Cloud Masters Episode #127
Amazon RDS performance optimization: Instance types, storage, and monitoring best practices
Learn how to optimize your Amazon RDS databases by understanding instance types, storage configurations, and monitoring strategies that prevent bottlenecks and reduce costs.
Cloud Masters Episode #127

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Cloud Masters
Cloud Masters
Amazon RDS performance optimization: Instance types, storage, and monitoring best practices
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Cloud Masters
Cloud Masters
Amazon RDS performance optimization: Instance types, storage, and monitoring best practices
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Episode notes

Key Moments

00:00: Introduction
00:57: Amazon RDS overview
03:19: Amazon Aurora overview
06:19: RDS vs Aurora decision framework
08:14: RDS Instance type optimization
10:45: RDS instance upgrades
13:50: Key RDS monitoring metrics
18:20: Storage bottlenecks in RDS
20:53: When to use each RDS storage option
26:16: Troubleshooting: IOPS bottleneck case study
31:48: Aurora storage mode options
35:20: Aurora storage mode selection
38:00: Understanding Aurora compatibility
39:17: Using Aurora Parallel Query for cache optimization
44:46: RDS performance best practices
51:38: RDS security considerations
53:07: DBAs in a managed service world
57:53: Evolving how you use RDS

Additional resources
Use this script to determine the optimal Aurora mode (Standard vs. I/O-optimized) for a cluster by comparing the costs of each mode based on its usage: Aurora mode cost calculator

About the guests

Kate Gawron
Kate is a Senior Database Cloud Architect at DoiT International with over 20 years experience working with AWS and Oracle databases. A published author of “AWS Database Specialty Exam Guide” and online “Practical Oracle Database Security” courses, Kate helps companies refactor their databases to work optimally with AWS and Google Cloud.
Pol Alzina
Pol is a Database Specialist at DoiT International, with over 10 years of expertise in optimizing and managing production databases on AWS. He has actively contributed to several open-source projects focused on enhancing database efficiency and automation. Pol helps organizations overcome performance challenges, optimize infrastructure, and reduce cloud costs to achieve peak performance.
Kate is a Senior Database Cloud Architect at DoiT International with over 20 years experience working with AWS and Oracle databases. A published author of “AWS Database Specialty Exam Guide” and online “Practical Oracle Database Security” courses, Kate helps companies refactor their databases to work optimally with AWS and Google Cloud.
Pol is a Database Specialist at DoiT International, with over 10 years of expertise in optimizing and managing production databases on AWS. He has actively contributed to several open-source projects focused on enhancing database efficiency and automation. Pol helps organizations overcome performance challenges, optimize infrastructure, and reduce cloud costs to achieve peak performance.

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