API Gateway is a server that acts as an API front-end, receives API requests, enforces throttling and security policies, passes requests to the back-end service and then passes the response back to the requestor.

In this guide you will learn how to build an API Gateway for a web service.

The following are the sections available in this guide.

• What you'll build
• Prerequisites
• Implementation
• Testing
• Deployment

To understand how you can build an API Gateway for RESTful web services using Ballerina, let’s consider a real world use case of ordering items from an e-shopping website for authorized users.

The following figure illustrates how the API Gateway created using Ballerina can be used with a RESTful service.

• Create Order : To place a new order you can send an HTTP POST request with the order details to localhost:9090/e-shop/order.

NOTE: You need to set the Authorization header in the request.

• Ballerina Distribution
• A Text Editor or an IDE

• Ballerina IDE plugins (IntelliJ IDEA, VSCode, Atom)
• Docker
• Kubernetes

If you want to skip the basics, you can download the GitHub repo and continue from the "Testing" section.

For the purpose of this guide, let's use the following package structure.

api-gateway
 └── guide
    ├── api_gateway
    │   ├── order_service.bal
    │   └── tests
    │       └── order_service_test.bal
    └── ballerina.conf

• Create the above directories in your local machine, along with the empty .bal files.

• You can add desired usernames and passwords inside the ballerina.conf file. We have added two sample users as follows,

["b7a.users"]

["b7a.users.alice"]
password="abc"
scopes="customer"

["b7a.users.bob"]
password="xyz"
scopes="customer"

• Then open the terminal and navigate to api-gateway/guide and run Ballerina project initializing toolkit.

   $ ballerina init

Now let us look into the implementation of the order management with the managed security layer.

import ballerina/http;
import ballerina/auth;

http:AuthProvider basicAuthProvider ={id:"basic1", scheme:"basic", authProvider:"config"};

// The endpoint used here is 'endpoints:ApiEndpoint', which by default tries to
// authenticate and authorize each request.
// The developer has the option to override the authentication and authorization
// at service and resource level.
endpoint http:APIListener listener {
    port:9090,
    authProviders:[basicAuthProvider]
};

// Add the authConfig in the ServiceConfig annotation to protect the service using Auth
@http:ServiceConfig {
    basePath:"/e-store",
    authConfig:{
        authProviders:["basic1"],
        authentication:{enabled:true}
    }
}
service<http:Service> eShopService bind listener {

    @Description {value:"Resource that handles the HTTP POST requests that are directed
         to the path '/order' to create a new order."}
    // Add authConfig param to the ResourceConfig to limit the access for scopes
    @http:ResourceConfig {
        methods:["POST"],
        path:"/order",
        // Authorize only users with "create_orders" scope
        authConfig:{
            scopes:["customer"]
        }
    }
    addOrder(endpoint client, http:Request req) {
        // Retrieve the order details from the request
        json orderReq = check req.getJsonPayload();
        // Extract the Order ID from the request from the order, use "1" for ID if Nill()
        string orderId = orderReq.Order.ID.toString() but { () => "1" };

        // Create response message.
        json payload = {status:"Order Created.", orderId:orderId};
        http:Response response;
        response.setJsonPayload(untaint payload);

        // Send response to the client.
        _ = client -> respond(response);

        log:printInfo("Order created: " + orderId);
    }
}

• With that we've completed the development of OrderMgtService with Auth authentication.

You can run the RESTful service that you developed above, in your local environment. Open your terminal and navigate to api-gateway/guide, and execute the following command.

$ ballerina run api_gateway_service

• You can test the functionality of the e-shop RESTFul service by sending HTTP requests. For example, here's a cURL command for sending a new request for an order.

NOTE: Use base64 encoding scheme to encode the <username>:<password> with the username and password pair which is in the ballerina.conf file. You can visit https://www.base64encode.org/ to base64 encode username and password. We will use YWxpY2U6YWJj as the base64 encoded value for alice:abc.

Create Order

$ curl -H "Authorization: Basic YWxpY2U6YWJj" -X POST -d \
'{ "Order": { "ID": "100500", "Name": "XYZ", "Description": "Sample order."}}' \
"http://localhost:9090/e-store/order" -H "Content-Type:application/json"

Output :  
{"status":"Order Created.", "orderId":"100500"}

In Ballerina, the unit test cases should be in the same package inside a folder named as 'tests'. When writing the test functions, follow the convention given below.

• Test functions should be annotated with @test:Config. See the following example.

   @test:Config
   function testeShop() {

The source code for this guide contains unit test cases for the api_gateway_service package implemented above. To run the unit tests, open your terminal and navigate to api-gateway/guide, and run the following command.

