it possible to prevent server certificate validation.
Important! Ensure that this parameter is set to
true
in production environments. Setting this parameter tofalse
in production environemnts significantly degrades the overall security of the system.protocol
This parameter specifies the TLS protocol version currently used by Zowe API ML Discovery Service.
Tip: We recommend you use
TLSv1.2
as your security protocolkeyAlias
This parameter specifies the
alias
used to address the private key in the keystore.keyPassword
This parameter specifies the password associated with the private key.
keyStore
This parameter specifies the keystore file used to store the private key.
keyStorePassword
This parameter specifies the password used to unlock the keystore.
keyStoreType
This parameter specifies the type of the keystore.
trustStore
This parameter specifies the truststore file used to keep other parties public keys and certificates.
trustStorePassword: password
This parameter specifies the password used to unlock the truststore.
trustStoreType: PKCS12
This parameter specifies the truststore type. The default for this parameter is PKCS12.
ciphers: (Optional)
This parameter specifies the recommended ciphers.
To secure the transfer of data, TLS/SSL uses one or more cipher suites. A cipher suite is a combination of authentication, encryption, and message authentication code (MAC) algorithms. CIphers are used during the negotiation of security settings for a TLS/SSL connection as well as for the transfer of data.
Notes:
- Ensure that you define both the key store and the trust store even if your server is not using an Https port.
- Currently
ciphers
is not used. It is optional and serves as a place holder only.
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Eureka Discovery ServiceEureka Discovery Service parameters group contains a single parameter used to address Eureka Discovery Service location. An example is presented in the following snippet:
where:
discoveryServiceUrls
specifies the public URL of the Discovery Service. The system administrator at the customer site defines this parameter. It is possible to provide multiple values in order to utilize fail over and/or load balancing mechanisms.
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Registering your service with API MLThe following steps outline the process of registering your service with API ML. Each step is described in detail in this article.
- Add a web application context listener class
- Register a web application context listener
- Load service configuration
- Register with Eureka discovery service
- Unregister your service
Follow these steps:
Add a web application context listener class.
The web application context listener implements two methods to perform necessary actions at application start-up time as well as when the application context is destroyed:
- The
contextInitialized
method invokes theapiMediationClient.register(config)
method to register the application with API Mediation Layer when the application starts. - The
contextDestroyed
method invokes theapiMediationClient.unregister()
method when the application shuts down. This unregisters the application from the API Mediation Layer.
- The
Register a web application context listener.
Add the following code block to the deployment descriptor
web.xml
to register a context listener:Load the service configuration.
Load your service configuration from a file
service-configuration.yml
file. The configuration parameters are described in the preceding section, Configuring your service.Use the following code as an example of how to load the service configuration.
Example:
Note: The
ApiMediationServiceConfigReader
class also provides other methods for loading the configuration from two files,java.util.Map
instances, or directly from a string. Check theApiMediationServiceConfigReader
class JavaDoc for details.Register with Eureka Discovery Service.
Use the following call to register your service instance with Eureka Discovery Service:
Unregister your service.
The following code block is a full example of a context listener class implementation.
Example:
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Adding API documentationUse the following procedure to add Swagger API documentation to your project.
Follow these steps:
Add a Springfox Swagger dependency.
For Gradle add the following dependency in
build.gradle
:For Maven add the following dependency in
pom.xml
:
Add a Spring configuration class to your project.
Example:
Customize this configuration according to your specifications. For more information about customization properties, see Springfox documentation.
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Validating the discoverability of your API service by the Discovery ServiceOnce you are able to build and start your service successfully, you can use the option of validating that your service is registered correctly with the API ML Discovery Service.
Validatiing your service registration can be done in the API ML Discovery Service and the API ML Catalog. If your service appears in the Discovery Service UI but is not visible in the API Catalog, check to make sure that your configuration settings are correct.
Specific addresses and user credentials for the individual API ML components depend on your target runtime environment.
Note: If you are working with local installation of API ML and you are using our dummy identity provider, enter user
for both username
and password
. If API ML was installed by system administrators, ask them to provide you
with actual addresses of API ML components and the respective user credentials.
Tip: Wait for the Discovery Service to discover your service. This process may take a few minutes after your service was successfully started.
Follow these steps:
Use the Http
GET
method in the following format to query the Discovery Service for your service instance information:Check your service metadata.
Response example:
Check that your API service is displayed in the API Catalog and all information including API documentation is correct.
Check that you can access your API service endpoints through the Gateway.
(Optional) Check that you can access your API service endpoints directly outside of the Gateway.