Book Image

Scalable Data Streaming with Amazon Kinesis

By : Tarik Makota, Brian Maguire, Danny Gagne, Rajeev Chakrabarti
Book Image

Scalable Data Streaming with Amazon Kinesis

By: Tarik Makota, Brian Maguire, Danny Gagne, Rajeev Chakrabarti

Overview of this book

Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale. Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you’ll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk. By the end of this AWS book, you’ll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).
Table of Contents (13 chapters)
1
Section 1: Introduction to Data Streaming and Amazon Kinesis
5
Section 2: Deep Dive into Kinesis
10
Section 3: Integrations

Third-party integrations with Kinesis

In this section, we are going to learn how to integrate Kinesis with third-party software provider Splunk. Although we are using Splunk to show how we can work around some of the integration intricacies, this approach is applicable to other third-party integrations.

Firehose delivery is possible for generic HTTP endpoints. This enables us to use Firehose, a fully managed service, to send data to HTTP endpoints, and it opens doors for other integration points, including our own applications.

Splunk

If you are not familiar with Splunk, you should still read this section as we will cover some of the nuances of Lambda processing that are applicable, regardless of whether the delivery endpoint is for Splunk or not. We covered Firehose and Splunk integration in depth in Chapter 5, Kinesis Firehose, in the Amazon Kinesis Data Firehose Destinations/Splunk destination section.

Splunk's website defines the software as follows: "Splunk...