Recently I switched my Cat Feeder project's IaC to AWS CDK in favour of increasing my focus and productivity on building and iterating, rather than constantly mucking around with infrastructure everytime I resume my project after a break; which is rare and far between these days.

Just as with coding IoT microcontrollers such as the ESP32s, I want to get straight back into building every opportunity I get; so I am also switching away from Arduino based microcontroller development written in C++ - I don't have a background in C++ and to be honest this is the aspect I struggled with the most because I tend to forget things after not touching it for 6 months or so.

So I am switching to MicroPython to develop the logic for all my IoT devices going forward, this means I get to use Python - a programming lanaguge I work with frequently so there is less chance of me being forgetful when I use it at least once a month. MicroPython is a lean and efficient implementation of the Python 3 programming language that includes a subset of the Python standard library and is optimized to run on microcontrollers and in constrained environments - a good fit for IoT devices such as the ESP32!

What about all the Arduino hardware and components I already invested in?

Good news is MircoPython is supported on all ESP32 devices - based on the ones I myself have purchased; all I need to do to each ESP32 device is to flash it with a firmware - if you are impatient, you can scroll down and skip to below to the flashing the firmware section. When I first started Arduino, MicroPython was available to use, but that was 2 years ago and there were not as many good blog and tutorial content out there as there is today; I couldn't at the time work out how to control components such as sensors, servos and motors as well as I could with C++ based coding using Arduino; nowdays there are way more content to learn off and I've learnt (by PoCing individual components) enough to switch to MicroPython. As far as I understand it, any components you have for Arduino can be used in MicroPython, provided that there is a library out there that supports it, if there isn't then you can always write your own!

What's covered in this blog?

By the end of this blog, you will be able to send and receive MQTT messages from AWS IoT core using MicroPython, I will also cover the steps involved in flashing a MicroPython firmware image onto an ESP32C3. Although this blog has a focus and example on using an ESP32, this example can be applied to any micro-controllers of any brand or flavours, provided the micro-controller you are using supports MicroPython.

Flashing the MicroPython firmware onto a Seeed Studio XIAO ESP32C3

The following instructions works for any generic ESP32C3 devices!

Download the latest firmware from micropython.org​

https://micropython.org/download/ESP32_GENERIC_C3/

Next, I connected my ESP32C3 to my Mac and ran the following command to find the name of the device port

 /dev/ttyUSB0

My ESP32C3 is named "/dev/tty.usbmodem142401", the name for your ESP32C3 may be different.

Next, install esptool onto your computer, then run the following commands to flash the MicroPython firmware onto the ESP32C3 using the bin file you've just downloaded.

esptool.py --chip esp32c3 --port /dev/tty.usbmodem142401 erase_flash

esptool.py --chip esp32c3 --port /dev/tty.usbmodem142401 --baud 460800 write_flash -z 0x0 ESP32_GENERIC_C3-20240105-v1.22.1.bin

It should look something like this when you run the commands.

Install Thonny and run it. Then go to Tools -> Options, to configure the ESP32C3 device in Thonny to match the settings shown in the screenshot below.

If everything went well, you should see these 2 sections in Thonny: "MicroPython Device" and "Shell", if not then try clicking on the Stop button in the top menu.

AWS IoT Core Certificates and Keys​

In order to send MQTT messages to an AWS IoT Core Topic, or to receive a message from a Topic in reverse, you will need a set of Certificate and Key\s for your micro-controller; as well as the AWS IoT Endpoint specific to your AWS Account and Region.

It's great if you have those with you so you can skip to the next section, if not, do not worry I've got you covered. In a past blog I have a reference architecture accompanied by a GitHub repository on how to deploy resources for an AWS IoT Core solution using AWS CDK, follow that blog to the end and you will have a set of Certificate and Key to use for this MicroPython example; the CDK Stack will deploy all the neccessary resources and policies in AWS IoT Core to enable you to both send and receive MQTT messages to two separate IoT Topics.

Reference AWS IoT Core Architecture: https://chiwaichan.co.nz/blog/2024/02/02/feedmyfurbabies-i-am-switching-to-aws-cdk/

Upload the MicroPython Code to your device​

Now lets upload the MicroPython code to your micro-controller and prepare the IoT Certificate and Key so we can use it to authenticate the micro-controller to enable it to send and receive MQTT messages between your micro-controller and IoT Core.

Clone my GitHub repository that contains the MicroPython example code to publish and receive MQTT message with AWS IoT Core: https://github.com/chiwaichan/feedmyfurbabies-micropython-iot

It should look something like this.

Copy your Certificate and Key into the respective files shown in the above screenshot; otherwise, if you are using the Certificate and Key from my reference architecture, then you should use the 2 Systems Manager Parameter Store values create by the CDK Stack.

Next we convert the Certificate and Key to DER format - converting the files to DER format turns it into a binary format and makes the files more compact, especially neccessary when we run use it on small devices like the ESP32s.

In a terminal go to the certs directory and run the following commands to convert the certificate.pem and private.key files into DER format.

openssl rsa -in private.key -out key.der -outform DER
openssl x509 -in certificate.pem -out cert.der -outform DER

You should see two new files with the DER extension appear in the directory if all goes well; if not, you probably need to install openssl.

In Thonny, in the Files explorer, navigate to the GitHub repository's Root directory and open the main.py file. Fill in the values for the variables shown in the screenshot below to match your environment, if you are using my AWS CDK IoT referenece architecture then you are only required to fill in the WIFI details and the AWS IoT Endpoint specific to your AWS Account and Region.

Select both the certs folder and main.py in the Files explorer, then right click and select "Upload to /" to upload the code to your micro-controller; the files will appear in the "MicroPython Device" file explorer.

This is the moment we've been waiting for, lets run the main.py Python script by clicking on the Play Icon in green.

If all goes well you should see some output in the Shell section of Thonny.

The code in the main.py file has a piece of code that is generating a random number for the food_capacity percentage property in the MQTT message; you can customise the message to fit your use case.

But lets verify it is actually received by AWS IoT Core.

Alright, lets go the other way and see if we can receive MQTT messages from AWS IoT Core using the other Topic called "cat-feeder/action" we subscribed to in the MicroPython code.

