{"id":497,"date":"2019-03-15T10:18:04","date_gmt":"2019-03-15T09:18:04","guid":{"rendered":"http:\/\/blog.zhaw.ch\/splab\/?p=497"},"modified":"2019-03-15T16:37:57","modified_gmt":"2019-03-15T15:37:57","slug":"building-a-sample-mqtt-based-application-on-openwhisk","status":"publish","type":"post","link":"https:\/\/blog.zhaw.ch\/splab\/2019\/03\/15\/building-a-sample-mqtt-based-application-on-openwhisk\/","title":{"rendered":"Building a Sample MQTT-based Application on OpenWhisk"},"content":{"rendered":"\n

In two previous blog posts – here<\/a> and here<\/a> – we discussed our experience with deploying OpenWhisk on Kubernetes on OpenStack. As applied researchers at the Service Prototyping Lab, we are investigating potential use cases for such setups and for FaaS-based applications in general. In this blog post, we will therefore describe how we built a sample MQTT-based application that shows OpenWhisk in action for sensor data processing for future Internet of Things and smart dust scenarios.<\/p>\n\n\n\n

The basic idea of the application is that it consumes data from an MQTT feed, stores it in a database and provides a means to access the database via a web UI. The architecture of the application is shown in the figure below. The application is based on this blog post<\/a>.<\/p>\n\n\n\n

\"\"
Sample Application Architecture<\/figcaption><\/figure><\/div>\n\n\n\n\n\n\n\n

As can be seen from the figure, the motion sensor publishes messages to a specific topic. The trigger service provider subscribes to the same topic and fires OpenWhisk triggers that invoke the action addReadingToDb<\/code> that inserts each message to a CouchDB database. A user can point a browser at the renderHtml.js<\/code> web action which returns a HTML page to show the latest readings. Within the page, there\u2019s a JavaScript function that invokes the getLatestTenReadings<\/code> web action every 10 seconds to refresh the page.
<\/p>\n\n\n\n

The IoT motion sensor and the MQTT broker were provided by our friends at the Cloud Accounting and Billing Initiative<\/a> and were simply based on a Raspberry Pi with an attached motion sensor publishing to an MQTT broker. The motion sensor publishes a message to a specific topic ( lexxito<\/code> in this case) every time it detects motion. The simple message contains a JSON object with just two keys: time and status.<\/p>\n\n\n\n

We needed a persistent service that managed subscriptions from OpenWhisk trigger creations to topics and fired a trigger every time a new message was received. We used the service provider from the blog post mentioned above. However, we had to make some modifications to it as it assumed  Cloudant<\/a> – the IBM proprietary data store – as a backend. As we are using vanilla OpenWhisk, we needed an alternative and we decided to use CouchDB<\/a> instead. The modified code can be found here<\/a>.(We also found and fixed a bug with the remove_trigger<\/code> function in the feed_controller.js<\/code> file which threw an error every time we tried to delete a trigger).<\/p>\n\n\n\n

We then deployed a CouchDB instance on our Kubernetes cluster in a separate namespace using the Helm package manager following these instructions<\/a>. Next, we had to configure the CouchDB database so that it can be used by the service provider. To do that, we created a database in our CouchDB instance with the name topic_listeners<\/code> by running the following:
<\/p>\n\n\n\n

