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Onboarding a REST API service with the Plain Java Enabler (PJE)

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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 Enabler (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.

Introduction​

Zowe 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 balancer

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. The libraries are JAR artifacts available through an artifactory. Using these libraries is the recommended approach to onboard a REST service with the API ML.

The PJE library serves the needs of Java developers who are not using either Spring Boot or the Spring Framework. If Spring Boot or the Spring framework are used in the project you would like to onboard, see the Onboarding Overview for the corresponding enablers.

Additionally, this enabler is not intended for use in projects that depend on Spring Cloud Netflix components. Configuration settings in the PJE and Spring Cloud Netflix 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 enablers, see the documentation in the Onboarding Overview.

Onboarding your REST service with API ML​

The 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.

  1. Prerequisites

  2. Configuring your project

  3. Configuring your service

  4. Registering your service with API ML

  5. (Optional) Validating the discoverability of your API service by the Discovery Service

  6. (Optional) Troubleshooting

Prerequisites​

Ensure that the prerequisites from the Onboarding Overview are met.

  • The REST API service to onboard 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 API ML version ZoweApimlVersion 1.3.0 and higher. We recommend that you check the Zowe Artifactory for latest stable 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.

  • The API Mediation Layer provides the sample application using the Plain Java Enabler in the api-layer repository

Configuring your project​

Use either Gradle or Maven build automation systems to configure the project with the service to be onboarded. Use the appropriate configuration procedure that corresponds to your build automation system.

Note: You can use either the Zowe Artifactory or an artifactory of your choice. 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 Gradle tasks provided in the source code.

Gradle build automation system​

Use the following procedure to use Gradle as your build automation system.

Follow these steps:

  1. Create a gradle.properties file in the root of your project if one does not already exist.

  2. 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.

    # Repository URL for getting the enabler-java artifact
    artifactoryMavenRepo=https://zowe.jfrog.io/zowe/libs-release/

  3. Add the following Gradle code block to the repositories section of your build.gradle file:

    repositories {
        ...

        maven {
            url artifactoryMavenRepo
        }
    }

  4. In the same build.gradle file, add the necessary dependencies for your service. If you use the Java enabler from the Zowe Artifactory, add the following code block to your build.gradle script. Replace the $zoweApimlVersion with the proper version of the enabler, for example: 1.3.0:

    implementation "org.zowe.apiml.sdk:onboarding-enabler-java:$zoweApimlVersion"
    implementation "org.zowe.apiml.sdk:common-service-core:$zoweApimlVersion"

    The published artifact from the Zowe Artifactory also contains the enabler dependencies from other software packages. If you are using an artifactory other than Zowe, add also the following dependencies in your service build.gradle script:

    implementation "com.netflix.eureka:eureka-client:1.10.15"
    implementation "org.apache.httpcomponents:httpcore:4.4.14"
    implementation "com.fasterxml.jackson.core:jackson-databind:2.11.4"
    implementation "com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.9.10"

    providedCompile "javax.servlet:javax.servlet-api:3.1.0"
    compileOnly "org.projectlombok:lombok:1.18.20"

    Notes:

    • You may need to add more dependencies as required by your service implementation.
    • The information provided in this file is valid for ZoweApimlVersion 1.3.0 and higher.

  5. In your project home directory, run the gradle clean build command to build your project. Alternatively, you can run gradlew to use the specific gradle version that is working with your project.

Maven build automation system​

Use the following procedure if you use Maven as your build automation system.

Follow these steps:

  1. Add the following XML tags within the newly created pom.xml file:

    <repositories>
        <repository>
            <id>libs-release</id>
            <name>libs-release</name>
            <url>https://zowe.jfrog.io/zowe/libs-release/</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
    </repositories>

    Tip: If you want to use snapshot version, replace libs-release with libs-snapshot in the repository url and change snapshots->enabled to true.

  2. Add the proper dependencies:

    <dependency>
        <groupId>org.zowe.apiml.sdk</groupId>
        <artifactId>onboarding-enabler-java</artifactId>
        <version>$zoweApimlVersion</version>
    </dependency>
    <dependency>
        <groupId>org.zowe.apiml.sdk</groupId>
        <artifactId>common-service-core</artifactId>
        <version>$zoweApimlVersion</version>
    </dependency>

  3. In the directory of your project, run the mvn clean package command to build the project.

Configuring your service​

To configure your service, create the configuration file service-configuration.yml in your service source tree resources directory. The default path for a java application is src/main/resources. The service-configuration.yml file is used to set the application properties and eureka metadata. Application properties are for your service runtime. For example, the ssl section specifies the keystore and trustore. The eureka metadata is used for registration with API Mediation Layer.

Note: To externalize service onboarding configuration, see: Externalizing onboarding configuration.

