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Optimize your Amazon RDS and Aurora PostgreSQL workloads

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Optimize your Amazon RDS and Aurora PostgreSQL workloads
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Do you want to optimize your Amazon RDS and Aurora PostgreSQL workloads? Explore these handpicked resources for the best practices to optimize your Amazon RDS and Aurora PostgreSQL workloads.
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AnalyticsMigration & ModernizationDatabase
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Aurora PostgreSQLAmazon Relational Database Service
AWS OFFICIALUpdated 3 years ago510 views

Aurora PostgreSQL Query Plan Management feature

Use Query Plan Management (QPM) to manage the query execution plans generated by the optimizer for your SQL applications. QPM solves the problem of plan instability.

Introduction to Aurora PostgreSQL Query Plan Management

This AWS Database blog provides an introduction and quick start guide for QPM.

Managing query execution plans for Aurora PostgreSQL

See this AWS Documentation for a deep dive on QPM, including the best practices for QPM, capturing execution plans, and using managed plans.

Amazon Aurora PostgreSQL wait events

Use wait events as a tool to tune your Aurora PostgreSQL workloads. If you can determine the causes of the top wait events, you can sometimes make changes that improve performance.

Amazon Aurora PostgreSQL wait events

This AWS Documentation lists the common wait events for Aurora PostgreSQL.

Tuning with wait events for Aurora PostgreSQL

Follow this AWS Documentation to find out why sessions are waiting for resources and what they are doing. Then, find the possible causes and corrective actions.

Amazon Aurora PostgreSQL parameter configuration

Understand and use parameters to tune the memory utilization of your Aurora PostgreSQL workloads.

Amazon Aurora PostgreSQL parameters, part 1: Memory and query plan management

This blog covers parameters that you can use to tune the memory utilization of Aurora PostgreSQL and parameters that help control the behavior of the QPM feature.

Amazon Aurora PostgreSQL parameters, part 2: Replication, security, and logging

This blog explains the parameters related to replication, security, and logging.

Amazon Aurora PostgreSQL parameters, part 3: Optimizer parameters

This blog discusses Aurora PostgreSQL optimizer parameters that can improve the performance of queries.

Amazon Aurora PostgreSQL parameters, part 4: ANSI compatibility options

This blog covers parameters which can align Aurora PostgreSQL closer to American National Standards Institute (ANSI) standards and reduce the migration effort when migrating from commercial engines.

Connection pooling

Use Amazon RDS Proxy to bring efficiencies in your Amazon Aurora PostgreSQL workloads and make your applications more scalable, more resilient to database failures, and more secure.

Set up highly available PgBouncer and HAProxy with Amazon Aurora PostgreSQL readers

This blog explains a process to bring efficiencies in your Amazon Aurora PostgreSQL workloads to overcome observed inefficiencies with even distribution of connections over a pool of reader nodes.

Improving application availability with Amazon RDS Proxy

This blog describes how RDS Proxy insulates clients from reader-writer transition issues and overcomes sub-optimal client configurations. It discusses RDS Proxy benefits for failovers.

Use Amazon RDS Proxy with read-only endpoints

This post explains how RDS Proxy read-only endpoints can help you achieve read scalability of your read-heavy workloads with connection pooling and how to improve availability for your applications.

Using Amazon RDS Proxy

This AWS Documentation covers using RDS Proxy, including its limitations, core concepts, monitoring, troubleshooting, and more.

Vacuum for performance

Use the vacuum to optimize the performance of your Aurora PostgreSQL workloads.

PostgreSQL documentation for pg_stat_all_tables

The pg_stat_user_tables view contains the information on live tuple, dead tuples, and more. Checking the n_dead_tup column provides information about the dead tuple count.

PostgreSQL documentation for pgstattuple

The pgstattuple returns a relation's physical length, percentage of “dead” tuples, and other information. This can help you to determine if a vacuum is necessary or not.

PostgreSQL documentation for VACUUM

Vacuum reclaims storage occupied by dead tuples. In normal PostgreSQL operation, tuples that are deleted or obsoleted by an update aren't physically removed from their table.

Working with the PostgreSQL autovacuum on Amazon RDS for PostgreSQL

This documentation provides information about the autovacuum and how to tune some of its parameters on your RDS for PostgreSQL DB instance.

Understanding autovacuum in Amazon RDS for PostgreSQL environments

This blog discusses the autovacuum process and its importance. It also covers tuning autovacuum settings for better performance and the disadvantages of turning it off.

Parallel vacuuming in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL

This blog covers how parallel vacuuming works in Amazon RDS for PostgreSQL, which is a feature that was introduced in PostgreSQL 13.

Remove bloat from Amazon Aurora and RDS for PostgreSQL with pg_repack

This blog shows you how to identify and remove bloat from tables in Amazon RDS for PostgreSQL or Aurora PostgreSQL using manual operations, such as VACUUM and VACUUM FULL.
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