New – FreeRTOS Extended Maintenance Plan for Up to 10 Years

Last AWS re:Invent 2020, we announced FreeRTOS Long Term Support (LTS) that offers a more stable foundation than standard releases, as manufacturers deploy and later update devices in the field. FreeRTOS is an open source, real-time operating system for microcontrollers that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage. In Read more about New – FreeRTOS Extended Maintenance Plan for Up to 10 Years[…]

Announcing AWS IoT Greengrass 2.0 – With an Open Source Edge Runtime and New Developer Capabilities

I am happy to announce AWS IoT Greengrass 2.0, a new version of AWS IoT Greengrass that makes it easy for device builders to build, deploy, and manage intelligent device software. AWS IoT Greengrass 2.0 provides an open source edge runtime, a rich set of pre-built software components, tools for local software development, and new Read more about Announcing AWS IoT Greengrass 2.0 – With an Open Source Edge Runtime and New Developer Capabilities[…]

New – AWS IoT Core for LoRaWAN to Connect, Manage, and Secure LoRaWAN Devices at Scale

Today, I am happy to announce AWS IoT Core for LoRaWAN, a new fully-managed feature that allows AWS IoT Core customers to connect and manage wireless devices that use low-power long-range wide area network (LoRaWAN) connectivity with the AWS Cloud. Using AWS IoT Core for LoRaWAN, customers can now set up a private LoRaWAN network Read more about New – AWS IoT Core for LoRaWAN to Connect, Manage, and Secure LoRaWAN Devices at Scale[…]

90%+ price reduction for AWS IoT Jobs, Globally Available

I have good news for AWS customers using the AWS IoT Device Management service. There has been a 90%+ price reduction for AWS IoT Device Jobs ! Let’s check out the new prices: What is IoT? IoT (Internet of Things) represents the billions (literally!) of physical devices around the world that are connected to the Read more about 90%+ price reduction for AWS IoT Jobs, Globally Available[…]

Learn about AWS Services & Solutions – February 2019 AWS Online Tech Talks

Join us this February to learn about AWS services and solutions. The AWS Online Tech Talks are live, online presentations that cover a broad range of topics at varying technical levels. These tech talks, led by AWS solutions architects and engineers, feature technical deep dives, live demonstrations, customer examples, and Q&A with AWS experts. Register Read more about Learn about AWS Services & Solutions – February 2019 AWS Online Tech Talks[…]

Learn about AWS Services & Solutions – January AWS Online Tech Talks

Happy New Year! Join us this January to learn about AWS services and solutions. The AWS Online Tech Talks are live, online presentations that cover a broad range of topics at varying technical levels. These tech talks, led by AWS solutions architects and engineers, feature technical deep dives, live demonstrations, customer examples, and Q&A with Read more about Learn about AWS Services & Solutions – January AWS Online Tech Talks[…]

Just-in-time VPN access with an AWS IoT button

Guest post by AWS Community Hero Teri Radichel. Teri Radichel provides cyber security assessments, pen testing, and research services through her company, 2nd Sight Lab. She is also the founder of the AWS Architects Seattle Meetup. While traveling to deliver cloud security training, I connect to Wi-Fi networks, both in my hotel room and in Read more about Just-in-time VPN access with an AWS IoT button[…]

Learn about New AWS re:Invent Launches – December AWS Online Tech Talks

Join us in the next couple weeks to learn about some of the new service and feature launches from re:Invent 2018. Learn about features and benefits, watch live demos and ask questions! We’ll have AWS experts online to answer any questions you may have. Register today! Note – All sessions are free and in Pacific Read more about Learn about New AWS re:Invent Launches – December AWS Online Tech Talks[…]

Amazon SageMaker Neo – Train Your Machine Learning Models Once, Run Them Anywhere

Machine learning (ML) is split in two distinct phases: training and inference. Training deals with building the model, i.e. running a ML algorithm on a dataset in order to identify meaningful patterns. This often requires large amounts of storage and computing power, making the cloud a natural place to train ML jobs with services such Read more about Amazon SageMaker Neo – Train Your Machine Learning Models Once, Run Them Anywhere[…]