Lets go back the AWS Console and use the MQTT test client to publish a message.

In the Thonny Shell we can see the message "Hello from AWS IoT console" sent from the AWS IoT Core side and it being received by the micro-controller.

In a previous blog I talked about switching from CloudFormation template to AWS CDK as my preference for infrastructure as code, for provisioning my AWS Core IoT resources; I mentioned at the time whilst using resources using AWS CDK, as it would improve my productivity to focus on iterating and building. Although I switched to CDK for the reasons I described in my previous blog, there are some CloudFormation limitations that cannot be addressed just by switching to CDK alone.

In this blog I will talk about CloudFormation Custom Resources:

• What are CloudFormation Custom Resources?
• What is the problem I am trying to solve?
• How will I solve it?
• How am I using Custom Resources with AWS CDK?

CloudFormation Custom Resources allows you to write custom logic using AWS Lambda functions to provision resources, whether these resources live in AWS (you might ask why not just use CloudFormation or CDK: keep reading), on-premise or in other public clouds. These Custom Resource Lambda functions configured within a CloudFormation template, and are hooked into a CloudFormation Stack's lifecycle during the create, update and delete phases - to allow these lifecycle stages to happen, the logic must be implemented into the Lambda function's code.

What is the problem I am trying to solve?

In my AWS IoT Core reference architecture, it relies on use of two sets of certificates and private keys; they are used to authenticate each Thing devices connecting to AWS IoT Core - this ensures that only trusted devices can establish a connection.

In the CloudFormation template version of my reference architecture, I had in the deployement instructions to manually create 2 Cetificates in the AWS Console for the IoT Core service, this is because CloudFormation doesn't directly support creation of certificates for AWS IoT Core; as shown in the screenshot below.

There is nothing wrong with creating the certificates manually within the AWS Console when you are trying out my example for the purpose of learning, but it would best to be able to deploy an entire set of resources using infrastructure as code, so we can achieve consistent repeatable deployments with as minimal effort as possible. If you are someone completely new to AWS, coding and IoT, my deployment instructions would be very overwheling and the chances of you successfully deploying a fully functional example will be very unlikely.

How will I solve it?

If you got this far and actually read what was written up to this point, you probably would have guess the solution is Custom Resources: so lets talk about how the problem described above was solved.

So we know Custom Resources is part of the solution, but one important thing we need to understand is that, even though there isn't the ability to create the certificates directly using CloudFormation, but there is support for creating the certificates using the AWS SDK Boto3 Python library: create_keys_and_certificate.

So essentially, we are able create the AWS IoT Core certificates using CloudFormation (in an indirectly way) but it requires the help of Custom Reources (a Lambda function) and the AWS Boto3 Python SDK.

The Python code below is what I have in the Custom Resource Lambada function, it demonstrates the use of the Boto3 SDK to create the AWS IoT Core Certificates; and as a bonus, I am leveraging the Lambda function to save the Certificates into the AWS Systems Manager Parameter Store, this makes it much more simplier by centralising the Certificates in a single location without the engineer deploying this reference architecture having to manually copying/pasting/managing the Certificates - as I have forced readers in my original version of this reference architecture deployment. The code below also manages the lifecycle of the Certificates as the CloudFormation Stacks are deleted, by deleting the Certificates it created during the create phase of the lifecycle.

The overall flow to create the certificates is: Create a CloudFormation Stack --> Invoke the Custom Resource --> invoke the Boto3 IoT "create_keys_and_certificate" API --> save the certificates in Systems Manager Parameter Store

import os
import sys
import json
import logging as logger
import requests
import boto3
from botocore.config import Config
from botocore.exceptions import ClientError

import time

logger.getLogger().setLevel(logger.INFO)


def get_aws_client(name):
    return boto3.client(
        name,
        config=Config(retries={"max_attempts": 10, "mode": "standard"}),
    )


def create_resources(thing_name: str, stack_name: str, encryption_algo: str):

    c_iot = get_aws_client("iot")
    c_ssm = get_aws_client("ssm")

    result = {}

    # Download the Amazon Root CA file and save it to Systems Manager Parameter Store
    url = "https://www.amazontrust.com/repository/AmazonRootCA1.pem"
    response = requests.get(url)

    if response.status_code == 200:
        amazon_root_ca = response.text
    else:
        f"Failed to download Amazon Root CA file. Status code: {response.status_code}"


    try:
        # Create the keys and certificate for a thing and save them each as Systems Manager Parameter Store value later
        response = c_iot.create_keys_and_certificate(setAsActive=True)
        certificate_pem = response["certificatePem"]
        private_key = response["keyPair"]["PrivateKey"]
        result["CertificateArn"] = response["certificateArn"]
    except ClientError as e:
        logger.error(f"Error creating certificate, {e}")
        sys.exit(1)  

    # store certificate and private key in SSM param store
    try:
        parameter_private_key = f"/{stack_name}/{thing_name}/private_key"
        parameter_certificate_pem = f"/{stack_name}/{thing_name}/certificate_pem"
        parameter_amazon_root_ca = f"/{stack_name}/{thing_name}/amazon_root_ca"

        # Saving the private key in Systems Manager Parameter Store
        response = c_ssm.put_parameter(
            Name=parameter_private_key,
            Description=f"Certificate private key for IoT thing {thing_name}",
            Value=private_key,
            Type="SecureString",
            Tier="Advanced",
            Overwrite=True
        )
        result["PrivateKeySecretParameter"] = parameter_private_key

        # Saving the certificate pem in Systems Manager Parameter Store
        response = c_ssm.put_parameter(
            Name=parameter_certificate_pem,
            Description=f"Certificate PEM for IoT thing {thing_name}",
            Value=certificate_pem,
            Type="String",
            Tier="Advanced",
            Overwrite=True
        )
        result["CertificatePemParameter"] = parameter_certificate_pem

