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Developing Stream Processing Applications with AWS Kinesis

Ivan Mushketyk

AWS Kinesis is a powerful, real-time, elastic, reliable service for stream processing. This course will teach you how to build modern stream processing applications using AWS Kinesis, stream processing services, and Big Data frameworks.

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AWS Kinesis is a powerful, real-time, elastic, reliable service for stream processing. This course will teach you how to build modern stream processing applications using AWS Kinesis, stream processing services, and Big Data frameworks.

The landscape of the Big Data field is changing. Previously, you could go away with processing incoming data for hours or even days. Now you need to do it in minutes or even seconds. These challenges require new solutions, new architectures, and new tools. AWS Kinesis is a service for stream processing that allows building applications that were impossible to create before. In the course, Developing Stream Processing Applications with AWS Kinesis, you'll learn the ins and outs of AWS Kinesis. First, you'll discover how it works, how to scale it up and down, and how to write applications using it. Next, you'll learn how to use a variety of tools to work with it, such as Kinesis Client Library, Kinesis Connector Library, Apache Flink, and AWS Lambda. Finally, you'll explore how to use more high-level Kinesis products such as Kinesis Firehose and how to write streaming applications using SQL queries with Kinesis Analytics. When you are finished with this course, you'll have an in-depth knowledge of AWS Kinesis that will help you to build your streaming applications.

AWS Kinesis is used to collect large streams of data in real time from hundreds of thousands of sources.

Using AWS Kinesis, this course will teach you how to build modern stream processing applications, stream processing services, and Big Data frameworks.

This course is for those with an intermediate knowledge of stream processing and those wanting to learn the ins and outs of AWS Kinesis.

It is encouraged that you have an understanding of AWS Kinesis and other services.

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What's inside

Syllabus

Course Overview
Kinesis Fundamentals
Reading and Writing Data to Kinesis
Developing Applications Using Kinesis Client Library
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Implementing Advanced Kinesis Consumers
Funneling Data with Kinesis Firehose
Implementing Stream Analysis Applications Using Streaming SQL
Kinesis in Production

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops expertise in AWS Kinesis, a service for stream processing
Taught by Ivan Mushketyk, a recognized expert in AWS Kinesis
Examines Kinesis, a highly relevant AWS service for stream processing
Suitable for learners who seek a thorough grounding in stream processing using AWS Kinesis
Intermediate knowledge of stream processing is assumed for this course
Assumes basic understanding of AWS Kinesis and related services

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Activities

Coming soon We're preparing activities for Developing Stream Processing Applications with AWS Kinesis. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Developing Stream Processing Applications with AWS Kinesis will develop knowledge and skills that may be useful to these careers:
Big Data Architect
As a Big Data Architect, you will design, develop, and manage big data systems that process and analyze large datasets. You may work on the design and implementation of data pipelines using AWS Kinesis, and use streaming SQL to analyze streaming data. Having a deep understanding of AWS Kinesis and stream processing technologies will be beneficial in this role.
Cloud Architect
As a Cloud Architect, you will design and implement cloud computing solutions. You may be responsible for designing and implementing solutions using AWS Kinesis and other AWS services. A comprehensive understanding of AWS Kinesis and stream processing can be helpful in this role.
Data Engineer
In this role, you will design, develop, and maintain data pipelines. You may work on the development of data pipelines using AWS Kinesis, and use streaming SQL to analyze streaming data. A deep understanding of AWS Kinesis and stream processing technologies can be beneficial in this role.
Data Analyst
As a Data Analyst, you will collect, analyze, and interpret data to support decision-making. You may use AWS Kinesis to collect and process streaming data, and use streaming SQL to analyze streaming data. This course can equip you with the skills to succeed in this role.
Data Scientist
As a Data Scientist, you will use data to solve business problems. You may use AWS Kinesis to collect and process streaming data, and use streaming SQL to analyze streaming data. Having a deep understanding of AWS Kinesis and stream processing technologies can help you in this role.
DevOps Engineer
As a DevOps Engineer, you will be responsible for the development and operation of software systems. You may be responsible for deploying and managing AWS Kinesis applications. Having a deep understanding of AWS Kinesis and stream processing technologies can be helpful in this role.
Enterprise Architect
As an Enterprise Architect, you will be responsible for the design and implementation of enterprise IT architectures. You may be responsible for designing and implementing solutions using AWS Kinesis and other AWS services. This course may help you build a foundation for this role.
Full Stack Engineer
As a Full Stack Engineer, you will be responsible for the development and maintenance of software systems. You may be responsible for developing and deploying AWS Kinesis applications. This course can equip you with the skills to succeed in this role.
Java Developer
As a Java Developer, you will be responsible for the development of software systems using the Java programming language. You may be responsible for developing AWS Kinesis applications. This course can equip you with the skills to succeed in this role.
Information Security Analyst
As an Information Security Analyst, you will be responsible for the security of IT systems. You may be responsible for securing AWS Kinesis applications. This course may help you build a foundation for this role.
Machine Learning Engineer
As a Machine Learning Engineer, you will be responsible for the development and deployment of machine learning models. You may use AWS Kinesis to collect and process streaming data for machine learning models. This course may help you build a foundation for this role.
Network Engineer
As a Network Engineer, you will be responsible for the design, implementation, and maintenance of computer networks. You may be responsible for deploying and managing AWS Kinesis applications. This course may help you build a foundation for this role.
Software Architect
As a Software Architect, you will be responsible for the design and implementation of software systems. You may be responsible for designing and implementing solutions using AWS Kinesis and other AWS services. This course may help you build a foundation for this role.
Product Manager
As a Product Manager, you will be responsible for the development and management of software products. You may be responsible for developing and launching products that use AWS Kinesis. This course may help you build a foundation for this role.
Systems Engineer
As a Systems Engineer, you will be responsible for the design, implementation, and maintenance of computer systems. You may be responsible for deploying and managing AWS Kinesis applications. This course may help you build a foundation for this role.

Reading list

We've selected five books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Developing Stream Processing Applications with AWS Kinesis.
Provides a comprehensive overview of Apache Kafka, a popular open-source stream processing platform. It covers the architecture, key concepts, and practical applications of Kafka.
Offers a comprehensive guide to designing and building data-intensive applications. It covers various aspects of data processing, storage, and analysis, providing valuable insights for understanding the challenges and best practices in this domain.
Focuses on optimizing Python code for performance, which is crucial in stream processing. It covers techniques for profiling, benchmarking, and optimizing Python applications, enabling readers to write efficient and scalable stream processing code.
Provides a comprehensive overview of Hadoop, a widely-used distributed computing platform for big data processing. It offers a good understanding of the ecosystem and techniques used in big data analytics, which can be helpful in understanding the context of stream processing.
Provides a solid foundation in distributed computing and data processing using MapReduce. While it is not directly related to stream processing, it offers valuable insights into the underlying principles and techniques used in many stream processing systems.

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