The following code snippet shows an example of service-configuration.yml. Some parameters which are specific for your service deployment are in ${parameterValue} format. For your service configuration file, provide actual values or externalize your onboarding configuration.

Example:

serviceId: sampleservice
title: Hello API ML
description: Sample API ML REST Service
baseUrl: https://${samplehost}:${sampleport}/${sampleservice}
serviceIpAddress: ${sampleHostIpAddress}
preferIpAddress: false

homePageRelativeUrl: /application/home
statusPageRelativeUrl: /application/info
healthCheckRelativeUrl: /application/health

discoveryServiceUrls:
    - https://${discoveryServiceHost1}:${discoveryServicePort1}/eureka
    - https://${discoveryServiceHost2}:${discoveryServicePort2}/eureka

routes:
    - gatewayUrl: api/v1
      serviceUrl: /sampleservice/api/v1

authentication:
   scheme: httpBasicPassTicket
   applid: ZOWEAPPL

apiInfo:
    - apiId: zowe.apiml.sampleservice
      version: 1.0.0
      gatewayUrl: api/v1
      swaggerUrl: http://${sampleServiceSwaggerHost}:${sampleServiceSwaggerPort}/sampleservice/api-doc
      doumentationUrl: http://
    - apiId: zowe.apiml.sampleservice
      version: 2.0.0
      gatewayUrl: api/v2
      swaggerUrl: http://${sampleServiceSwaggerHost}:${sampleServiceSwaggerPort}/sampleservice/api-doc?group=api-v2
      documentationUrl: http://
      defaultApi: true
catalog:
    tile:
        id: sampleservice
        title: Hello API ML
        description: Sample application to demonstrate exposing a REST API in the ZOWE API ML
        version: 1.0.0

ssl:
   enabled: true
   verifySslCertificatesOfServices: true
   protocol: TLSv1.2
   keyAlias: localhost
   keyPassword: password
   keyStore: keystore/localhost.keystore.p12
   keyStoreType: PKCS12
   keyStorePassword: password
   trustStore: keystore/localhost.truststore.p12
   trustStoreType: PKCS12
   trustStorePassword: password

Optional metadata section

The following snippet presents additional optional metadata that can be added.

Example:

customMetadata:
    yourqualifier:
        key1: value1
        key2: value2

The onboarding configuration parameters are broken down into the following groups:

REST service identification​

  • serviceId

    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 the serviceId for routing to the API service instances. When two API services use the same serviceId, 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 is sampleservice, the service URL in the API ML Gateway address space appears as the following path:

      https://gateway-host:gateway-port/sampleservice/api/v1/...

  • 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

    Note: Ensure that the baseUrl does not end with a trailing /. Inclusion of / causes a malformed URL if any of the above administrative endpoints begin with a /. It is expected that each administrative endpoint begins with a /. Warnings will be logged if this recommendation is not followed.

  • serviceIpAddress (Optional)

    This parameter specifies the service IP address and can be provided by a system administrator in the externalized service configuration. If this parameter is not present in the configuration file or is not set as a service context parameter, it is resolved from the hostname part of the baseUrl.

  • preferIpAddress (Optional)

    Set the value of this parameter to true to advertise a service IP address instead of its hostname.

Administrative endpoints​

The following snippet presents the format of the administrative endpoint properties:

homePageRelativeUrl:
statusPageRelativeUrl: /application/info
healthCheckRelativeUrl: /application/health

where:

  • homePageRelativeUrl

    specifies the relative path to the home page of your service.

    Start this path with /. If your service has no home page, leave this parameter blank.

    Examples:

    • homePageRelativeUrl: This service has no home page
    • homePageRelativeUrl: / 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 path with /.

    Example:

    healthCheckRelativeUrl: /application/health

    This results in the URL: ${baseUrl}/application/health

API info​

REST 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:

apiInfo:
    - apiId: zowe.apiml.sampleservice
      version: 1.0.0
      gatewayUrl: api/v1
      swaggerUrl: http://localhost:10021/sampleservice/api-doc
      documentationUrl: http://your.service.documentation.url
      defaultApi: true
      codeSnippet:
        - endpoint: /endpoint1
          language: java
          codeBlock: |
            System.out.println("Greeting code snippet");
        - endpoint: /endpoint2
          language: javascript
          codeBlock: |
            console.log('hello');

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. The apiId 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 the routes 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.

  • apiInfo.defaultApi (Optional)

    specifies that this API is the default one shown in the API Catalog. If no apiInfo fields have defaultApi set to true, the default API is the one with the highest API version.

