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Using the EI Analytics Portal

Let's use EI Analytics to view and monitor statistics and message tracing.

You can monitor the following statistics and more through the EI Analytics portal:

  • Request Count
  • Overall TPS
  • Overall Message Count
  • Top Proxy Services by Request Count
  • Top APIs by Request Count
  • Top Endpoints by Request Count
  • Top Inbound Endpoints by Request Count
  • Top Sequences by Request Count


Monitoring the usage of the integration runtime using statistical information is very important for understanding the overall health of a system that runs in production. Statistical data helps to do proper capacity planning, to keep the runtimes in a healthy state, and for debugging and troubleshooting problems. When it comes to troubleshooting, the ability to trace messages that pass through the mediation flows of the Micro Integrator is very useful.

Before you begin

  • Set up the EI Analytics deployment.
  • Note the following server directories in your deployment.

    EI_ANALYTICS_HOME This is the root folder of your EI Analytics installation.
    EI_7.1.0_HOME This is the root folder of your EI 7.1.0 installation.

Starting the servers

Let's start the servers in the given order.

Starting the Analytics Server


Be sure to start the Analytics server before starting the Micro Integrator.

  1. Open a terminal and navigate to the <EI_ANALYTICS_HOME>/bin directory.
  2. Start the Analytics server by executing the following command:


Starting the Micro Integrator

Once you have started the Analytics Server, you can start the Micro Integrator.

Starting the Analytics Portal

  1. Open a terminal and navigate to the <EI_ANALYTICS_HOME>/bin directory.
  2. Start the Analytics Portal's runtime by executing the following command:


In a new browser window or tab, open the Analytics portal using the following URL: https://localhost:9645/analytics-dashboard. Use admin for both the username and password.

Publishing statistics to the Portal

Let's test this solution by running the service chaining tutorial. When the artifacts deployed in the Micro Integrator are invoked, the statistics will be available in the portal.

Follow the steps given below.

Step 1: Deploy integration artifacts

If you have already started the Micro Integrator server, let's deploy the artifacts. Let's use the integration artifacts from the service chaining tutorial.

  1. Download the CAR file.
  2. Copy the CAR file to the <MI_HOME>/repository/deployment/server/carbonapps/ directory.
Step 2: Start the backend

Let's start the hospital service that serves as the backend to the service chaining use case:

  1. Download the JAR file of the back-end service from here.
  2. Open a terminal, navigate to the location where your saved the back-end service.
  3. Execute the following command to start the service:
    java -jar Hospital-Service-JDK11-2.0.0.jar
Step 3: Sending messages

Let's send 8 requests to the Micro Integrator to invoke the integration artifacts:


For the purpose of demonstrating how successful messages and message failures are illustrated in the portal, let's send 2 of the requests while the back-end service is not running. This should generate a success rate of 75%.

  1. Create a JSON file called request.json with the following request payload.

        "name": "John Doe",
        "dob": "1940-03-19",
        "ssn": "234-23-525",
        "address": "California",
        "phone": "8770586755",
        "email": "[email protected]",
        "doctor": "thomas collins",
        "hospital": "grand oak community hospital",
        "cardNo": "7844481124110331",
        "appointment_date": "2025-04-02"

  2. Open a command line terminal and execute the following command (six times) from the location where you save the request.json file:

    curl -v -X POST --data @request.json http://localhost:8290/healthcare/categories/surgery/reserve --header "Content-Type:application/json"
    If the messages are sent successfully, you will receive the following response for each request.
        "appointmentNo": 1,
        "doctorName": "thomas collins",
        "patient": "John Doe",
        "actualFee": 7000.0,
        "discount": 20,
        "discounted": 5600.0,
        "paymentID": "e1a72a33-31f2-46dc-ae7d-a14a486efc00",
        "status": "Settled"

  3. Now, shut down the back-end service and send two more requests.

Viewing the Analytics Portal

Once you have signed in to the analytics portal server, click the Enterprise Integrator Analytics icon shown below to open the portal.

Opening the Analytics dashboard for WSO2 EI

Statistics overview

View the statistics overview for all the integration artifacts that have published statistics:

ESB total request count

Transactions per second

The number of transactions handled by the Micro Integrator per second is mapped on a graph as follows.

ESB overall TPS

Overall message count

The success rate and the failure rate of the messages received by the Micro Integrator during the last hour are mapped in a graph as follows.

ESB overall message count

Top APIs by request

The HealthcareAPI REST API is displayed under TOP APIS BY REQUEST COUNT as follows.

Top APIs by request count

Endpoints by request

The three endpoints used for the message mediation are displayed under Top Endpoints by Request Count as shown below.

Top endpoints by request count

Per API requests

In the Top APIS BY Request COUNT gadget, click HealthcareAPI to open the OVERVIEW/API/HealthcareAPI page. The following is displayed.

  • The API Request Count gadget shows the total number of requests handled by the StockQuoteAPI REST API during the last hour:
    Total request per API
  • The API Message Count gadget maps the number of successful messages as well as failed messages at different times within the last hour in a graph as shown below.
    API message count
  • The API Message Latency gadget shows the speed with which the messages are processed by mapping the amount of time taken per message at different times within the last hour as shown below.
    API message latency
  • The Messages gadget lists all the the messages handled by the StockQuoteAPI REST API during the last hour with the following property details as follows.
    Message per API
  • The Message Flow gadget illustrates the order in which the messages handled by the StockQuoteAPI REST API within the last hour passed through all the mediation sequences, mediators and endpoints that were included in the message flow as shown below.
    Message flow per API

Per Endpoint requests

In the Top Endpoints by Request Count gadget, click one of the endpoints to view simillar statistics per endpoint.

  • ChannelingFeeEP
  • SettlePaymentEP
  • GrandOaksEP

You can also navigate to any of the artifacts by using the top-left menu as shown below. For example, to view the statistics of a specific endpoint, click Endpoint and search for the required endpoint.

Dashboard navigation menu

Message tracing

When you go to the Analytics portal the message details will be logged as follows:

Message tracing per API