$ curl -X PUT \"http:\/\/username:password@COUCHDB_HOST:COUCHDB_PORT\/topic_listeners\"<\/code><\/pre>\n\n\n\n
This call returns the very informative response: <\/p>\n\n\n\n
{\"ok\":true}<\/code><\/pre>\n\n\n\n
Which indicates that the configuration of the database was successful.
<\/p>\n\n\n\n
Then, we needed to add some views to our database. Views<\/a> in CouchDB are used to query and filter documents. We created a file called views.json<\/a><\/code> and added it to CouchDB by running the following command:
<\/p>\n\n\n\n
$ curl -X PUT \"http:\/\/username:password@COUCHDB_HOST:COUCHDB_PORT\/topic_listeners\/_design\/subscriptions\" --data-binary @views.json<\/code><\/pre>\n\n\n\n
We had to create the readings<\/code> database that will be used by the addReadingToDb<\/code> action on CouchDB by running the following command:<\/p>\n\n\n\n
$ curl -X PUT \"http:\/\/username:password@COUCHDB_HOST:COUCHDB_PORT\/readings\"<\/code><\/pre>\n\n\n\n
Then, we were ready to deploy the service provider on our Kubernetes cluster by containerizing it first using the provided Dockerfile<\/a>, pushing the docker container to Docker Hub<\/a>, and then creating a deployment.yaml<\/a><\/code> file for it.
<\/p>\n\n\n\n
Then, we deployed the service provider by running:
<\/p>\n\n\n\n
$ kubectl apply -f deployment.yaml<\/code><\/pre>\n\n\n\n
And to expose the pod as a service, we ran:
<\/p>\n\n\n\n
$ kubectl expose pod mqtt-provider --port='3000' --type='NodePort'<\/code><\/pre>\n\n\n\n
With that, the service provider was now ready to accept trigger registrations.
<\/p>\n\n\n\n
We then turned our attention to configuring OpenWhisk to connect to the service provider in order to register triggers with it. To do that, we created a shared package under the \/whisk.system<\/code> namespace to make it accessible to all users, with the name mqtt<\/code> by running the following:<\/p>\n\n\n\n
$ wsk package create \\\n--shared yes \\\n-p provider_endpoint \"http:\/\/SERVICE_PROVIDER_HOST:SERVICE_PROVIDER_NODEPORT\/mqtt\" mqtt<\/code><\/pre>\n\n\n\n
And we added some description to the package:
<\/p>\n\n\n\n
$ wsk package update mqtt \\\n-a description 'The mqtt package provides functionality to connect to MQTT brokers'<\/code><\/pre>\n\n\n\n
Next, we created a feed action and associated it with the mqtt<\/code> package. A feed action is an action that manages the lifecycle of triggers. The code for the feed action used in our sample application can be found here<\/a>. 
<\/p>\n\n\n\n
The feed action will take care of creating and removing triggers. This means that when a user would like to create a trigger, i.e. subscribe to a specific topic on an MQTT broker and fire triggers whenever a new message is published on the topic, the feed action will send a request to the service provider in order to register the trigger with the specific topic on the MQTT broker.
<\/p>\n\n\n\n
We added the feed action to the mqtt<\/code> package by running the following command:
<\/p>\n\n\n\n
$ wsk action create -a feed true mqtt\/mqtt_feed feed_action.js<\/code><\/pre>\n\n\n\n
Once we had the feed action configured, we were able to associate a trigger with the lexxito<\/code> topic on the MQTT broker. To do that, we ran the following command:<\/p>\n\n\n\n
$ wsk trigger create \/guest\/feed_trigger \\\n--feed \/whisk.system\/mqtt\/mqtt_feed \\\n-p topic 'lexxito' \\\n-p url 'mqtt:\/\/mqtt.demonstrator.info' \\\n-p authKey $WHISK_GUEST_AUTH \\\n-p triggerName '\/guest\/feed_trigger'<\/code><\/pre>\n\n\n\n
Next, we created the action addReadingToDb<\/code> that will insert each message to the CouchDB database. The code for the action can be viewed here<\/a>.
<\/p>\n\n\n\n
The addReadingToDb<\/code> action is a NodeJS package that used the sync-request<\/a><\/code> NPM module to perform a POST request to the readings database on CouchDB. This was achieved by following the instructions from this<\/a> blog post on how to package NPM dependencies for OpenWhisk actions.
<\/p>\n\n\n\n
Next, we added the AddReadingToDb<\/code> action to OpenWhisk by running the following command:
<\/p>\n\n\n\n
