Application Development Approaches in AWS (webinar slides)

The ways you can engage AWS to run applications in the cloud are numerous: traditional application deployments on an EC2 virtual machine, containerized applications running on ECS or Kubernetes, or fully serverless. Chariot’s Ken Rimple, director of Training/Mentoring Services, will take you through some sample architectures and the pros/cons of complexity, cost, and technical considerations for each one.

IoT on AWS – Connecting to IoT Core

AWS IoT provides connectivity to IoT devices through HTTP and MQTT. In this session we learn how to leverage AWS Core IoT as an MQTT broker, how to connect your devices using a client certificate, how policies can enforce data security, and how rules are used to move data elsewhere in the AWS infrastructure.

By Ken Rimple, Director of Training/Mentoring Services, Chariot Solutions

IoT on AWS – Intro to Kinesis

While IoT Core can route your device messages directly to subscribers, you gain flexibility, scalability and reliability when you put a Kinesis stream in the data path. Kinesis is a persistent data log that accepts messages from multiple producers, buffers them for up to a week, and allows multiple consumers to read them.

By Keith Gregory, AWS Practice Lead at Chariot Solutions

This talk will cover the high-level design of Kinesis, how it scales, how clients can retrieve records that have been stored in it, and the use of Kinesis Analytics to to transform data and extract outliers.

IoT on AWS – Coping with Aging (Data)

Data has different purposes over time: when fresh, it can be used for real-time decision-making; as it ages, it becomes useful for analytics; eventually, it becomes a record, useful or perhaps not. Each of these stages requires a different approach to storage and management, and this talk looks at appropriate ways to work with your data at the different stages of its life.

By Keith Gregory, AWS Practice Lead at Chariot Solutions

IoT on AWS – That’s Not A Data Lake…

This talk will review two common use cases for the use of captured metric data: 1) Real-time analysis, visualization, and quality assurance, and 2) Ad-hoc analysis. Once metric data is generated, to support the use cases mentioned above it must be ingested properly using a robust and fault-tolerant streaming framework. The most common open source streaming options will be mentioned however this talk be concerned with Apache Flink specifically. A brief discussion of Apache Beam will also be included in the context of the larger discussion of a unified data processing model.

Best practices around data persistence will be discussed. An attempt will be made to eliminate confusion about the format data should take when it is ‘at rest’. Different serialization formats will be compared and discussed in context with the most typical analysis use cases. Finally fully managed solutions such as AWS Data Lake will be mentioned briefly. We will discuss their relative advantages and disadvantages.

By Eric Snyder, Software Architect at Chariot Solutions

IoT on AWS – Amplify Mobile Applications and Device Shadows

In this session we will walk through the steps required to securely communicate with your device using the Device Shadow service. This will include an overview of user authentication and authorization, connecting to AWS IoT, and using MQTT to communicate with the device’s “Device Shadow” to read and update its state. All this, using the AWS Amplify CLI and SDK.

By Steve Smith, Mobile Practice Lead at Chariot Solutions

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