$ ballerina test -c ballerina.conf

The source code for the tests can be found at order_service_test.bal.

Once you are done with the development, you can deploy the service using any of the methods listed below.

• As the first step, you can build a Ballerina executable archive (.balx) of the service that we developed above. Navigate to api-gateway/guide and run the following command.

   $ ballerina build api_gateway_service

• Once the .balx file is created inside the target folder, you can run that with the following command.

   $ ballerina run target/api_gateway_service.balx

Services can be packaged and deployed as Docker containers as well. You can use the Ballerina Docker Extension (provided in the Ballerina Platform) which provides native support for running Ballerina programs in containers. You just need to add the relevant Docker annotations to your listener endpoints.

• In our order_service.bal file, we need to import ballerinax/docker and add the @docker:Config annotation to the listener endpoint as shown below to enable Docker image generation when building the service.

import ballerina/auth;
import ballerina/http;
import ballerinax/docker;

http:AuthProvider basicAuthProvider = {id:"basic1", scheme:"basic", authStoreProvider:"config"};

@docker:Config {
    registry:"ballerina.guides.io",
    name:"api_gateway",
    tag:"v1.0"
}
endpoint http:APIListener listener {
    port:9090,
    authProviders:[basicAuthProvider]
};

@http:ServiceConfig {
    basePath:"/e-shop",
    authConfig:{
        authProviders:["basic1"],
        authentication:{enabled:true}
    }
}
service<http:Service> eShop bind listener {

• Now you can build a Ballerina executable archive (.balx) of the service that we developed above, using the following command. It points to the service file that we developed above and it will create an executable binary out of that. This will also create the corresponding docker image using the docker annotations that you have configured above. Navigate to the <SAMPLE_ROOT>/guide/ folder and run the following command.

   $ ballerina build api_gateway_service
    Compiling source
        api_gateway_service:0.0.0

    Compiling tests
        api_gateway_service:0.0.0

    Running tests
        api_gateway_service:0.0.0
    ballerina: started HTTP/WS endpoint 0.0.0.0:9090
    ballerina: stopped HTTP/WS endpoint 0.0.0.0:9090
            [pass] testWithIncorrectAuth
            [pass] testWithCorrectAuth

            2 passing
            0 failing
            0 skipped

    Generating executable
        ./target/api_gateway_service.balx
            @docker 		 - complete 3/3

            Run following command to start docker container:
            docker run -d ballerina.guides.io/api_gateway:v1.0

• Once you have successfully built the Docker image, you can run it using the docker run command which was given at the end of the build output.

   $ docker run -d -p 9090:9090 ballerina.guides.io/api_gateway_service:v1.0

Here we are running a Docker container with the flag -p <host_port>:<container_port> to map the container's port 9090 to the host's port 9090 so that the service will be accessible through the same port on the host.

• Verify that the container is up and running with the use of docker ps. The status of the container should be shown as 'Up'.
• You can invoke the service using the same cURL commands that we've used above.

   $ curl -H "Authorization: Basic YWxpY2U6YWJj" -v -X POST -d '{ "Order": \
   { "ID": "100500", "Name": "XYZ", "Description": "Sample order."}}' \
   "http://localhost:9090/e-store/order" -H "Content-Type:application/json"    

• You can run the service that we developed above, on Kubernetes. The Ballerina language offers native support for running Ballerina programs on Kubernetes, with the use of Kubernetes annotations that you can include as part of your service code. It will create the necessary Docker images as well. Therefore there's no need to explicitly create Docker images prior to deploying it on Kubernetes.

• We need to import ballerinax/kubernetes and use @kubernetes annotations as shown below to enable Kubernetes deployment for the service we developed above.

NOTE: Linux users can use Minikube to try this out locally.

import ballerina/auth;
import ballerina/http;
import ballerinax/kubernetes;

@kubernetes:Ingress {
    hostname:"ballerina.guides.io",
    name:"ballerina-guides-restful-service",
    path:"/"
}
@kubernetes:Service {
    serviceType:"NodePort",
    name:"ballerina-guides-restful-service"
}
@kubernetes:Deployment {
    image:"ballerina.guides.io/api_gateway:v1.0",
    name:"ballerina-guides-restful-service"
}
endpoint http:Listener listener {
    port:9090
};

service<http:Service> eShop bind listener {

• Here we have used the @kubernetes:Deployment annotation to specify the name of the Docker image which will be created as part of building this service.
• We have also specified @kubernetes:Service so that it will create a Kubernetes service which will expose the Ballerina service that is running on a Pod.
• Additionally we have used @kubernetes:Ingress which is the external interface to access your service (with path / and host name ballerina.guides.io).