  • apiInfo.codeSnippet (Optional)

    specifies the customized code snippet for a specific endpoint (API operation). The snippet is displayed in the API Catalog under the specified operation, after executing the request using the Try it out functionality. When specifying this configuration, you need to provide the following parameters:

    • endpoint
      The endpoint that represents the API operation of the customized snippet
    • language
      The language of the snippet
    • codeBlock
      The content of the snippet to be displayed in the API Catalog

API routing information​

The 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:

routes:
    - gatewayUrl: api
      serviceUrl: /sampleservice-api
    - gatewayUrl: api/v1
      serviceUrl: /sampleservice-api/ver1
    - gatewayUrl: api/v1/api-doc
      serviceUrl: /sampleservice-api/api-doc

where:

  • routes

    specifies the container element for the route.

  • 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.

Examples:

  • https://gateway:10010/sampleservice/api
    is routed to: 
    https://service:10015/sampleservice-api
  • API major version 1: 
    https://gateway:10010/sampleservice/api/v1
    is routed to: 
    https://service:10015/sampleservice-api/ver1
  • APIs docs major version 1: 
    https://gateway:10010/sampleservice/api/v1/api-doc
    is routed to: 
    https://service:10015/sampleservice-api/api-doc

API Catalog information​

The 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 following image is an example of a tile in the API Catalog:

Tile

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:

    catalog:
      tile:
        id: apimediationlayer
        title:  API Mediation Layer API
        description: The API Mediation Layer for z/OS internal API services.
        version: 1.0.0

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.

Authentication parameters​

These parameters are not required. Default values are used when parameters are not specified. For more information, see Authentication Parameters for Onboarding REST API Services.

API Security​

REST 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 parameters 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 to false in production environments 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 protocol

  • keyAlias

    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. When using keyring, the value should be set to the SAF keyring location. For information about required certificates, see Zowe API ML TLS requirements.

    If you have an issue with loading the keystore file in your environment, try to provide the absolute path to the keystore file. The sample keystore file for local deployment is in api-layer repository

  • 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. When using keyring, this value should be set to the SAF keyring location. For information about required certificates, see Zowe API ML TLS requirements.

    If you have an issue with loading the truststore file in your environment, try to provide the absolute path to the truststore file. The sample truststore file for local deployment is in api-layer repository

  • 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.

Note: Ensure that you define both the keystore and the truststore even if your server is not using an Https port.

SAF Keyring configuration​

You can choose to use SAF keyring instead of keystore and truststore for storing certificates. For information about required certificates, see Zowe API ML TLS requirements. For information about running Java on z/OS with keyring, see SAF Keyring. Make sure that the enabler can access and read the keyring. Please refer to documentation of your security system for details.

The following example shows enabler configuration with keyrings.

Example:

ssl:
    keyAlias: localhost
    keyPassword: password
    keyStore: safkeyring:////my_racf_id/my_key_ring
    keyStorePassword: password
    keyStoreType: JCERACFKS
    trustStore: safkeyring:////my_racf_id/my_key_ring
    trustStoreType: JCERACFKS
    trustStorePassword: password

Eureka Discovery Service​

The Eureka Discovery Service parameters group contains a single parameter used to address Eureka Discovery Service location. An example is presented in the following snippet:

Example:

discoveryServiceUrls:
- https://localhost:10011/eureka
- http://......

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.

Custom Metadata​

For information about custom metadata, see the topic Custom Metadata.

Registering your service with API ML​

The following steps outline the process of registering your service with API ML. Each step is described in detail in this article. The process describes the integration with the usage of the Java application server. The guideline is tested with the Tomcat application server. The specific steps that apply for other application servers may differ.

  1. Add a web application context listener class
  2. Register a web application context listener
  3. Load service configuration
  4. Register with Eureka discovery service
  5. Unregister your service

Follow these steps:

  1. Implement and add a web application context listener class:

    implements javax.servlet.ServletContextListener

    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 the apiMediationClient.register(config) method to register the application with API Mediation Layer when the application starts.
    • The contextDestroyed method invokes the apiMediationClient.unregister() method when the application shuts down. This unregisters the application from the API Mediation Layer.

  2. Register a web application context listener.

    Add the following code block to the deployment descriptor web.xml to register a context listener:

    <listener>
        <listener-class>com.your.package.ApiDiscoveryListener</listener-class>
    </listener>

  3. 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:

    @Override
    public void contextInitialized(ServletContextEvent sce) {
        ...
        String configurationFile = "/service-configuration.yml";
        ApiMediationServiceConfig config = new ApiMediationServiceConfigReader().loadConfiguration(configurationFile);
        ...

    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 the ApiMediationServiceConfigReader class JavaDoc for details.

