As Hardware, we have chosen an Arduino Uno WiFi Rev2.
1. Configure the Arduino Device
1.1 Set up the WiFi Connection
1.1.1 Manage Username and Password
#define SECRET_SSID "<your username>"
#define SECRET_PASS "<your password>"
1.1.2 WiFi Connection Code
#include <WiFiNINA.h>
#include "arduino_secrets.h"
///////please enter your sensitive data in the Secret tab/arduino_secrets.h
char ssid[] = SECRET_SSID; // your network SSID (name)
char pass[] = SECRET_PASS; // your network password (use for WPA, or use as key for WEP)
WiFiClient wifiClient;
void setup() {
//Initialize serial and wait for port to open:
Serial.begin(9600);
while (!Serial) {
; // wait for serial port to connect. Needed for native USB port only
}
// attempt to connect to Wifi network:
Serial.print("Attempting to connect to WPA SSID: ");
Serial.println(ssid);
while (WiFi.begin(ssid, pass) != WL_CONNECTED) {
// failed, retry
Serial.print(".");
delay(5000);
}
Serial.println("You're connected to the network");
Serial.println();
}
void loop()
{}
1.2 Set up the MQTT Connection to akenza
#include <PubSubClient.h>
//MQTTClient mqttClient(WiFiClient);
char host[] = "mqtt.akenza.io";
char clientid[] = "Arduino";
char username[] = "<copy from Akenza Device Api configuration>";
char password[] = "<copy from Akenza Device Api configuration>";
char outTopic[] = "<copy from Akenza Device Api configuration>";
PubSubClient client(host, 1883, callback, wifiClient);
void setup() {
if (client.connect(host, username, password)) {
Serial.print("Connected to ");
Serial.println(host);
Serial.println();
boolean r = client.subscribe(outTopic);
Serial.print("Subscribed to ");
Serial.println(outTopic);
Serial.println();
}
else {
// connection failed
// mqttClient.state() will provide more information
// on why it failed.
Serial.print("Connection failed: ");
Serial.println(client.state());
Serial.println();
}
}MQTT Essentials
Real-Time Supply Chain With Apache Kafka in the Food and Retail Industry
The supply chain in the food and retail industry is complex, error-prone, and slow. This article explores real-world deployments across the end-to-end supply chain powered by data streaming with Apache Kafka to improve business processes with real-time services. The examples include manufacturing, logistics, stores, delivery, restaurants, and other parts of the food and retail business. Case studies include Walmart, Albertsons, Instacart, Domino's Pizza, Migros, and more.
The Supply Chain in the Food and Retail Industry
The food industry is a complex, global network of diverse businesses that supplies most of the food consumed by the world's population. It is far beyond the following simplified visualization :-)
OPC-UA, MQTT, and Apache Kafka: The Trinity of Data Streaming in IoT
In the IoT world, MQTT (Message Queue Telemetry Transport protocol) and OPC-UA (OPC Unified Architecture) have established themselves as open and platform-independent standards for data exchange in Industrial Internet of Things (IIoT) and Industry 4.0 use cases. Data streaming with Apache Kafka is the data hub for integrating and processing massive volumes of data at any scale in real-time. This article explores the relationship between Kafka and the IoT protocols, when to use which technology, and why sometimes HTTP/REST is the better choice. The conclusion explores real-world case studies from Audi and BMW.
Industry 4.0: Data Streaming Platforms Increase Overall Plant Effectiveness and Connect Equipment
Machine data must be transformed and made available across the enterprise as soon as it is generated to extract the most value from the data. As a result, operations can avoid critical failures and increase the effectiveness of their overall plant.
Golang and Event-Driven Architecture
On March 31, 2022, I gave a talk at Conf42:Golang about using Go in an event-driven architecture entitled "Gopher in an Event-Driven Playground." You can check out the talk here or read along to know more about event-driven systems and how different messaging protocols are used in Go!
What's All the Hype About?
For all of us Go enthusiasts out there, we truly understand the beauty of using Go in applications and microservices because of its lightweight, high performance, and elegant syntax, to name just a few (let the debate start! ).
Kafka for Real-Time Replication Between Edge and Hybrid Cloud
Not all workloads should go to the cloud! Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration. This blog post explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell edge hardware and serverless Confluent Cloud.
Not Every Workload Should Go Into the Cloud
Almost every company has a cloud-first strategy in the meantime. Nevertheless, not all workloads should be deployed in the public cloud. A few reasons why IT applications still run at the edge or in a local data center:
Apache Kafka Landscape for Automotive and Manufacturing
Before the Covid pandemic, I had the pleasure of visiting "Motor City" Detroit in November 2019. I met with several automotive companies, suppliers, startups, and cloud providers to discuss use cases and architectures around Apache Kafka. A lot has happened. Since then, I have also met several OEMs and suppliers in Europe and Asia. As I finally go back to Detroit this January 2022 to meet customers again, I thought it would be a good time to update the status quo of event streaming and Apache Kafka in the automotive and manufacturing industry.
Today, in 2022, Apache Kafka is the central nervous system of many applications in various areas related to the automotive and manufacturing industry for processing analytical and transactional data in motion across edge, hybrid, and multi-cloud deployments. This article explores the automotive event streaming landscape, including connected vehicles, smart manufacturing, supply chain optimization, aftersales, mobility services, and innovative new business models.
