AWS-IoT-Lens pdf free download

AWS-IoT-Lens pdf free download.AWS Well-Architected Framework.
One of the benefits of implementing loT solutions is the ability to gain deep insights and data about what’s happening in the local/edge environment. A primary way of realizing contextual insights is by’ implementing solutions that can process and perform analytics on loT data.
Storage Services
loT workloads are often designed to generate large quantities of data. You will want to ensure this discrete data is transmitted, processed, and consumed securely, while being stored durably.
Amazon S3 is object-based storage engineered to store and retrieve any amount of data from anywhere on the Internet. With Amazon S3, you can build loT applications that store large amounts of data for a variety of purposes:
regulatory, business evolution, metrics, longitudinal studies, analytics machine learning, and organizational enablement. Amazon S3 gives you a broad range of flexibility in the way you manage data for not just for cost optimization and latency, but also for access control and compliance.
Analytics and Machine Learning Services
Once your ToT data has reached a central storage location, you can begin to unlock the value of ToT by implementing analytics and machine learning on device behavior. With analytics systems, you can begin to operationalize improvements in your physical hardware by making data-driven decisions based on your analysis. With analytics and machine learning, ToT systems can implement proactive strategies like predictive maintenance or anomaly detection to improve the efficiencies of the system.
AWS JoT Analytics makes it easy to run sophisticated analytics on volumes on loT data. AWS loT Analytics manages the underlying loT data store while you can build different materialized views of your data using your own analytical queries or Jupyter notebooks.
Amazon Athena is an interactive quety service that makes it easy to analyze data in Amazon S3 using standard SQL Athena is serverless, so there is no infrastructure to manage, and customers pay only for the queries that they run.
Amazon SageMaker is a fully managed platform that enables you to quickly build, train, and deploy machine learning models in the cloud or down to the edge layer. With Amazon SageMaker, loT architectures can develop a model of historical device telemetry in order to infer future behavior.
Application Layer
One of the key value propositions of using AWS loT is provided by the ease with which data generated by loT devices can be consumed by other relevant cloud native capabilities. These connected capabilities include features from serverless computing, relational databases to create materialized views of your loT data, and management applications to operate, inspect, secure, and manage your JoT operations.
Management Applications
The purpose of management applications is to create scalable ways to operate your devices once they are deployed in the field. Common operational tasks such as inspecting connectivity state of a device, ensuring device credentials are configured correctly, and querying devices based on their current state must be in place prior to launch so that your system has the required visibility to troubleshoot applications.
AWS loT Device Defender is a fully managed service that audits your device fleets, detects abnormal device behavior, alerts you to security issues, and helps you investigate and mitigate commonly encountered ToT security issues.
AWS loT Device Management eases the organizing, monitoring, and managing of loT devices at scale. AWS JoT Device Management enables you to group devices for easier management. You can also enable real time search indexing against the current state of your devices through Device Management Fleet Indexing. Both Device Groups and Fleet Indexing can be used in conjunction with Over the Air Updates (OTA) in determining which target devices need to be updated.AWS-IoT-Lens pdf download.