  4. Register with Eureka Discovery Service.

    Use the following call to register your service instance with Eureka Discovery Service:

    Example:

    try {
        apiMediationClient = new ApiMediationClientImpl()
        apiMediationClient.register(config);
    } catch (ServiceDefinitionException sde) {
        log.error("Service configuration failed. Check log for previous errors: ", sde);
    }

  5. Unregister your service.

    Use the contextDestroyed method to unregister your service instance from Eureka Discovery Service in the following format:

    Example:

    @Override
    public void contextDestroyed(ServletContextEvent sce) {
        if (apiMediationClient != null) {
            apiMediationClient.unregister();
        }

        apiMediationClient = null;
    }

The following code block is a full example of a context listener class implementation.

Example:

import org.zowe.apiml.eurekaservice.client.ApiMediationClient;
import org.zowe.apiml.eurekaservice.client.config.ApiMediationServiceConfig;
import org.zowe.apiml.eurekaservice.client.impl.ApiMediationClientImpl;
import org.zowe.apiml.eurekaservice.client.util.ApiMediationServiceConfigReader;
import org.zowe.apiml.exception.ServiceDefinitionException;
import lombok.extern.slf4j.Slf4j;
import javax.servlet.ServletContextEvent;
import javax.servlet.ServletContextListener;
/**
 *  API ML Micro service implementation of ServletContextListener interface.
 */
@Slf4j
public class ApiDiscoveryListener implements ServletContextListener {
    /**
     * @{link ApiMediationClient} instance used to register and unregister the service with API ML Discovery service.
     */
    private ApiMediationClient apiMediationClient;
    /**
     *  Loads a {@link ApiMediationServiceConfig} using an instance of class ApiMediationServiceConfigReader
     *  and registers this micro service with API ML.
     *
     *  {@link ApiMediationServiceConfigReader} has several methods for loading configuration from YAML file,
     *  {@link java.util.Map} or a string containing the configuration data.
     *
     *  Here we use the most convenient method for our Java Servlet based service,
     *  i.e expecting all the necessary initialization information to be present
     *  in the  {@link javax.servlet.ServletContext} init parameters.
     *  After successful initialization, this method creates an {@link ApiMediationClient} instance,
     *  which is then used to register this service with API ML Discovery Service.
     *
     *  The registration method of ApiMediationClientImpl catches all RuntimeExceptions
     *  and only can throw {@link ServiceDefinitionException} checked exception.
     *
     * @param sce
     */
    @Override
    public void contextInitialized(ServletContextEvent sce) {
        try {
            /*
             * Load configuration method with ServletContext
             */
            ApiMediationServiceConfig config = new ApiMediationServiceConfigReader().loadConfiguration(sce.getServletContext());
            if (config  != null) {
                /*
                 * Instantiate {@link ApiMediationClientImpl} which is used to un/register the service with API ML Discovery Service.
                 */
                apiMediationClient = new ApiMediationClientImpl();
                /*
                 * Call the {@link ApiMediationClient} instance to register your micro service with API ML Discovery Service.
                 */
                apiMediationClient.register(config);
            }
        } catch (ServiceDefinitionException sde) {
            log.error("Service configuration failed. Check log for previous errors: ", sde);
        }
    }
    /**
     * If apiMediationClient is not null, attempt to unregister this service from API ML registry.
     */
    @Override
    public void contextDestroyed(ServletContextEvent sce) {
        if (apiMediationClient != null) {
            apiMediationClient.unregister();
        }
        apiMediationClient = null;
    }
}

Validating the discoverability of your API service by the Discovery Service​

Once 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.

Follow these steps:

  1. Validate successful onboarding

  2. Check that you can access your API service endpoints through the Gateway.

  3. (Optional) Check that you can access your API service endpoints directly outside of the Gateway.

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.

Troubleshooting​

Log messages during registration problems​

When an Enabler connects to the Discovery service and fails, an error message prints to the Enabler log. The default setting does not suppress these messages as they are useful to resolve problems during the Enabler registration. Possible reasons for failure include the location of Discovery service is not correct, the Discovery Service is down, or the TLS certificate is invalid.

These messages continue to print to the Enabler log, while the Enabler retries to connect to the Discovery Service. To fully suppress these messages in your logging framework, set the log levels to OFF on the following loggers:

com.netflix.discovery.DiscoveryClient, com.netflix.discovery.shared.transport.decorator.RedirectingEurekaHttpClient

Some logging frameworks provide other tools to suppress repeated messages. Consult the documentation of the logging framework you use to find out what tools are available. The following example demonstrates how the Logback framework can be used to suppress repeated messages.

Example:

The Logback framework provides a filter tool, DuplicateMessageFilter.

Add the following code to your configuration file if you use XML configuration:

<turboFilter class="ch.qos.logback.classic.turbo.DuplicateMessageFilter">
    <AllowedRepetitions>0</AllowedRepetitions>
</turboFilter>

Note: For more information, see the full configuration used in the Core Services in GitHub.

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