MISC-TN-005: Running AWS Greengrass Core on SBCSPG

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SBCSPG-1.jpg Applies to SBCSPG
Cloud-computing-banner.jpg Applies to IoT
Warning-icon.png This technical note was validated against specific versions of hardware and software. It may not work with other versions. Warning-icon.png

History[edit | edit source]

Version Date Notes
1.0.0 August 2019 First public release

Introduction[edit | edit source]

In these days, we are witnessing the cloud war. Almost every week, the top three cloud providers⁠—Amazon, Microsoft, and Google⁠—add new services and new functionalities.

Technically speaking, it is hard to determine which platform is the best. Although basic services are similar, each platform has different peculiarities that make it more or less suitable for a specific application.

With regard to IoT applications, all major cloud platforms provide advanced services. Of course, (Industrial) IoT is a typical scenario in which DAVE Embedded Systems' products are used.

In principle, DAVE Embedded Systems' products are designed to be cloud-agnostic in order to let the users the freedom to choose the cloud platform they think best fits their needs.

This Technical Note, for instance, shows how to interface the SBCSPG Industrial IoT gateway to Amazon Web Services (AWS) by using Greengrass service. Specifically, this document shows how to configure and run the AWS Greengrass Core software (GGC) on the SBCSPG. According to AWS website, AWS IoT Greengrass is

software that lets you run local compute, messaging, data caching, sync, and ML inference capabilities on connected devices in a secure way. With AWS IoT Greengrass, connected devices can run AWS Lambda functions, execute predictions based on machine learning models, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet.

AWS IoT Greengrass seamlessly extends AWS to devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. With AWS IoT Greengrass, you can use familiar languages and programming models to create your device software in the cloud, and then deploy it to your devices. AWS IoT Greengrass can be programmed to filter device data and only transmit necessary information back to the cloud.

In other words, Greengrass allows you to implement edge computing functionalities easily and quickly by deploying them on the edge device through the AWS platform. The following is a short clip that illustrates well the concept of Greengrass.

Getting Started with AWS Greengrass

It is worth remembering that edge computing means a distributed computing paradigm which brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth, according to Wikipedia.

Cloud and Edge computing in a typical IIoT scenario (image source: [1])

Within the processing power limits of the edge device, moving such computations to the edge can be an effective way to optimize costs. When the Internet connection is intermittent or poor, it may even be mandatory to meet system's requirements. Generally speaking, when implementing an IoT system, balancing between cloud computing and edge computing is one of the most important issues the system architect has to address.

It should be stressed that this Technical Note is not a step-by-step guide to set up the edge device and the cloud platform to implement a Greengrass-based system. AWS documentation is rich and detailed in this regard. Rather, this document aims to underline some specific SBCSPG-related steps required to run GGC on this device successfully. The procedure is based on the Getting Started with AWS IoT Greengrass guide, which is, therefore, a recommended reading.

The test was performed with:

  • Linux kernel 4.1.15-rialto-1.1.3
  • Debian Stretch distribution (for more details, please see this Technical Note)
  • AWS IoT Greengrass Core 1.9.2.

Setting up the edge device[edit | edit source]

The first thing to do was to rebuild the Linux kernel after adding the missing options⁠ required by GGC, which are detailed here.

Once the device was up and running with the fresh Linux kernel, to enable IP routing to the Internet, the default gateway was setup like this:

root@sbcspg:~# route add default gw eth0

/etc/resolv.conf was edited to add a typical DNS entry:

root@sbcspg:~# cat /etc/resolv.conf

Then, the root file system had to be configured according to the requirements described here.

AWS documentation was a little bit confusing about the Node.JS and Java requirements. Both were installed, just in case. With regard to Java, OpenJDK 1.8.0 was installed.

The following guides were useful to install some of the required packages:

To setup cgroups, this script was used.

