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Serverless Architectures with AWS

You're reading from   Serverless Architectures with AWS Discover how you can migrate from traditional deployments to serverless architectures with AWS

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789805024
Length 226 pages
Edition 1st Edition
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Author (1):
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Mohit Gupta Mohit Gupta
Author Profile Icon Mohit Gupta
Mohit Gupta
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Introduction to AWS

AWS is a highly available, reliable, and scalable cloud service platform offered by Amazon that provides a broad set of infrastructure services. These services are delivered on an "on-demand" basis and are available in seconds. AWS was one of the first platforms to offer the "pay-as-you-go" pricing model, where there is no upfront expense. Rather, payment is made based on the usage of different AWS services. The AWS model provides users with compute, storage, and throughput as needed.

The AWS platform was first conceptualized in 2002 and Simple Queue Service (SQS) was the first AWS service, which was launched in 2004. However, the AWS concept has been reformulated over the years, and the AWS platform was officially relaunched in 2006, combining the three initial service offerings of Amazon S3 (Simple Storage Service): cloud storage, SQS, and EC2 (Elastic Compute Cloud). Over the years, AWS has become a platform for virtually every use case. From databases to deployment tools, from directories to content delivery, from networking to compute services, there are currently more than 100 different services available with AWS. More advanced features, such as machine learning, encryption, and big data are being developed at a rapid pace. Over the years, the AWS platform of products and services has become very popular with top enterprise customers. As per current estimates, over 1 million customers trust AWS for their IT infrastructure needs.

AWS Serverless Ecosystem

We will take a quick tour of the AWS serverless ecosystem and briefly talk about the different services that are available. These services will be discussed in detail in future chapters.

Figure 1.4 shows the AWS serverless ecosystem, which is comprised of eight different AWS services:

  • Lambda: AWS Lambda is a compute service that runs code in response to different events, such as in-app activity, website clicks, or outputs from connected devices, and automatically manages the compute resources required by the code. Lambda is a core component of the serverless environment and integrates with different AWS services to do the work that's required.
  • Simple Storage Service (S3): Amazon S3 is a storage service that you can use to store and retrieve any amount of information, at any time, from anywhere on the web. AWS S3 is a highly available and fault-tolerant storage service.
  • Simple Queue Service (SQS): Amazon SQS is a distributed message queuing service that supports message communication between computers over the internet. SQS enables an application to submit a message to a queue, which another application can then pick up at a later time.
  • Simple Notification Service (SNS): Amazon SNS is a notification service that coordinates the delivery of messages to subscribers. It works as a publish/subscribe (pub/sub) form of asynchronous communication.
  • DynamoDB: Amazon DynamoDB is a NoSQL database service.
  • Amazon Kinesis: Amazon Kinesis is a real-time, fully managed, and scalable service.
  • Step Functions: AWS Step Functions make it easy to coordinate components of distributed applications. Suppose you want to start running one component of your application after another one has completed successfully, or you want to run two components in parallel. You can easily coordinate these workflows using Step Functions. This saves you the time and effort required to build such workflows yourself and helps you to focus on business logic more.
  • Athena: Amazon Athena is an interactive serverless query service that makes it easy to use standard SQL to analyze data in Amazon S3. It allows you to quickly query structured, unstructured, and semi-structured data that's stored in S3. With Athena, you don't need to load any datasets locally or write any complex ETL (extract, transform, and load), as it provides the capability to read data directly from S3. We will learn more about AWS Athena in Chapter 4, Serverless Amazon Athena and the AWS Glue Data Catalog.

    Here's a diagram of the AWS serverless ecosystem:

Figure 1.3 – The AWS Serverless Ecosystem
Figure 1.3 : The AWS serverless ecosystem Ecosystem
You have been reading a chapter from
Serverless Architectures with AWS
Published in: Dec 2018
Publisher: Packt
ISBN-13: 9781789805024
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