IoT Automotive Cloud Demo

Deploying the demo-iot-automotive-cloud with Rich Sensor Data Preview Feature

This README file provides a step-by-step guide for deploying the demo-iot-automotive-cloud project with the Rich Sensor Data Preview feature enabled. The guide assumes that you have basic knowledge of AWS, CDK, and Python.

Prerequisites

• For the deployment of the Grafana stack, Docker needs to be installed and running.
• Install venv with pip: pip install virtualenv
• Ensure your AWS accounts are fully allow-listed.
• All deployments are restricted to the regions where AWS IoT FleetWise is available.

Initial Setup

First, install the AWS CDK globally using npm (important not do this in the python venv!):

npm install -g aws-cdk

Make sure your AWS account and region are set up correctly and you have the appropriate keys exported.

Deploying the Yocto Image

Before deploying the main CDK app, navigate to the demo-iot-automotive-embeddedlinux-image repo and follow the README instructions there for creating the Yocto image. This will generate a yoctoSdkS3Path which will be used in a later step. You need to look up the S3 URI manually in S3 named: "nxpgoldboxbigapipeline-pipelineoutput***"

export YOCTO_SDK_S3_BUCKET=<s3 bucket name>

for example nxpgoldboxbigapipeline-demoartifactb63fbde0-bblb29a8xtuk

export YOCTO_SDK_SCRIPT_NAME=<Yocto sdk script name>

for example: fsl-auto-glibc-x86_64-cortexa53-crypto-toolchain-38.0.sh

Creating an S3 Bucket for the Build Artifacts

Create an S3 bucket for storing the aws-iot-fleetwise-edge code and rosbag2_rich_data_demo rich sensor data artifacts:

export FWE_RS_BUILD_ARTIFACTS_BUCKET=fwe-rs-build-artifacts-<yourId>-<yourRegion>
aws s3api create-bucket --bucket $FWE_RS_BUILD_ARTIFACTS_BUCKET --region <yourRegion> --create-bucket-configuration LocationConstraint=<yourRegion>

Downloading and Uploading Artifacts

Prepare the rosbag2_rich_data_demo.tar.bz2.

Upload these artifacts to the S3 bucket:

aws s3 cp rosbag2_rich_data_demo.tar.bz2 s3://$FWE_RS_BUILD_ARTIFACTS_BUCKET

Alternatively, follow the instructions here to get aws-iot-fleetwise-edge code and rosbag2_rich_data_demo.tar.bz2.

Clean Up if you previously used AWS IoT FleetWise in your AWS Account

If you previously registered your account with the FleetWise service, you need to delete the existing AWSServiceRoleForIoTFleetWise Role. Go to IAM in your account, find the Role AWSServiceRoleForIoTFleetWise and delete it. This will enable you to register for the Gamma service.

Set the FWE Config

Since FWE requires specific configuration based on the region and the environment it's running, we will need to configure it by first exporting the appropriate env variables and then generating the fwe-config.yaml:

export INTERFACE_NAME=vcan0
export ENDPOINT_URL=xxx-ats.iot.us-east-1.amazonaws.com
export THING_NAME=vCar
export TOPIC_PREFIX="\$aws/iotfleetwise/vehicles/$THING_NAME"
export CREDENTIALS_PROVIDER_ENDPOINT_URL=xxx.credentials.iot.us-east-1.amazonaws.com
export GG_TOKEN_EXCHANGE_ROLE_ALIAS=<GGTokenExchangeRoleAlias taken from the cloudformation>

sed -e "s/{INTERFACE_NAME}/$INTERFACE_NAME/g" \
    -e "s/{ENDPOINT_URL}/$ENDPOINT_URL/g" \
    -e "s/{THING_NAME}/$THING_NAME/g" \
    -e "s/{TOPIC_PREFIX}/$TOPIC_PREFIX/g" \
    -e "s/{GG_TOKEN_EXCHANGE_ROLE_ALIAS}/$GG_TOKEN_EXCHANGE_ROLE_ALIAS/g" \
    -e "s/{CREDENTIALS_PROVIDER_ENDPOINT_URL}/$CREDENTIALS_PROVIDER_ENDPOINT_URL/g" \
    greengrass_components/fleetwise_edge_connector/fwe-config.yaml.template > greengrass_components/fleetwise_edge_connector/fwe-config.yaml