If you are using Minikube, you need to set a couple of additional attributes to the @kubernetes:Deployment annotation.

• dockerCertPath - The path to the certificates directory of Minikube (e.g., /home/ballerina/.minikube/certs).

• dockerHost - The host for the running cluster (e.g., tcp://192.168.99.100:2376). The IP address of the cluster can be found by running the minikube ip command.

• Now you can build a Ballerina executable archive (.balx) of the service that we developed above, using the following command. This will also create the corresponding Docker image and the Kubernetes artifacts using the Kubernetes annotations that you have configured above.

   $ ballerina build api_gateway_service
   Compiling source
       api_gateway_service:0.0.0

   Compiling tests
       api_gateway_service:0.0.0

   Running tests
       api_gateway_service:0.0.0
   ballerina: started HTTP/WS endpoint 0.0.0.0:9090
   ballerina: stopped HTTP/WS endpoint 0.0.0.0:9090
            [pass] testWithIncorrectAuth
            [pass] testWithCorrectAuth

            2 passing
            0 failing
            0 skipped

   Generating executable
       ./target/api_gateway_service.balx
            @kubernetes:Service 			 - complete 1/1
            @kubernetes:Ingress 			 - complete 1/1
            @kubernetes:Deployment 			 - complete 1/1
            @kubernetes:Docker 			     - complete 3/3

            Run following command to deploy kubernetes artifacts:
            kubectl apply -f ./target/api_gateway_service/kubernetes

• You can verify that the Docker image that we specified in @kubernetes:Deployment was created, by using the docker images command.
• Also the Kubernetes artifacts related to our service will be generated in ./target/api_gateway_service/kubernetes.
• Now you can create the Kubernetes deployment using:

   $ kubectl apply -f ./target/api_gateway_service/kubernetes 
 
   deployment.extensions "ballerina-guides-api-gateway" created
   ingress.extensions "ballerina-guides-restful-service" created
   service "ballerina-guides-eshop-service" created

• You can verify that the Kubernetes deployment, service and ingress are functioning as expected by using the following Kubernetes commands.

   $ kubectl get service
   $ kubectl get deploy
   $ kubectl get pods
   $ kubectl get ingress

• If everything is successfully deployed, you can invoke the service either via Node Port or Ingress.

Node Port:

$ curl  -H "Authorization: Basic YWxpY2U6YWJj" -v -X POST -d \
'{ "Order": { "ID": "100500", "Name": "XYZ", "Description": "Sample order."}}' \
"http://<Minikube_host_IP>:<Node_Port>/e-store/order" -H "Content-Type:application/json"

If you are using Minikube, you should use the IP address of the Minikube cluster obtained by running the minikube ip command. The port should be the node port given when running the kubectl get services command.

Ingress:

Add /etc/hosts entry to match hostname. For Minikube, the IP address should be the IP address of the cluster.

127.0.0.1 ballerina.guides.io

Invoke the service

$ curl  -H "Authorization: Basic YWxpY2U6YWJj" -v -X POST -d \
'{ "Order": { "ID": "100500", "Name": "XYZ", "Description": "Sample order."}}' \
"http://ballerina.guides.io/e-store/order" -H "Content-Type:application/json"

Ballerina comes with support for observability built-in to the language. Observability is disabled by default. It can be enabled by adding the following configurations to ballerina.conf file in api-gateway/guide/. A sample configuration file can be found in api-gateway/guide/api_gateway_service.

[b7a.observability]

[b7a.observability.metrics]
# Flag to enable Metrics
enabled=true

[b7a.observability.tracing]
# Flag to enable Tracing
enabled=true

   $ ballerina run --config api_gateway_service/ballerina.conf api_gateway_service/

NOTE: The above configuration is the minimum configuration needed to enable tracing and metrics. With these configurations, default values are loaded for the rest of the configuration parameters of metrics and tracing. To start the ballerina service using the configuration file, run the following command.

You can monitor Ballerina services using built-in tracing capabilities of Ballerina. We'll use Jaeger as the distributed tracing system. Follow the following steps to use tracing with Ballerina.

• You can add the following configurations for tracing. Note that these configurations are optional if you already have the basic configuration in ballerina.conf as described above.