        # Saving the Amazon Root CA in Systems Manager Parameter Store, 
        # Although this file is publically available to download, it is intended to provide a complete set of files to try out this working example with as much ease as possible
        response = c_ssm.put_parameter(
            Name=parameter_amazon_root_ca,
            Description=f"Amazon Root CA for IoT thing {thing_name}",
            Value=amazon_root_ca,
            Type="String",
            Tier="Advanced",
            Overwrite=True
        )
        result["AmazonRootCAParameter"] = parameter_amazon_root_ca
    except ClientError as e:
        logger.error(f"Error creating secure string parameters, {e}")
        sys.exit(1)

    try:
        response = c_iot.describe_endpoint(endpointType="iot:Data-ATS")
        result["DataAtsEndpointAddress"] = response["endpointAddress"]
    except ClientError as e:
        logger.error(f"Could not obtain iot:Data-ATS endpoint, {e}")
        result["DataAtsEndpointAddress"] = "stack_error: see log files"

    return result

# Delete the resources created for a thing when the CloudFormation Stack is deleted
def delete_resources(thing_name: str, certificate_arn: str, stack_name: str):
    c_iot = get_aws_client("iot")
    c_ssm = get_aws_client("ssm")

    try:
        # Delete all the Systems Manager Parameter Store values created to store a thing's certificate files
        parameter_private_key = f"/{stack_name}/{thing_name}/private_key"
        parameter_certificate_pem = f"/{stack_name}/{thing_name}/certificate_pem"
        parameter_amazon_root_ca = f"/{stack_name}/{thing_name}/amazon_root_ca"
        c_ssm.delete_parameters(Names=[parameter_private_key, parameter_certificate_pem, parameter_amazon_root_ca])
    except ClientError as e:
        logger.error(f"Unable to delete parameter store values, {e}")

    try:
        # Clean up the certificate by firstly revoking it then followed by deleting it
        c_iot.update_certificate(certificateId=certificate_arn.split("/")[-1], newStatus="REVOKED")
        c_iot.delete_certificate(certificateId=certificate_arn.split("/")[-1])
    except ClientError as e:
        logger.error(f"Unable to delete certificate {certificate_arn}, {e}")


def handler(event, context):
    props = event["ResourceProperties"]
    physical_resource_id = ""
    

    try:
        # Check if this is a Create and we're failing Creates
        if event["RequestType"] == "Create" and event["ResourceProperties"].get(
            "FailCreate", False
        ):
            raise RuntimeError("Create failure requested, logging")
        elif event["RequestType"] == "Create":
            logger.info("Request CREATE")

            resp_lambda = create_resources(
                thing_name=props["CatFeederThingLambdaCertName"],
                stack_name=props["StackName"],
                encryption_algo=props["EncryptionAlgorithm"]
            )

            resp_controller = create_resources(
                thing_name=props["CatFeederThingControllerCertName"],
                stack_name=props["StackName"],
                encryption_algo=props["EncryptionAlgorithm"]
            )

            # The values in the response_data could be used in the CDK code, for example used as Outputs for the CloudFormation Stack deployed
            response_data = {
                "CertificateArnLambda": resp_lambda["CertificateArn"],
                "PrivateKeySecretParameterLambda": resp_lambda["PrivateKeySecretParameter"],
                "CertificatePemParameterLambda": resp_lambda["CertificatePemParameter"],
                "AmazonRootCAParameterLambda": resp_lambda["AmazonRootCAParameter"],
                "CertificateArnController": resp_controller["CertificateArn"],
                "PrivateKeySecretParameterController": resp_controller["PrivateKeySecretParameter"],
                "CertificatePemParameterController": resp_controller["CertificatePemParameter"],
                "AmazonRootCAParameterController": resp_controller["AmazonRootCAParameter"],
                "DataAtsEndpointAddress": resp_lambda[
                    "DataAtsEndpointAddress"
                ],
            }

            # Using the ARNs of the pairs of certificates created as the PhysicalResourceId used by Custom Resource
            physical_resource_id = response_data["CertificateArnLambda"] + "," + response_data["CertificateArnController"]
        elif event["RequestType"] == "Update":
            logger.info("Request UPDATE")
            response_data = {}
            physical_resource_id = event["PhysicalResourceId"]
        elif event["RequestType"] == "Delete":
            logger.info("Request DELETE")

            certificate_arns = event["PhysicalResourceId"]
            certificate_arns_array = certificate_arns.split(",")

            resp_lambda = delete_resources(
                thing_name=props["CatFeederThingLambdaCertName"],
                certificate_arn=certificate_arns_array[0],
                stack_name=props["StackName"],
            )

            resp_controller = delete_resources(
                thing_name=props["CatFeederThingControllerCertName"],
                certificate_arn=certificate_arns_array[1],
                stack_name=props["StackName"],
            )
            response_data = {}
            physical_resource_id = certificate_arns
        else:
            logger.info("Should not get here in normal cases - could be REPLACE")

        send_cfn_response(event, context, "SUCCESS", response_data, physical_resource_id)
    except Exception as e:
        logger.exception(e)
        sys.exit(1)


def send_cfn_response(event, context, response_status, response_data, physical_resource_id):
    response_body = json.dumps({
        "Status": response_status,
        "Reason": "See the details in CloudWatch Log Stream: " + context.log_stream_name,
        "PhysicalResourceId": physical_resource_id,
        "StackId": event['StackId'],
        "RequestId": event['RequestId'],
        "LogicalResourceId": event['LogicalResourceId'],
        "Data": response_data
    })

    headers = {
        'content-type': '',
        'content-length': str(len(response_body))
    }

    requests.put(event['ResponseURL'], data=response_body, headers=headers)

How I am using Custom Resources with AWS CDK?

What I am about to describe in this section can also be applied to a regular CloudFormation template, as a matter of fact, CDK will generate a CloudFormation template behind the scenes during the Synth phase of the CDK code in the latest version of my IoT Core reference architecture implemented using AWS CDK: https://chiwaichan.co.nz/blog/2024/02/02/feedmyfurbabies-i-am-switching-to-aws-cdk/

If you want to get straight into deploying the CDK version of reference architecture, go here: https://github.com/chiwaichan/feedmyfurbabies-cdk-iot

In my CDK code, I provision the Custom Resource lambda function and the associated IAM Roles and Polices using the Python code below. The line of code "code=lambda_.Code.from_asset("lambdas/custom-resources/iot")" loads the Custom Resource Lambda function code shown earlier.

