Running the Application in the Sandbox

Now that we have the application code implemented, let’s build the application and exercise its functionality locally without requiring deploying it in a cluster.

Run the Streamlets Locally

The sbt runLocal command allows you to run your application on your local machine without a Kubernetes cluster.

  1. From the sbt shell, invoke runLocal:

    You should see output similar to the following:

sbt:sensor-data> runLocal
[info] Streamlet 'sensordata.SensorDataToMetrics' found
[info] Streamlet 'sensordata.MetricsValidation' found
[info] Streamlet 'sensordata.SensorDataHttpIngress' found
[info] Streamlet 'sensordata.ValidMetricLogger' found
[info] Streamlet 'sensordata.InvalidMetricLogger' found
[success] /path/to/sensor-data/src/main/blueprint/blueprint.conf verified.

                 │   │
                 │   └───────┐
                 │           │
                 v           v
 ┌─────────────────┐ ┌───────────────┐
 │[invalid-metrics]│ │[valid-metrics]│
 └────────┬────────┘ └─────┬─────────┘
          │                │
          v                v
  ┌──────────────┐  ┌────────────┐
  │invalid-logger│  │valid-logger│
  └──────────────┘  └────────────┘
---------------------------- Streamlets per project ----------------------------
 sensor-data-scala - output file: file:/tmp/cloudflow-local-run3239069643364862589/sensor-data-scala-local.log

	http-ingress [sensordata.SensorDataHttpIngress]
	- HTTP port [3000]
	invalid-logger [sensordata.InvalidMetricLogger]
	metrics [sensordata.SensorDataToMetrics]
	valid-logger [sensordata.ValidMetricLogger]
	validation [sensordata.MetricsValidation]


------------------------------------ Topics ------------------------------------

----------------------------- Local Configuration -----------------------------
Using Sandbox local configuration file: src/main/resources/local.conf

------------------------------------ Output ------------------------------------
Pipeline log output available in folder: /tmp/cloudflow-local-run3239069643364862589

Running sensor-data-scala
To terminate, press [ENTER]

While the application is running in this local mode, it’s possible to exercise all its interfaces and observe the output written by the streamlets logging or standard output.

The line sensor-data-scala - output file: <path-to-temp-file> indicates the location of the captured output. You can follow the output using command line utilities (tail) or a text editor that support live updates (e.g. sublime text)

We can also appreciate that the ingress streamlet is reachable on the TCP port 3000.

http-ingress [sensordata.SensorDataHttpIngress]
	- HTTP port [3000]

You can send data to this port to exercise the pipeline. To make this easy, we include a script that takes a sample dataset from the test-data/ directory and sends it record-by-record to the HTTP ingress port for processing.

You should see an output similar to this:

$ ./
Sending {"deviceId":"c75cb448-df0e-4692-8e06-0321b7703992","timestamp":1495545646279,"measurements":{"power":1.7,"rotorSpeed":3.9,"windSpeed":105.9}}
HTTP/1.1 202 Accepted
Server: akka-http/10.1.11
Date: Wed, 10 Jun 2020 18:11:18 GMT
Content-Type: text/plain; charset=UTF-8
Content-Length: 88

The request has been accepted for processing, but the processing has not been completed

You can then observe the results by inspecting the output file of the application, as explained above. In the <path-to-temp-file, you should see output similar to this:

[INFO] [06/10/2020 20:21:34.400] [] [] valid-logger {"deviceId": "c75cb448-df0e-4692-8e06-0321b7703992", "timestamp": 1495545646279, "name": "windSpeed", "value": 105.9}

When you are done experimenting with the running application, you can stop it by pressing ENTER

Running sensor-data-scala
To terminate, press [ENTER]

[info] Attempting to terminate local application

What’s next

Now, we are ready to Set up a Kubernetes cluster.