Finally, a couple of file system setting had to be tuned, too. They are hardlink and softlink protections. For more details about these settings, please refer to the following links:

Finally, the recommended certificate was installed

sudo wget -O root.ca.pem https://www.amazontrust.com/repository/AmazonRootCA1.pem

To verify that the device is setup properly, it is recommended to use the dependency checker script provided by AWS itself. The following image shows the output of the checker executed on SBCSPG after completing the configuration.

Output of the GGC dependencies checker

As shown, only one check is highlighted, which refers to the kernel version. To run GGC 1.9.2, it is recommended a 4.4 kernel version or later. Although checker's report didn't warn about the use of containers, we verified that GGC couldn't work on top of SBCSPG's 4.1.15 Linux kernel. Because a newer kernel was not available for SBCSPG at the time of this writing, to work around this issue, the default Lamba functions containerization was disabled.

In order to make the checker happy, two symbolic links were created as well:

lrwxrwxrwx 1 root root  4 Jul 30 16:50 /usr/bin/java8 -> java
lrwxrwxrwx 1 root root  6 Jul 30 16:52 /usr/bin/nodejs8.10 -> nodejs

Configuring AWS Greengrass on the cloud side and installing GGC on the edge device[edit | edit source]

Module 2 of the Getting started guide details how to setup the Greengrass service on the cloud side.

Once created the group, disable the default Lamba functions containerization, as stated previously.

At the end of this step, a file has to be downloaded containing Core's security resources, which will be installed on the edge device. This archive also contains configuration information specific to your AWS IoT Greengrass core and the AWS IoT endpoint, stored in the file config.json. After uncompressing it onto the SBCSPG, please verify that the useSystemd in config.json is set to yes.

If everything is configured properly, after staring Greengrass Core daemon, the following messages are logged into the /greengrass/ggc/var/log/system/runtime.log file:

[2019-08-07T11:41:01.127+02:00][INFO]-Greengrass Version: 1.9.2-RC4
[2019-08-07T11:41:01.127+02:00][INFO]-Greengrass Root: /greengrass
[2019-08-07T11:41:01.127+02:00][INFO]-Greengrass Write Directory: /greengrass/ggc
[2019-08-07T11:41:01.127+02:00][INFO]-Group File Directory: /greengrass/ggc/deployment/group
[2019-08-07T11:41:01.127+02:00][INFO]-Default Lambda UID: 109
[2019-08-07T11:41:01.127+02:00][INFO]-Default Lambda GID: 114
[2019-08-07T11:41:01.131+02:00][INFO]-The current core is using the AWS IoT certificates with fingerprint.	{"fingerprint": "3805f49f1af9e764b3ae8ca87f8ec43d7b94d1e3f05494fa166f6d3abbe14015"}
[2019-08-07T11:41:01.133+02:00][INFO]-Will persist worker process info.	{"dir": "/greengrass/ggc/packages/1.9.2/var/worker/processes"}
[2019-08-07T11:41:01.135+02:00][INFO]-Will persist worker process info.	{"dir": "/greengrass/ggc/packages/1.9.2/var/worker/processes"}
[2019-08-07T11:41:01.14+02:00][INFO]-Subscription added to the system	{"source": "arn:aws:lambda:us-east-2:504613037555:function:Greengrass_HelloWorld:1", "sourceType": 0, "subject": "hello/world", "target": "cloud", "targetType": 2}
[2019-08-07T11:41:01.155+02:00][INFO]-The current core is using the AWS IoT certificates with fingerprint.	{"fingerprint": "3805f49f1af9e764b3ae8ca87f8ec43d7b94d1e3f05494fa166f6d3abbe14015"}
[2019-08-07T11:41:01.171+02:00][INFO]-No proxy URL found.
[2019-08-07T11:41:01.213+02:00][INFO]-Started Deployment Agent to listen for updates.
[2019-08-07T11:41:01.22+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGDeviceCertificateManager", "workerId": "7c195254-cd25-4389-75d4-267b9cbd5bd7", "pid": 1600}
[2019-08-07T11:41:01.224+02:00][INFO]-Connecting with MQTT.	{"endpoint": "a15axy3tr9fuwq-ats.iot.us-east-2.amazonaws.com:8883", "clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:01.495+02:00][WARN]-[5]GK Remote: Error retrieving public key data: ErrPrincipalNotConfigured: private key for MqttCertificate is not set
[2019-08-07T11:41:01.595+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGIPDetector:1", "workerId": "ff88e76a-9ca4-459f-7e20-689800240635", "pid": 1614}
[2019-08-07T11:41:02.057+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGConnManager", "workerId": "7e719557-11c0-4e47-4532-1d9eb06129fd", "pid": 1625}
[2019-08-07T11:41:02.329+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGCloudSpooler:1", "workerId": "8ae31447-0295-4ae8-450a-872305ce315b", "pid": 1636}
[2019-08-07T11:41:02.338+02:00][WARN]-[5]GK Remote: Error retrieving public key data: ErrPrincipalNotConfigured: private key for MqttCertificate is not set
[2019-08-07T11:41:02.428+02:00][INFO]-MQTT connection successful.	{"attemptId": "uIzF", "clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:02.428+02:00][INFO]-MQTT connection established.	{"endpoint": "a15axy3tr9fuwq-ats.iot.us-east-2.amazonaws.com:8883", "clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:02.429+02:00][INFO]-MQTT connection connected. Start subscribing.	{"clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:02.429+02:00][INFO]-Deployment agent connected to cloud.