# IAM Role for Lambda Function
        custom_resource_lambda_role = iam.Role(
            self, "CustomResourceExecutionRole",
            assumed_by=iam.ServicePrincipal("lambda.amazonaws.com")
        )

        # IAM Policies
        iot_policy = iam.PolicyStatement(
            actions=[
                "iot:CreateCertificateFromCsr",
                "iot:CreateKeysAndCertificate",
                "iot:DescribeEndpoint",
                "iot:AttachPolicy",
                "iot:DetachPolicy",
                "iot:UpdateCertificate",
                "iot:DeleteCertificate"
            ],
            resources=["*"]  # Modify this to restrict to specific secrets
        )

        # IAM Policies
        ssm_policy = iam.PolicyStatement(
            actions=[
                "ssm:PutParameter",
                "ssm:DeleteParameters"
            ],
            resources=[f"arn:aws:ssm:{self.region}:{self.account}:parameter/*"]  # Modify this to restrict to specific secrets
        )

        logging_policy = iam.PolicyStatement(
            actions=[
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            resources=["arn:aws:logs:*:*:*"]
        )
       
        custom_resource_lambda_role.add_to_policy(iot_policy)
        custom_resource_lambda_role.add_to_policy(ssm_policy)
        custom_resource_lambda_role.add_to_policy(logging_policy)

        # Define the Lambda function
        custom_lambda = lambda_.Function(
            self, 'CustomResourceLambdaIoT',
            runtime=lambda_.Runtime.PYTHON_3_8,
            handler="app.handler",
            code=lambda_.Code.from_asset("lambdas/custom-resources/iot"),
            timeout=Duration.seconds(60),
            role=custom_resource_lambda_role
        )


        # Properties to pass to the custom resource
        custom_resource_props = {
            "EncryptionAlgorithm": "ECC",
            "CatFeederThingLambdaCertName": f"{cat_feeder_thing_lambda_name.value_as_string}",
            "CatFeederThingControllerCertName": f"{cat_feeder_thing_controller_name.value_as_string}",
            "StackName": f"{construct_id}",
        }

        # Create the Custom Resource
        custom_resource = CustomResource(
            self, 'CustomResourceIoT',
            service_token=custom_lambda.function_arn,
            properties=custom_resource_props
        )

When you execute a "cdk deploy" using the CLI on the CDK reference architecture, CDK will synthesize from the Python CDK code, a CloudFormation template, and then create a CloudFormation Stack using the synthesized CloudFormation template for you.

For more details on the CDK AWS IoT reference architecture and deployment instructions, please visit my blog: https://chiwaichan.co.nz/blog/2024/02/02/feedmyfurbabies-i-am-switching-to-aws-cdk/

In my previous AWS IoT Cat feeder project I used a Lambda function as the event handler each time the Seeed Studio AWS IoT 1-click button was pressed, the Lambda function in turn published an MQTT message to AWS Iot Core which is received by the Cat Feeder (via a Seeed Studio XIAO ESP32C3 micro-controller) to dispense food into either one of the cat bowls or both (depending on the type of press performed on the IoT button). The long term goal is to integrate the AWS IoT Cat Feeder with the Feed My Fur Babies project.

In this Part 2 of the Feed My Fur Babies blog series, I will be introducing the Event-Sourcing pattern to the https://www.feedmyfurbabies.com architecture; describe the benefits of designing an architecture around Event-Souring and an example implemented using Terraform. I recently learnt Terraform and I now prefer it over the native IaC.

Current state architecture​

Here is the current state of the Cat Feeder architecture amd the IoT related resources previously deployed in AWS using CloudFormation:

The responsibilities of each of the resources deployed in the diagram prior to the introduction of the Event-Sourcing pattern into the architecture are:

• AWS IoT 1-Click Button: This is an IoT button I physically press to emit an event to dispense food into one or both of the cat bowls, this button can be used anywhere where there is a WIFI connection
• AWS IoT Core Certificates: Certificates are associated with resources and devices that interacts with the AWS IoT Core Service, either publishing an MQTT message to an AWS IoT Topic, or receiving an MQTT message from a Topic
• AWS Lambda - IoT 1-Click Event Handler & sends an MQTT message to an Iot topic: This Lambda function is responsible for handling incoming events created by the AWS IoT 1-Click Button, as well as translating the event into an MQTT message before sending it to an AWS IoT Core Topic. This is the component in the architecture that is the main focus of this blog post, we will describe how this component will be re-architectured and decomposed to work in conjunction with the introduction of the Event-Sourcing pattern.
• AWS IoT Core: This is the IoT service that manages the IoT Topics and Subcriptions to said Topics
• Seeed Studio XIAO ESP32C3: a micro-controller subscribed to the IoT Topic (the one the Lambda sent MQTT messages to) that will dispense food into 1 or 2 cat bowls when it receives an MQTT message from the Topic

For further details on what role this architecture plays in the Smart IoT Cat Feeder, visit Part 2 of the Smart Cat Feeder Blog Series.

What is Event-Sourcing?

The idea of Event-Sourcing is to capture all events that occurs within a system during its lifetime, these events are stored in an immutable ledger in the sequence in which they occurred in.

One of the biggest benefits of capturing all the events of a system is that we are able to replay every single event that has ever occured within the system (partially or as a whole) at a later time (lets say 5 years later), and have the ability to selectively replay the 5 years worth of events to one or more specific downstream event bus targets: an event bus target could be a new application that was deployed into your production environment 5 years after the first event was created; what this means is that we could hydrate this new application's datastore with 5 years worth of data as if it existed at the beginning when the first event occured. Also, imagine being able to re-create entire datastores with the full history for 100s of applications (where each application has its own datastore) within your system landscape, these datastores could be hydrated with the full history of events stored in the immutable Event-Sourcing ledger, or even replay the events that occur from the very first event and up to a specific event at a given point in time (e.g. half of the entire ledge) - effectively providing you with the ability to create any datastore in any datastore engine with the data inside in a state to any given point in time.

How do we introduce Event-Sourcing into the architecture?

