Category: AWS IoT Greengrass

Introduction As edge computing continues to gain traction in various industries, organizations are often looking for ways to efficiently analyze, optimize, and troubleshoot edge applications for better performance and reliability. In this blog post, we will demonstrate how to use AWS IoT Greengrass and AWS Distro for OpenTelemetry to implement tracing and observability methods that […]

Introduction As our world becomes increasingly interconnected, the Internet of Things (IoT) is becoming an unavoidable part of our daily lives. IoT devices, ranging from smart thermostats in our homes to sophisticated sensors in industrial settings, are everywhere. However, the effective management of these devices throughout their lifecycle presents a significant challenge. AWS IoT services, […]

Research suggests that Internet of Things (IoT) solution implementations typically take an average of 18-24 months to reach the market and be ready for adoption. Common scenarios related to IoT solution development include device provisioning, telemetry collection, and remote command and control. Depending on your use case, prototyping a well-architected IoT solution requires considerations for good design principles and best practices for each of these scenarios. This post illustrates how you can adopt a prototyping design pattern that combines an AWS Cloud Development Kit (AWS CDK), AWS IoT Greengrass, and Docker to accelerate your IoT solution prototyping on AWS.

The Internet of Things (IoT) has become increasingly prevalent in a variety of industries. In addition, with the increasing number of connected devices and the amount of sensitive information being transmitted, IoT security has become a top concern. As the global population continues to rise, the demand for energy has surged to unprecedented levels. In […]

Introduction Customers in manufacturing, logistics, and energy sectors often have stringent requirements for needing to run machine learning (ML) models at the edge. Some of these requirements include low-latency processing, poor or no connectivity to the internet, and data security. For these customers, running ML processes at the edge offers many advantages over running them […]

Introduction Internet of Things (IoT) developers often need to implement a robust mechanism for managing IoT device state either locally or remotely. A typical example is a smart home radiator, an IoT device where you can use the built-in control panel to adjust the temperature (device state), or trigger temperature adjustment messages remotely from a […]

Introduction We’re very pleased to introduce the Certificate Rotator component for AWS IoT Greengrass, a new component in the Greengrass Software Catalog. AWS IoT Greengrass brings the AWS cloud closer to edge devices to support applications that demand local data processing and low latency. The growing number of edge devices in consumer, enterprise, and industrial […]

AWS IoT VP, Yasser Alsaied, talks IoT strategy, commitment, and outlook Introduction The future of the Internet of Things (IoT) has been a topic of ongoing discussion and speculation. With implications for IoT hyperscalers, vendors, and customers alike, the landscape is rapidly evolving. To shed light on this topic, I spoke with Yasser Alsaied, vice […]

Introduction Performing machine learning inference on edge devices using models trained in the cloud has become a popular use case in Internet of Things (IoT) as it brings the benefits of low latency, scalability, and cost savings. When deploying models to edge devices with limited compute and memory, developers have the challenge to manually tune […]

Introduction When implementing an Internet of Things (IoT) workload, companies are faced with multiple options when it comes to choosing a platform. From building it entirely from scratch, including your own device hardware, all the way to purchasing preconfigured hardware and just connecting to a completely Software as a service (SaaS) IoT platform. The goal […]