Deploying the test Lambda function to the edge device[edit | edit source]

Module 3 (Part 1) of the Getting started guide shows hot to deploy a Lamba function⁠—which was created on the cloud⁠—to the edge device. This function, coded in Python, simply sends a "Hello, world!" message to the cloud at regular intervals.

Testing the execution of the Lambda function on the edge device[edit | edit source]

Once the function has been deployed, on the edge device the following messages appear in the runtime.log file.

[2019-08-07T11:41:02.43+02:00][INFO]-Start subscribing.	{"numOfTopics": 2, "clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:02.43+02:00][INFO]-Trying to subscribe to topic $aws/things/SBCSPG_grp0_Core-gda/shadow/update/delta
[2019-08-07T11:41:02.6+02:00][INFO]-Trying to subscribe to topic $aws/things/SBCSPG_grp0_Core-gda/shadow/get/accepted
[2019-08-07T11:41:02.89+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGTES", "workerId": "ed4e9532-696d-41a2-77e8-96f5226f8138", "pid": 1646}
[2019-08-07T11:41:02.933+02:00][INFO]-All topics subscribed.	{"clientId": "SBCSPG_grp0_Core"}
[2019-08-07T11:41:03.306+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGShadowService", "workerId": "d22b0689-28bc-472c-5637-dc67d673cb76", "pid": 1658}
[2019-08-07T11:41:03.708+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGShadowSyncManager", "workerId": "9783bd15-4674-41ee-6578-653bfeef2cd3", "pid": 1668}
[2019-08-07T11:41:04.098+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:::function:GGSecretManager:1", "workerId": "d0ef6e38-e19c-4e1f-6e16-1a82ccd115fa", "pid": 1680}
[2019-08-07T11:41:04.328+02:00][INFO]-Started all system components.
[2019-08-07T11:41:04.37+02:00][INFO]-Created worker.	{"functionArn": "arn:aws:lambda:us-east-2:504613037555:function:Greengrass_HelloWorld:1", "workerId": "373c16da-f79a-44b1-7640-7ca327d730ef", "pid": 1691}
[2019-08-07T11:41:05.963+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:11.004+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:16.036+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:21.074+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:26.116+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:31.151+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:36.186+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:41.23+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:46.278+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:51.322+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:41:56.359+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:01.399+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:06.441+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:11.481+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:16.522+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:21.57+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:26.612+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:31.656+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:36.705+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:41.742+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:46.787+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""}
[2019-08-07T11:42:51.828+02:00][INFO]-Handled functions request.	{"functionName": "arn:aws:lambda:::function:GGRouter", "invocationId": ""} 

On the cloud, the log of the received messages looked like this:

Received messages on the cloud