$ wsk action create addReadingToDb \\\n--kind nodejs:default addReadingToDb.zip<\/code><\/pre>\n\n\n\n
Next, we had to create an OpenWhisk rule that connected the feed_trigger<\/code> to the addReadingToDb<\/code> action so that every time the feed_trigger<\/code> is fired, the addReadingToDb<\/code> action gets invoked. An OpenWhisk rule associates a trigger with an action, invoking the action when the associated trigger is fired.
<\/p>\n\n\n\n
To create the rule, we ran the following:
<\/p>\n\n\n\n
$ wsk rule create mqttRule \/guest\/feed_trigger addReadingToDb<\/code><\/pre>\n\n\n\n
Now every time a new message is published on the topic lexxito<\/code>, a trigger is fired by the trigger service provider carrying with it the contents of the message to the addReadingToDb<\/code> action. The action will then be invoked and will add the contents of the message to the readings<\/code> database.
<\/p>\n\n\n\n
The UI<\/strong><\/h2>\n\n\n\n
We then turned our attention to the user-facing component of our sample application.
<\/p>\n\n\n\n
We wanted to serve static content within OpenWhisk without using any external services like GitHub Pages, for example. Since OpenWhisk doesn\u2019t provide a convenient way to serve static content, we looked into using OpenWhisk web actions to return a HTML page.
<\/p>\n\n\n\n
An OpenWhisk web action is an action that\u2019s accessible via REST API without needing credentials nor the OpenWhisk CLI. That is, upon the creation of a web action, a URL is created for it that can be hit to invoke the web action.
<\/p>\n\n\n\n
We created a web action, renderHtml.js<\/code> that returns a HTML page to show the latest readings from the readings<\/code> database. The code for the renderHtml.js<\/code> action can be viewed here<\/a>.
<\/p>\n\n\n\n
To create the renderHtml.js<\/code> web action, we ran the following command:
<\/p>\n\n\n\n
$ wsk action create renderHtml renderHtml.js --web true<\/code><\/pre>\n\n\n\n
Within the HTML code that renderHtml.js<\/code> returns, there\u2019s a JavaScript script that invokes another web action, getLatestTenReadings<\/code>, every ten seconds in order to refresh the page. The getLatestTenReadings<\/code> web action queries the readings<\/code> database and returns the ten most-recent entries in the readings<\/code> database.
<\/p>\n\n\n\n
The code for getLatestReadings<\/code> can be viewed here<\/a>.
<\/p>\n\n\n\n
Similar to the addReadingToDb<\/code> action, this is a NodeJS package that uses the sync-request<\/code> NPM module to retrieve the ten most-recent entries from the readings database.
<\/p>\n\n\n\n
We created the getLatestTenReadings<\/code> web action by running the following command:<\/p>\n\n\n\n
$ wsk action create getLatestTenReadings \\\n--kind nodejs:default getLatestTenReadings.zip \\\n--web true<\/code><\/pre>\n\n\n\n
And we got the URL to getLatestTenReadings<\/code> by running the following:<\/p>\n\n\n\n
$ wsk action get getLatestTenReadings --url<\/code><\/pre>\n\n\n\n
We got the URL to the renderHtml<\/code> web action by running the following:
<\/p>\n\n\n\n
$ wsk action get renderHtml --url<\/code><\/pre>\n\n\n\n
Finally, by pointing the browser at this endpoint, the dynamic MQTT data should be visible.
<\/p>\n\n\n\n
Lessons Learnt<\/h2>\n\n\n\n
Getting a basic application running on OpenWhisk that uses a custom external feed, requires database support, and serves static content is not a trivial task. Perhaps some of the issues that we faced are addressed in commercial variants of OpenWhisk, but the developer experience of getting a simple app operational on vanilla OpenWhisk is not so straightforward for what is touted to be a very developer-oriented platform.
<\/p>\n\n\n\n
Nonetheless, OpenWhisk remains an exciting platform with a lot of potential. But, from our experience, there is still too much friction associated with getting a basic application running.
<\/p>\n
Schlagw\u00f6rter: faas<\/a>, howto<\/a>, iot<\/a>, mqtt<\/a>, openwhisk<\/a>, sensors<\/a>, serverless<\/a>
<\/div>","protected":false},"excerpt":{"rendered":"
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