One of the newest sets of services that Amazon is offering is the Internet of Things or IoT. If you are working with IoT, Lynn Langit recommends using Amazon’s Amazon’s reference architecture, the Pragma architecture. To help you get started thinking about cloud service needs around IT solutions, Lynn Langit will guide you through Amazon’s Big Data backend architecture for the Internet of Things.
- [Voiceover] One of the newest sets…of services that Amazon's offering…is for Internet of Things or IoT.…So let's get started working with IoT.…Because IoT on the cloud is really completely new,…not only at Amazon but for the competitors…and for almost every customer,…it's just a new set of services.…Amazon's been really great about…communicating reference architectures.…This is what's called their Pragma Architecture…and you'll see more on the link below.…So to get us started thinking…about cloud service needs around IoT solutions,…they provide us with this reference.…
So on the left side you'll see small thing or things,…and those are the IoT devices,…and they're really sending two types of messages,…that you're going to design cloud architectures…to receive and process.…The first is on what they call the Speed Layer,…and this is the near real-time.…So this is the commands coming back to the device…and let's just make a specific example…so it's easier to understand,…let's pretend it's a thermostat you control…
Author
Lynn Langit
Released
7/18/2016Starting with top-level categories of storage, data, computer, and services, Lynn guides you through planning your ideal AWS architecture, providing service demos using the AWS Console, command-line interface, and other tools. Learn when to use which service for which business case, such as Docker or Lambda or DynamoDB or Aurora? She shows how to script creation of services such as S3 buckets and EC2 instances, create and populate a managed data warehouse, and develop a data processing pipeline that works for you. Chapter 6 covers the AWS Internet of Things (IoT) services.
These exercises can help you build proof-of-concepts, minimum viable products, and deployable solutions to scale and support big data initiatives at your company.
- Setting up your AWS account
- Using AWS tools
- Defining your minimum viable products
- Choosing computer, storage, and data services
- Using S3, EC2, or Docker for website hosting
- Developing an AWS website
- Using a data warehouse
- Developing a data processing pipeline
- Developing an Internet of Things project with AWS
Skill Level Intermediate
Duration
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Introduction
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Welcome42s
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Exercise files1m 21s
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Knowledge checks23s
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1. Start Your AWS Project
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Set up AWS accounts7m 23s
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Set up cost management3m 11s
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Knowledge check21s
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2. Plan Your AWS Architecture
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Define your MVP2m 10s
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Choose services: Compute11m 51s
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Choose services: Storage11m 55s
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Choose services: Data7m 17s
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Knowledge check21s
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3. Develop the AWS Website
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Use S3 for website hosting4m 23s
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Use EC2 for website hosting7m 55s
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Add RDS Aurora database7m 18s
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Knowledge check22s
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4. Develop the AWS Data Warehouse
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Why use a data warehouse?6m 24s
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Use Redshift6m 33s
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Run a baseline query3m 35s
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Use BIME for visualization1m 42s
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Knowledge check22s
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5. Develop AWS Data Processing Pipeline
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Why use data streaming?6m 28s
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Knowledge check21s
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6. Develop AWS IoT Project
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Understand IoT concepts5m 19s
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Knowledge check22s
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Conclusion
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Next steps33s
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Video: Understand IoT concepts