   [b7a.observability]

   [b7a.observability.tracing]
   enabled=true
   name="jaeger"

   [b7a.observability.tracing.jaeger]
   reporter.hostname="localhost"
   reporter.port=5775
   sampler.param=1.0
   sampler.type="const"
   reporter.flush.interval.ms=2000
   reporter.log.spans=true
   reporter.max.buffer.spans=1000

• Run Jaeger Docker image using the following command

   $ docker run -d -p5775:5775/udp -p6831:6831/udp -p6832:6832/udp -p5778:5778 -p16686:16686 \
   -p14268:14268 jaegertracing/all-in-one:latest

• Navigate to api-gateway/guide and run the restful-service using the following command

   $ ballerina run --config api_gateway_service/ballerina.conf api_gateway_service

• Observe the tracing using Jaeger UI using following URL

   http://localhost:16686

Metrics and alerts are built-in with ballerina. We will use Prometheus as the monitoring tool. Follow the below steps to set up Prometheus and view metrics for the eShop service.

• You can add the following configurations for metrics. Note that these configurations are optional if you already have the basic configuration in ballerina.conf as described under the Observability section.

   [b7a.observability.metrics]
   enabled=true
   reporter="prometheus"

   [b7a.observability.metrics.prometheus]
   port=9797
   host="0.0.0.0"

• Create a file prometheus.yml inside /tmp/ location. Add the below configurations to the prometheus.yml file.

   global:
     scrape_interval:     15s
     evaluation_interval: 15s

   scrape_configs:
     - job_name: prometheus
       static_configs:
         - targets: ['172.17.0.1:9797']

NOTE : Replace 172.17.0.1 if your local Docker IP differs from 172.17.0.1

• Start a Prometheus Docker container using the following command

   $ docker run -p 19090:9090 -v /tmp/prometheus.yml:/etc/prometheus/prometheus.yml \
   prom/prometheus

• Navigate to api-gateway/guide and run the restful-service using the following command

   $ ballerina run --config api_gateway_service/ballerina.conf api_gateway_service

• You can access Prometheus at the following URL

   http://localhost:19090/

Ballerina has a log package for logging to the console. You can import ballerina/log package and start logging. The following section will describe how to search, analyze, and visualize logs in real time using Elastic Stack.

• Start the Ballerina service with the following command from api-gateway/guide

   $ nohup ballerina run api_gateway_service &>> ballerina.log&

NOTE: This will write the console log to the ballerina.log file in the api-gateway/guide directory

• Start Elasticsearch using the following command

   $ docker run -p 9200:9200 -p 9300:9300 -it -h elasticsearch --name \
   elasticsearch docker.elastic.co/elasticsearch/elasticsearch:6.2.2 

NOTE: Linux users might need to run sudo sysctl -w vm.max_map_count=262144 to increase vm.max_map_count

• Start Kibana plugin for data visualization with Elasticsearch

   $ docker run -p 5601:5601 -h kibana --name kibana --link \
   elasticsearch:elasticsearch docker.elastic.co/kibana/kibana:6.2.2     

• Configure Logstash to format the Ballerina logs

i) Create a file named logstash.conf with the following content

input {  
 beats{ 
     port => 5044 
 }  
}

filter {  
 grok{  
     match => { 
	 "message" => "%{TIMESTAMP_ISO8601:date}%{SPACE}%{WORD:logLevel}%{SPACE}
	 \[%{GREEDYDATA:package}\]%{SPACE}\-%{SPACE}%{GREEDYDATA:logMessage}"
     }  
 }  
}   

output {  
 elasticsearch{  
     hosts => "elasticsearch:9200"  
     index => "store"  
     document_type => "store_logs"  
 }  
}  

ii) Save the above logstash.conf inside a directory named as {SAMPLE_ROOT}/pipeline

iii) Start the Logstash container, replace the {SAMPLE_ROOT} with your directory name

$ docker run -h logstash --name logstash --link elasticsearch:elasticsearch \
-it --rm -v ~/{SAMPLE_ROOT}/pipeline:/usr/share/logstash/pipeline/ \
-p 5044:5044 docker.elastic.co/logstash/logstash:6.2.2

• Configure Filebeat to ship the Ballerina logs

i) Create a file named filebeat.yml with the following content

filebeat.prospectors:
- type: log
  paths:
    - /usr/share/filebeat/ballerina.log
output.logstash:
  hosts: ["logstash:5044"]  

NOTE : Modify the ownership of filebeat.yml file using $chmod go-w filebeat.yml

ii) Save the above filebeat.yml inside a directory named as {SAMPLE_ROOT}/filebeat

iii) Start the Logstash container, replace the {SAMPLE_ROOT} with your directory name

$ docker run -v {SAMPLE_ROOT}/filbeat/filebeat.yml:/usr/share/filebeat/filebeat.yml \
-v {SAMPLE_ROOT}/guide/api_gateway_service/ballerina.log:/usr/share\
/filebeat/ballerina.log --link logstash:logstash docker.elastic.co/beats/filebeat:6.2.2

• Access Kibana to visualize the logs using following URL

   http://localhost:5601