We start off with the AWS Lambda function shown in the current state architecture where its responsibilites is to handle the events received from the AWS IoT 1-Click Button each time it is pressed, as well as sending an MQTT message to an AWS Iot Core Topic in response to each incoming event; essentially it has 2 distinct responsibilities

Next, we decompose the single Lambda function into 2 separate distinct Lambda functions based on its 2 responsibilities, then we chain the 2 Lambda functions together to preserve its functionality - what we have effectively achieved by doing this is decoupling the 2 responsibilities as 2 separate units of work - resulting in 2 separate compute resources.

The benefits by a decoupled architecture are:

• Each of the Lambda functions can be implemented in different languages - e.g. one in Python and the other can be in Java
• Independent release cycles for each of the Lambda functions
• Changes to either one of the 2 responsibilities can be made independently of each other
• Each Lambda function can be scaled independently of another

In this step we use Amazon EventBridge as the Event-Sourcing store - known as the immutable ledger we described earlier, we will also leverage EventBridge as a serverless event bus to help us receive, filter, transform, route and deliver events to downstream services (event bus targets). In this instance we will slip EventBridge in between the 2 Lambda functions and we will be storing every single IoT event sent by the IoT Button into the immutable ledge,

Benefits of adding EventBridge to the architecture:

• The IoT 1-Click Lambda handler no longer directly calls the downstream Lambda function - so it is unaware of the downstream targets
• The IoT events are stored in an immutable ledger in the sequence in which they occurred in
• Prepare the system landscape with the ability to more easily develop micro-services in an Event-Driven architecture using the orchestration pattern

Target State Architecture

This is the end result of introducing Event-Sourcing to the architecture; it may not look like much benefits has been gained from adding Amazon EventBridge - in fact one might think that we've added more components and in effect created more moving parts and complexity. But I have decided to specifically introduce this very early into the architecture as an investment so that I am in a position to rapdily build out my micro-service architecture - reaping the rewards from the get go.

Try it out for yourself

I have created a GitHub Repository to deploy a complete working example of the resources shown in the Target State Architecture using Terraform.

I suggest you deploy this to have a play for yourself:

1. Clone the repository: "git clone git@github.com:chiwaichan/feedmyfurbabies-202303-eventsourcing-using-eventbridge.git"
2. Setup your Terraform environment
3. Run: "terraform init && terraform apply"

Also, check out each individual resource deployed by this Terrafrom code.

Create a test IoT 1-Click event to pass the event end-to-end through all the deployed resources

This is the IoT 1-Click Lambda function handler shown in the AWS Console

Create a test event so we can invoke the Lambda function to simulate an event as if a physical IoT Button is pressed

Here we can view the logs for this Lambda function Test invocation

The IoT 1-Click Lambda function handler sends an Event to the Custom EventBridge Event Bus named "feedmyfurbabies"

The event sent to the Custom Event Bus matches on the "source" attribute with a value of "com.feedmyfurbabies" with the Custom Event Bus Rule named "feeds-rule"

This Lambda function is the downstream target of the Custom Event Bus Rule that was mactched by the event and is responsible for interpreting the event message and translate it into an MQTT message, then in turn sends it to the AWS IoT Core Topic "cat-feeder/action" that you can subscribe to using a micro-controller, e.g. Seeed Studio XIAO ESP32C3.

Here we can see the logs of the event received by the EventBridge Custom Bus Rule

In the AWS Console for the AWS Iot Core Service, we can subscribe to Topics to receive an MQTT message right at the end of the downstream services - this is useful if you don't use a micro-controller

Future State Architecture

We end up with an architecture that will enable us to easily add targets to consume events managed by the EventBridge Custom Event Bus, doing so in a way where the IoT 1-Click Lambda function has no knowledge of any newly created subscribers of the Custom Event Bus.

In a future blog I will demonstrate this.

I'm starting a new blog series where I will be documenting my build of a full-stack Web and Mobile application using AWS Amplify to implement both the frontend, as well as the backend; whilst developing dependent downstream Services outside of Amplify using AWS Serverless components to implement a Micro-Service architecture using Event-Driven design pattern - where we will break the application up into smaller consumable chunks that works together well.

Since we are creating from scratch a completely new application, I will also incorporate a vital pattern that will reduce complexity throughout the lifetime of the application: we will also be implementing the application using the Event-Sourcing pattern - this pattern ensures every Event ever published within a system is stored within an immutable ledger; this ledger will enable new Data Stores of any Data Store Engine to be created at any given time by replaying the Events in the ledger, of Events created from a start date and time to an end Date and Time.

CQRS is a pattern I will write up about with great detailed in a blog in the near future, CQRS will enable the ability to create mulitple Data Stores with identical data, each Data Store using a unique Data Store Engine instance.

What is AWS Amplify?​

Amplify is an AWS Service that provides any frontend web or mobile developers with no cloud expertise the ability to build and host full-stack applications on AWS. As a frontend developer, you can leverage it to build and integrate AWS Services and components into your frontend without having to deal with the underlying AWS Services; all Services the frontend is built on top of is managed by AWS Amplify - e.g. no need to managed CloudFormation Stacks, S3 Storage or AWS Cognito.

What will I be doing with Amplify​

My experience from a while ago was full-stack application development and I have worked under that role for over 10 years, I've used various frontend/backend frameworks, components and patterns.

I will be building a website called Feed My Fur Babies where I will provide video streams showing live feeds of my cats from web cams placed in various spots around my house, the website will also provide users with the ability to feed my cats using internet enabled devices like the IoT Cat Feeders I recently put together and watch them hoon on their favorite treats; although I am experienced with building websites from the ground up using AWS Service, I am aiming to build Feed My Fur Babies whilst leveraging as little as possible on that experience - this is so I am building the website as close to the targeted demographics skillset of a typical Amplify as possible, i.e. as a developer with only frontend experience.

Current Architecture State

Update

Let's talk about what was done to get to the current architecture state.

First thing I did was buying the domain feedmyfurbabies.com using AWS Route53.

Next, I created a new Amplify App called "Feedme".

