Amazon Aurora: Best Practices

Amazon Aurora has revolutionized relational databases. This course will teach you everything you need to know about Amazon Aurora’s amazing superiority over other RDBMS and how to work with it using best practices.
Course info
Level
Advanced
Updated
Oct 7, 2020
Duration
3h 59m
Table of contents
Course Overview
Understanding Amazon Aurora's Amazing Architecture
Introducing Amazon Aurora's Resulting Feature Improvements
Building and Launching Amazon Aurora Clusters
Managing and Maintaining Amazon Aurora Clusters
Securing Amazon Aurora
Logging, Monitoring, and Auditing Amazon Aurora Clusters
Exploring Amazon Aurora's Unique Backup and Restore Strategies
Examining Amazon Aurora Data Migration Strategies
Designing Amazon Aurora Test Environments
Troubleshooting Amazon Aurora
Recognizing Amazon Aurora's Extended Capabilities
Description
Course info
Level
Advanced
Updated
Oct 7, 2020
Duration
3h 59m
Description

Amazon Aurora is a relational database built for the cloud. In this course, Amazon Aurora: Best Practices, you’ll learn to leverage Aurora’s scalability, high performance, high availability, durability, and security while taking advantage of the management tasks that are managed for you. First, you’ll explore the architectural improvements that make Aurora a cut above the competition. Next, you’ll discover the feature improvements that this architecture enables, as well as how to efficiently and effectively design, deploy, access, monitor, use, and maintain Amazon Aurora clusters to improve performance, reduce costs, and jumpstart data transformation and innovation. Finally, you’ll learn how to utilize advanced functionalities like data migration, schema conversion, and troubleshooting techniques. When you’re finished with this course, you’ll have the skills and knowledge of Amazon Aurora needed to utilize AWS’s relational database for traditional relational database functionalities, and also know what it can for machine learning and artificial intelligence.

Course FAQ
Course FAQ
What is Amazon Aurora?

Amazon Aurora is a relational database service offered by AWS.

What will I learn in this Amazon Aurora course?

In this course, you will learn how Aurora works, how to connect to the different endpoints, how to use automated backups, automated and manual monitoring tools, and machine learning capabilities.

What is AWS?

Amazon Web Services (AWS) is a cloud platform that offers over 175 services to individuals and organizations.

Is Amazon Aurora Serverless?

Amazon Aurora's serverless offering acts as an "on-demand", auto scaling configuration where the database will start up, shut down, and scale to the appropriate capacity based on your application's needs.

What are some benefits of learning amazon aurora?

Some of the benefits of learning Amazon Aurora is that it is a relational database provided from AWS and that the engine is compatible with MySQL. Aurora is cost-effective, Highly scalable, and easy to use.

About the author
About the author

Kim Schmidt is an AWS Partner & Vendor. She's worked for or with Dun & Bradstreet, Google, Microsoft, & AWS. Kim is currently writing a book "Artificial Intelligence & Analytics on AWS."

More from the author
Serverless Analytics on AWS
Intermediate
2h 40m
Aug 20, 2019
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone, my name is Kim Schmidt, and welcome to my course, Amazon Aurora: Best Practices. I am an AWS Data and AI expert at DataLeader. Amazon Aurora is a true relational database paradigm shift, and you don't drive a Maserati at 50 miles an hour. What new technology like Aurora does is create new opportunities to do a job that customers want done, and knowing the feature improvements Aurora has will grant you the knowledge to take full advantage of Aurora's power. Aurora supports MySQL, PostGreSQL, and serverless engines, each with different use cases. Amazon Aurora's high performance is achieved by its amazing architectural improvements. Aurora is AWS's relational database of choice, not just for its improved relational capabilities, but also for analytical and machine learning capabilities. Some of the major topics that we'll cover include how Aurora's new SSD‑based, fault tolerant, self‑healing, log‑structured storage creates six copies of your data spread across three availability zones that continually, incrementally, and asynchronously backs up to S3; how to connect to the different endpoints in Aurora cluster of database instances and when to use each one; how to use Aurora's automated backups, snapshots, cloning, and backtracking for backup and restoration; how to work with automated and manual monitoring tools and about monitoring Aurora using Amazon Alexa; and about Aurora's machine learning capabilities and its integrations with other state‑of‑the‑art AWS services. Before beginning the course, you should be familiar with common on‑prem and in‑cloud database technologies with hands‑on experience working with AWS. I hope you'll join me on this amazing journey to learn about the relational database built for the cloud with the Amazon Aurora: Best Practices course at Pluralsight.