MQTT Messaging With Java and Raspberry Pi
In December 2021, I had the chance to write a three-post blog series for HiveMQ. They provide an MQTT compatible message broker you can install yourself, or through a cloud service they provide. That cloud service is free to connect up to 100 devices! Even for the most enthusiastic maker, that’s a lot of microcontrollers or computers!
You can find example code for many programming languages on the HiveMQ site, but as a Java and Raspberry Pi fan, I wanted to add some extra examples. The full descriptions are available on the HiveMQ blog, so let me give you a short overview here on DZone to give you an idea of the possibilities.
Beginner’s Guide to Embedded Systems and Secure IoT Communication
If you are new to embedded programming or if you are new to the complex world of setting up secure IoT devices requiring X.509 certificate and PKI management, then the SharkSSL IDE for ESP32 is a great starting point. With this IDE, even a "Noob" can be up and running with the first RTOS-powered IoT device in 30 minutes.
In addition to many C code examples, the SharkSSL IDE also includes a project that lets developers with no C code experience program the ESP32 using a high level programming language called Lua.
Sticky Session Load Balancing (Part 2): MQTT Broker Clustering
In the last post: Load Balancing - MQTT Broker Clustering Part 1, we introduced MQTT load balancing in general: load balancing can be applied either on the transport layer or the application layer.
Now it’s time to dive into application layer load balancing, the most interesting part: sticky-session.
Kafka for Condition Monitoring and Predictive Maintenance in Industrial IoT
The manufacturing industry is moving away from just selling machinery, devices, and other hardware. Software and services increase revenue and margins. A former cost center becomes a profit center for innovation. Equipment-as-a-Service (EaaS) even outsources the maintenance to the vendor. This paradigm shift is only possible with reliable and scalable real-time data processing leveraging an event streaming platform such as Apache Kafka.
This post explores how the next generation of software for Condition Monitoring and Predictive Maintenance can help build new innovative products and improve the OEE for customers.
Using MQTT for IIOT Apps
Introduction to MQTT
MQTT is a communication protocol that has taken off in the IIoT community. It’s a lightweight, efficient protocol that works through a publisher/broker/subscriber model. It creates an easy way for field devices to communicate and retrieve data from a single location. In this tutorial, we’ll go over MQTT and dive into an example of how you can publish data using a groov EPIC PAC and retrieve the data using an MQTT client.
How MQTT Works
The Open Systems Interconnection (OSI) model is used to describe the way machines and applications communicate between themselves. The model was developed with the idea that a provider can utilize different protocols or software components at every layer without having to re-architect the entire structure. The MQTT protocol will come into play at Layer 7 of the model; on top of TCP/IP (Layer 4). The reason that this is important is that this keeps a lot of infrastructure in place while redefining how the packets are being sent between devices.
Apache Kafka and MQTT (Part 4 of 5) – Mobility Services and Transportation
Apache Kafka and MQTT are a perfect combination for many IoT use cases. This blog series covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions. This post is part four: Mobility Services and Transportation.
Apache Kafka + MQTT Blog Series
Apache Kafka and MQTT (Part 3 of 5) – Manufacturing 4.0 and Industrial IoT
Apache Kafka and MQTT are a perfect combination for many Industrial IoT use cases. This blog series covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions. This post is part three: Manufacturing, Industrial IoT, and Industry 4.0.
Apache Kafka + MQTT Blog Series
Apache Kafka and MQTT (Part 2 of 5) – V2X and Connected Vehicles
Apache Kafka and MQTT are a perfect combination for many IoT use cases. This blog series covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions. This post is part two: Connected Vehicles and V2X applications.
Apache Kafka + MQTT Blog Series
The first blog post explores the relation between MQTT and Apache Kafka. Afterward, the other four blog posts discuss various use cases, architectures, and reference deployments.
Apache Kafka for the Connected World: Vehicles, Factories, Cities
The digital transformation enables a connected world. People, vehicles, factories, cities, digital services, and other "things" communicate with each other in real-time to provide a safe environment, efficient processes, and a fantastic user experience. This scenario only works well with data processing in real-time at scale. This blog post shares a presentation that explains why Apache Kafka plays a key role in these industries and use cases but also to connect the different stakeholders.
Software is Changing and Connecting the World
Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way integrating with various legacy and modern data sources and sinks.
Apache Kafka for Smart Grid, Utilities and Energy Production
The energy industry is changing from system-centric to smaller-scale and distributed smart grids and microgrids. A smart grid requires a flexible, scalable, elastic, and reliable cloud-native infrastructure for real-time data integration and processing. This post explores use cases, architectures, and real-world deployments of event streaming with Apache Kafka in the energy industry to implement a smart grid and real-time end-to-end integration.
Smart Grid - The Energy Production and Distribution of the Future
The energy sector includes corporations that primarily are in the business of producing or supplying energy such as fossil fuels or renewables.
Smart Factory with Apache Kafka and 5G Campus Networks
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices using modern smart technology. Event Streaming with Apache Kafka plays a key role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way of integrating with various legacy and modern data sources and sinks. This blog post explores Apache Kafka's relationship to modern telco infrastructures that leverage private 5G campus networks for Industrial IoT (IIoT) and edge computing.