Within the App I created two Hosted Environments: one environment is to host the production environment, the other is to host a development environment. Each Hosted Environment is configured to be built and deployed from a specfic Branch in the shared CodeCommit Repository used to version control the frontend source code.

This is the Part 4 and final blog of the series where I detail my journey in learning to build an IoT solution.

Please have a read of my previous blogs to get the full context leading up to this point before continuing.

• Part 1: I talked about setting up a Seeed AWS IoT Button
• Part 2: I talked about publishing events to an Adruino Micro-controller from AWS
• Part 3: I talked about my experience of using a 3D Printer for the first time to print a Cat Feeder

Why am I building this Feeder?​

I've always wanted to dip my toes into building IoT solutions beyond doing what a typical tutorial teaches in only turning on LEDs - I wanted to build something that would used everyday. Plus, I often forget to feed the cats while I am away from home (for the day), so it would be nice to come home to a non-grumpy cat by feeding them remotely any time and from any where in the world using the internet.

What was used to build this Feeder?​

• A 3D Printer using PLA as the filament material.
• An Arduino based micro-controller - in this case a Seeed Studio XIAO ESP32C3
• A couple of motors and controllers
• AWS Services
• Seeed AWS IoT Button
• Some code
• and some cat food

So how does it work and how is it put together?​

To simply describe what is built, the Feeder uses an Iot button click to trigger events over the internet to instruct the feeder to dispense food into one or both food bowls.

Here are some diagrams describing the architecture of the solution - the technical things that happens in-between the IoT button and the Cat Feeder.

When the Feeder receives a MQTT message from the AWS IoT Core Service, it runs the motor for 10 seconds to dispense food into either one of food bowls, and if the message contains an event value to dispense food into both bowls we can run both motors concurrently using the L298N controller.

Here's a video of some timelapse picture captured during the 3 weeks it took to 3D print the feeder.

The Feeder is made up of a small handful of basic hardware components, below is a Breadboard diagram depicting the components used and how they are all wired up together. A regular 12V 2A DC power adapter supply is used to power all the components.

The code to start and stop a motor is about 10 lines of code as shown below. This is the completed version of the Arduino Sketch shown in Part 2 of this blog series when it was partially written at the time.

#include "secrets.h"
#include <WiFiClientSecure.h>
#include <MQTTClient.h>
#include <ArduinoJson.h>
#include "WiFi.h"

// The MQTT topics that this device should publish/subscribe
#define AWS_IOT_PUBLISH_TOPIC   "cat-feeder/states"
#define AWS_IOT_SUBSCRIBE_TOPIC "cat-feeder/action"

WiFiClientSecure net = WiFiClientSecure();
MQTTClient client = MQTTClient(256);

int motor1pin1 = 32;
int motor1pin2 = 33;
int motor2pin1 = 16;
int motor2pin2 = 17;

void connectAWS()
{
  WiFi.mode(WIFI_STA);
  WiFi.begin(WIFI_SSID, WIFI_PASSWORD);

  Serial.println("Connecting to Wi-Fi");
  Serial.println(AWS_IOT_ENDPOINT);

  while (WiFi.status() != WL_CONNECTED) {
    delay(500);
    Serial.print(".");
  }

  // Configure WiFiClientSecure to use the AWS IoT device credentials
  net.setCACert(AWS_CERT_CA);
  net.setCertificate(AWS_CERT_CRT);
  net.setPrivateKey(AWS_CERT_PRIVATE);

  // Connect to the MQTT broker on the AWS endpoint we defined earlier
  client.begin(AWS_IOT_ENDPOINT, 8883, net);

  // Create a message handler
  client.onMessage(messageHandler);

  Serial.println("Connecting to AWS IOT");
  Serial.println(THINGNAME);

  while (!client.connect(THINGNAME)) {
    Serial.print(".");
    delay(100);
  }

  if (!client.connected()) {
    Serial.println("AWS IoT Timeout!");
    return;
  }

  Serial.println("About to subscribe");
  // Subscribe to a topic
  client.subscribe(AWS_IOT_SUBSCRIBE_TOPIC);

  Serial.println("AWS IoT Connected!");
}

void publishMessage()
{
  StaticJsonDocument<200> doc;
  doc["time"] = millis();
  doc["state_1"] = millis();
  doc["state_2"] = 2 * millis();
  char jsonBuffer[512];
  serializeJson(doc, jsonBuffer); // print to client

  client.publish(AWS_IOT_PUBLISH_TOPIC, jsonBuffer);

  Serial.println("publishMessage states to AWS IoT" );
}

void messageHandler(String &topic, String &payload) {
  Serial.println("incoming: " + topic + " - " + payload);

  StaticJsonDocument<200> doc;
  deserializeJson(doc, payload);
  const char* event = doc["event"];

  Serial.println(event);

  feedMe(event);  
}

void setup() {
  Serial.begin(9600);
  connectAWS();

  pinMode(motor1pin1, OUTPUT);
  pinMode(motor1pin2, OUTPUT);
  pinMode(motor2pin1, OUTPUT);
  pinMode(motor2pin2, OUTPUT);
}

void feedMe(String event) {
  Serial.println(event);

  bool feedLeft = false;
  bool feedRight = false;

  if (event == "SINGLE") {
    feedLeft = true;
  }
  if (event == "DOUBLE") {
    feedRight = true;
  }
  if (event == "LONG") {
    feedLeft = true;
    feedRight = true;
  }

  if (feedLeft) {
    Serial.println("run left");
    digitalWrite(motor1pin1, HIGH);
    digitalWrite(motor1pin2, LOW);
  }

  if (feedRight) {
    Serial.println("run right");
    digitalWrite(motor2pin1, HIGH);
    digitalWrite(motor2pin2, LOW);
  }

  delay(10000);
  digitalWrite(motor1pin1, LOW);
  digitalWrite(motor1pin2, LOW);
  digitalWrite(motor2pin1, LOW);
  digitalWrite(motor2pin2, LOW);
  delay(2000);

  Serial.println("fed");
}

void loop() {
  publishMessage();
  client.loop();
  delay(3000);
}

Demo Time​

The Seeed AWS IoT Button is able to detect 3 different types of click events: Long, Single and Double, and we are able to leverage this all the way to the feeder so we will have it performing certains actions base on the click event type.

