AWS IoT Core now supports a new IoT rule action to deliver messages from your devices directly to your Amazon Managed Streaming for Apache Kafka (“Amazon MSK”) or self-managed Apache Kafka clusters for data analysis and visualization, without writing a single line of code.  

Today, AWS and Grafana Labs launched the AWS IoT SiteWise plugin for Grafana. This plugin lets you easily visualize your AWS IoT SiteWise data in your Grafana dashboards. With this plugin, you can easily visualize and monitor your equipment data in near-real time using the wide range of visualization options in Grafana dashboards. You can also easily combine data from multiple sources (e.g., AWS IoT SiteWise, Amazon Timestream, Amazon CloudWatch) and monitor them all using a single Grafana dashboard. You can also embed these Grafana dashboards into your custom applications. 

AWS IoT SiteWise now supports data ingestion using ModBus TCP and EtherNet/IP (EIP) protocols. You can do so by adding Modbus or EIP devices as data sources to your SiteWise Gateway . For data ingestion from OPC-UA data sources, you can now customize the scan mode and scan rate along with specifying deadbands. Lastly, you can provide a custom AWS IoT Greengrass StreamManager stream as a destination for protocol data.

AWS introduces AWS IoT EduKit, an easy way to learn to build IoT applications using AWS services through a prescriptive learning program. AWS IoT EduKit helps developers – from students to experienced engineers and professionals – receive hands-on experience building end-to-end IoT applications by combining a reference hardware kit with a set of easy to follow guides and example code. To learn more, please visit AWS IoT EduKit .

Today, we are announcing the public preview of ML Detect, a new feature of AWS IoT Device Defender that automatically detects device-level operational and security anomalies across your fleet by learning from past data. Today, customers can use AWS IoT Device Defender’s Rules Detect to manually set static alarms. ML Detect makes this easier by automatically learning your fleet’s expected behavior using machine learning so that you don’t need an in-depth understanding of how your devices behave across a range of metrics to get started, like messages sent, disconnect frequency, and bytes in/out. Also, ML Detect automatically updates the expected behavior based on new data trends caused by seasonality and other changing factors. When an anomaly is detected, you can respond by choosing a built-in mitigation action like quarantining a device. 

You can now use AWS Launch Wizard to deploy new Active Directory (AD) infrastructure on Amazon EC2, or add domain controllers to an existing Active Directory hosted on Amazon EC2 or on-premises. AWS Launch Wizard uses AWS Well-Architected Framework to guide you through setting up your deployment on environment which includes setting up Amazon Virtual Private Clouds (Amazon VPCs), security groups, and AWS Identity and Access Management (AWS IAM) roles. AWS Launch Wizard reduces the time that it takes to set up an Active Directory infrastructure and deploy self-managed domain controllers.  

With Application Manager, a new capability in AWS Systems Manager, it is now easier to manage SQL Server workloads that are deployed using AWS Launch Wizard. Application Manager automatically imports SQL Server resources created by AWS Launch Wizard, and enables you to perform operational tasks such as database integrity checks, backup and restore, and index maintenance centrally from the Application Manager console.  

We are thrilled to announce AWS IoT Core for LoRaWAN, a fully managed capability 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, enterprises can now setup a private LoRaWAN network by connecting their own LoRaWAN devices and gateways to the AWS cloud – without developing or operating a LoRaWAN Network Server (LNS). This allows customers to eliminate the undifferentiated work and operational overhead of managing an LNS, and enables them to quickly connect and secure LoRaWAN device fleets at scale. AWS IoT Core for LoRaWAN also makes it easy to act on the data from connected devices using AWS services for processing, storage, analytics, or machine learning. With built-in integration with AWS IoT Rules Engine, AWS IoT Core for LoRaWAN automatically routes messages from connected LoRaWAN devices to customer defined rules, thus accelerating IoT application development. 

Today, we are announcing AWS IoT SiteWise Edge (Preview), a new feature of AWS IoT SiteWise providing software that runs on-premises at industrial sites and makes it easy to collect, process, and monitor equipment data locally before sending the data to AWS Cloud destinations. SiteWise Edge is installed on local hardware such as third-party industrial gateways and computers, or on AWS Outposts and AWS Snow Family compute devices. 

For customers using AWS Organizations, the AWS Personal Health Dashboard now provides an all-up view of Health events occurring across your organization. From a single aggregated dashboard, you can learn about maintenance events, security vulnerabilities, and AWS service degredations affecting any account in your AWS organization. Organizational View for the Personal Health Dashboard comes at no additional cost and does not require a premium AWS Support plan.