To obtain the credentials provider endpoint, run:

aws iot describe-endpoint --endpoint-type iot:CredentialProvider

Deploying the Main CDK App with Additional Context

Finally, proceed to deploy the main CDK app using the following commands:

cd lib/cdk-aws-iotfleetwise
npm install
python3 -m venv .venv
source .venv/bin/activate
pip install -r ../../requirements.txt

# build the lib - needs to be done every time the lib changed!
npm run build
pip install dist/python/cdk-aws-iotfleetwise-0.0.0.tar.gz
cd ../../

# cdk bootstrap (needs to be done once)
cdk bootstrap -c s3FweArtifacts=$FWE_RS_BUILD_ARTIFACTS_BUCKET -c yoctoSdkS3Path=$YOCTO_SDK_S3_BUCKET -c yoctoSdkScriptName=$YOCTO_SDK_SCRIPT_NAME

# deploy API Gateway Endpoint stack
cdk deploy VisionVisualsStack -c s3FweArtifacts=$FWE_RS_BUILD_ARTIFACTS_BUCKET -c yoctoSdkS3Path=$YOCTO_SDK_S3_BUCKET -c yoctoSdkScriptName=$YOCTO_SDK_SCRIPT_NAME

# Create the Grafana Chart JSON file from the template, based on the API Gateway endpoint

export API_ENDPOINT_DOMAIN_NAME=xxx.execute-api.xxx.amazonaws.com
sed -e "s/{API_ENDPOINT_DOMAIN_NAME}/$API_ENDPOINT_DOMAIN_NAME/g" \
    grafana_dashboards/grafana-image/provisioning/dashboards/IndividualSignalAnalysis.json.template > grafana_dashboards/grafana-image/provisioning/dashboards/IndividualSignalAnalysis.json


# Verify that a file called IndividualSignalAnalysis.json.template was created in grafana_dashboards/grafana-image/provisioning/dashboards/

# deploy stack
cdk deploy --all --require-approval never -c s3FweArtifacts=$FWE_RS_BUILD_ARTIFACTS_BUCKET -c yoctoSdkS3Path=$YOCTO_SDK_S3_BUCKET -c yoctoSdkScriptName=$YOCTO_SDK_SCRIPT_NAME

Deploying the GG Components

After successful stack deployment, the Greengrass components are built by CodePipeline. When the onboarding of the device is successful, a deployment of those components needs to be executed:

# Prepare the environment
export AWS_ACCOUNT_ID=$(aws sts get-caller-identity --query 'Account' --output text)
export AWS_REGION=<your_region>
export THING_NAME=<your_thing_name>

envsubst < "./greengrass_components/deployment.json.template" > "./greengrass_components/deployment.json"

# Make sure to match the versions of the components (1.0.0 are defaults after the initial deployment)

aws greengrassv2 create-deployment --cli-input-json file://greengrass_components/deployment.json --region ${AWS_REGION}

Steps needed to create a new Lambda layer zip

If in need to work with a version of boto3 not yet supported by the Lambda runtime, you can use your desired boto3 SDK version with the following commands:

cd lib/cdk-aws-iotfleetwise
mkdir -p boto3-layer/python
pip3 install boto3 -t boto3-layer/python
cd boto3-layer
zip -r boto3-layer.zip .
rm -rf boto3-layer

Known issues

• The update operation is not implemented for all Custom Resources. So you can still experience failed updates, failed delete etc.
• This integration is still under heavy development. We will continue doing bug fixes and improvements.
• Not possible at the moment to update the fleetwise stack, need to manually delete biga-aws-iotfleetwise stack in CloudFormation, which will fail, mark to keep resources and delete again.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.