The video below demonstrates the following scenarios:

• Long Click: this will dispense food into both cat bowls
• Single Click: this will dispense food into Ebok's cat bowl
• Double Click: this will dispense food into Queenie's cat bowl

What's next?​

Build the nervous system of an ultimate nerd project I have in mind that would allow me to voice control actions controlling servos, LEDs and audio outputs, by using a mesh of Seeed XIAO BLE Sense micro-controllers and TinyML Machine Learning.

In this Part 3 of the blog series I talk about my experience printing objects using a 3D Printer for the first time. In Part 1, I talked about setting up an IoT Button; and in Part 2, I talked about publishing events to an Adruino Micro-controller from AWS.

After putting in the hard work in setting up the Creality Ender 3 V2 3D printer, Queenie decided to give the BL Touch Auto Bed Levelling a test run. The Auto Levelling is a must as it greatly improvements productivity by not having to fiddle around with the bed as much without it.

Setting up the printer took 2 nights to set it up, a small portion of the effort was involved in physically putting all the printer parts together, but most of the time spent was fine tuning the Z axis (common problem) and levelling the bed - with prints we are working with margins of tolerances of 0.01mm in each of the 3 planes (X, Y and Z positions). I was lucky enough to avoid a lot of headache as a friend who has the same model had forewarned me of the common pain points in setting up this printer, so it would have taken a week or more to fine tune it if I had to figure it all out by myself.

There are loads of upgrade parts and accessories for the Creality Ender 3 which can be found on sites such as www.thingiverse.com published by the 3D printing community.

Now back to the Cat Feeder​

Turns out 3D modeling tools such as Blender is a lot more difficult to learn than I first anticipated; I originally set out to design a Cat Feeder model from scratch in Blender, however, the learning curve in picking it up is much stepper than I hoped; so I decided to jump on ThingieVerse and found a Cat Feeder designed shared by someone from the community. In future projects, I will be more strategic in what I decide build, I will focus on improving on the disciplines (AWS IoT, working with micro-controllers, sensors, motors, designing 3D models and printing plastics) where I need improvement the most. So the next project I have in mind is a Fish Feeder, the main goal of that is to improve my modeling skills, I will design an Feeder with way fewer and more simple components than this project but the core concept will remain the same. Fishes eat less than cats in terms of volume, which means I would be able to use a smaller single motor which in turns means a simpler controller/circuit and fewer parts, and potentially the feeder could run off a re-chargeable battery (charged via USB C) that could last roughly 6 months or more.

Here is what the printed parts look like.

It took almost 4 weeks of constant printing, then half way through I remembered to create a time-lapse of the print.

What's next?​

I'm building this project with parts sourced from AliExpress to keep the cost of the build to a minimum but the down side to that means some parts takes months to arrive, I am waiting for the stepper motor controller and DC-DC step down (5.0V to 3.3V) power supply buck modules to arrive. Once the remaining parts arrive I will put together all the circuit components, followed by combining it with the bits from Part 1 and Part 2, then put out a final blog for the series with a demonstration.

The source code for this blog can be found in my Github repository: https://github.com/chiwaichan/aws-iot-cat-feeder. This repository only includes the source code for the solution implemented up to this stage/blog in the project.

In the end I decided to go with the Seeed Studio XIAO ESP32C3 implementation of the ESP32 micro-controller for $4.99 (USD). I also ordered some other bits and pieces from AliExpress that's going to take some time to arrive.

In this Part 2 of the blog series I will demonstrate the exchange of messages (JSON payload) using the MQTT protocol between the ESP32 and the AWS IoT Core Service, as well as the exchange of messages between a Lambda Function and the ESP32 - this Lambda is written in Python which is intended to replace the Lambda triggered by the IoT button event found in Part 1.

Prerequisites if you like to try out the solution using the source code​

• An AWS account.
• An IoT button. Follow Part 1 of this blog series to onboard your IoT button into the AWS IoT 1-Click Service.
• Create 2 Certificates in the AWS IoT Core Service. One certificate is for the ESP32 to publish and subscribe to Topics to IoT Core, and the other is used by the IoT button's Lambda to publish a message to a Topic subscribed by the ESP32.

Create a Certificate using the recommended One-Click option.

Download the following files and take note of which device (the ESP32 or the IoT Lambda) you like to use this certificate for:

• xxxxx.cert.pem
• xxxxx.private.key
• Amazon Root CA 1: https://www.amazontrust.com/repository/AmazonRootCA1.pem

Activate the Certificate.

Click on Done. Then repeat the steps to create the second Certificate.

Publish ESP32 States to AWS IoT Core​

The diagram above depicts the components used that is required in order for the ESP32 to send the States of the Cat Feeder, I've yet to decide what to send but examples could be 1.) battery level 2.) Cat weight (based on a Cat's RFID chip and some how weighing them while they eat) 3.) or how much food is remaining in the feeder. So many options.

1. ESP32: This is the micro-controller that will eventually have a bunch of hardware components that we will take States from, then publish to a Topic.
2. MQTT: This is the lightweight pub/sub protocol used to send IoT messages over TCP/IP to AWS IoT Core.
3. AWS IoT Core: This is the service that will forward message to the ESP32 micro-controller that are subscribed to Topics.
4. IoT Topic: The Lambda will publish a message along with the type of button event (One click, long click or double click) to the Topic "cat-feeder/action", the value of the event is subject to what is supported by the IoT button you use.
5. Do something later on: I'll decide later on what to do downstream with the State values. This could be anything really, e.g. save a time series of the data into a database or bunch of DynamoDB tables, or get an alert to remind me to charge the Cat Feeder's battery with a customizable threshold?

Instructions to try out the Arduino/ESP32 part of the solution for yourself​

1. Install the Arduino IDE.
2. Follow this AWS blog on setting up an IoT device, start from "Installing and configuring the Arduino IDE" to including "Configuring and flashing an ESP32 IoT device". Their blog walks us through on preparing the Arduino IDE and on how to flash the ESP32 with a Sketch.
3. Clone the Arduino source code from my Github repository: https://github.com/chiwaichan/aws-iot-cat-feeder
4. Go to the "secrets.h" tab and replace the following variables:

• WIFI_SSID: This is the name of your Wifi Access Point
• WIFI_PASSWORD: The password for your Wifi.
• AWS_IOT_ENDPOINT: This is the regional endpoint of your AWS Iot Core Service.

• AWS_CERT_CA: The content of the Amazon Root CA 1 file created in the prerequisites for the first certificate.
• AWS_CERT_CRT: The content of the xxxxx.cert.pem file created in the prerequisites for the first certificate.
• AWS_CERT_PRIVATE: The content of the xxxxx.private.key file created in the prerequisites for the first certificate.

5. Flash the code onto the ESP32

You might need to push a button on the micro-controller during the flashing process depending on the your ESP32 micro-controller

6. Check the Arduino console to ensure the ESP32 can connect to AWS IoT and publish messages.

7. Verify the MQTT messages is received by AWS IoT Core

Sending a message to the ESP32 when the IoT button is pressed​

The diagram above depicts the components used to send a message to the ESP32 each time the Seeed AWS IoT button is pressed.

1. AWS IoT button: this is the IoT button I detail in Part 1; it's a physical button that can be anywhere in the world where I can press to feed the fur babies once the final solution is built.
2. AWS Lambda: This will replace the Lambda from the previous blog with the one shown in the diagram.
3. IoT Topic: The Lambda will publish a message along with the type of button event (One click, long click or double click) to the Topic "cat-feeder/action", the value of the event is subject to what is supported by the IoT button you use.
4. AWS IoT Core: This is the service that will forward message to the ESP32 micro-controller that are subscribed to Topics.
5. ESP32: We will see details of the button event from each click in the Arduino console once this part is set up.

Instructions to set up the AWS IoT button part of the solution​

1. Take the 3 files create in the second set of Certificate created in the AWS IoT Core Service in the prerequisites, then create 3 AWS Secrets Manager "Other type of secret: Plaintext" values. We need a Secret value for each file. This is to provide the Lambda Function the Certificate to call AWS IoT Core.

2. Get a copy of the AWS code from my Github repository: https://github.com/chiwaichan/aws-iot-cat-feeder

3. In a terminal go into the aws folder and run the commands found in the "sam-commands.text" file, be sure to replace the following values in the commands to reflect the values for your AWS account. This will create a CloudFormation Stack of the AWS IoT Services used by this entire solution.

• YOUR_BUCKET_NAME
• Value for IoTEndpoint
• Value for CatFeederThingLambdaCertName, this is the name of the long certificate value found in Iot Core created in the prerequisites for the second certificate.
• Value for CatFeederThingLambdaSecretNameCertCA, e.g. "cat-feeder-lambda-cert-ca-aaVaa2", check the name in Secrets Manager.
• Value for CatFeederThingLambdaSecretNameCertCRT
• Value for CatFeederThingLambdaSecretNameCertPrivate
• Value for CatFeederThingControllerCertName, this is the name of the long certificate value found in Iot Core created in the prerequisites for the second certificate used by the ESP32.
• Find the Lambda created in the CloudFormation stack and Test the Lambda to manually trigger the event.
• If you have setup an IoT 1-Click Button found in Part 1, you can replace that Lambda with the one created by the CloudFormation Stack. Go to the "AWS IoT 1-Click" Service and edit the "template" for the CatFeeder project.

10. Let's press the Iot Button in the following way:

• Single Click
• Double Click
• Long Click

11. Verify the button events are received by the ESP32 by going to the Arduino console and you should see something like this:

What's next?​

I recently got a Creality3D Ender-3 V2 printer, I've got many known unknowns I know I need to get up to speed with in regards to fundamentals of 3D printing and all the tools, techniques and software associated with it. I'll attempt to print an enclosure to house the ESP32 controller, the wires, power supply/battery (if I can source a battery that lasts for more than a month on a single charge) and most importantly the dry cat food; I like to use some mechanical components to dispense food each time we press the IoT button described in Part 1. I'll talk in depth on the progress made on the 3D printing in Part 3.

If you are forgetful when it comes to feeding your fur babies like me, and you often only realise you need to put some dry food into the bowl when you are at work then you should read these series of blogs. Over time, I'll be designing and building a smart cat feeder over time using a combination of components such as Arduino micro controllers, motors, sensors and IoT devices and Cloud services. I'll publish the steps taken in these series of blogs, also, I'll publish any designs and source code as I figure things out and make decisions on aspects of the design.

In this part 1 of the series, I will do a walkthrough on setting up an AWS IoT 1-Click device to trigger a Lambda Function. I got myself one of these Seeed IoT buttons for $20; I also bought a NCR18650B battery which I realised later on is only required if I wanted to run the device without it being powered by a USB type-C cable (used for charging the power as well).

Firstly, make sure you have an AWS account. Then install the AWS IoT1-Click app onto your phone and log in using your AWS account. With these we will be able to link IoT devices up to our AWS account.

Claim the IoT device with Device ID

Scan the barcode on the back of the device; you can scan multiple devices in bulk.

Next, I'll set up the Wifi on the device so that it can reach the internet internet from home. Can't see why I can't set it up to my phone's AP for feeding on the go, I'll try it out some other time.

Now we'll create a project and add the IoT device to a placement group in the AWS Console. Give a name and description for the project.

Next define a template, this is where we create a Lambda function; all the plumbing between the IoT device and Lambda will be handled for us.

Next we create a placement for the Iot device.

Since I have no Arduino micro-controllers (have yet to buy one), I will get the Lambda to log a message.

Push the button on the Iot device, wait for the event LED status to turn green after flashing white then check the logs CloudWatch Logs.

At some point I have to code the Lambda to perform a real action as each event comes through, which will be demonstrated in a following blog in the series instead of just logging to CloudWatch logs.

Within the app on your phone you can see status of each IoT device such as the remaining battery life percentage.

As well as a history of the button's events.

In the next blog, I'll configure the Lambda to push the event to a Topic for AWS IoT Core to subscribe to, which in turns will trigger an event to an ESP32 ( I've yet to decide on a specific version of the micro-controller) using the IoT MQTT protocol.