Amazon RDS Performance Insights

Score9 out of 10

3 Reviews and Ratings

What is Amazon RDS Performance Insights?

Amazon RDS Performance Insights is a database performance tuning and monitoring feature that helps to asess the load on a database, and determine when and where to take action. Performance Insights helps non-experts to detect performance problems with a dashboard that visualizes database load.

Performance Insights uses lightweight data collection methods that don’t impact the performance of your applications, and makes it easy to see which SQL statements are causing the load, and why. It requires no configuration or maintenance, and is currently available for Amazon Aurora (PostgreSQL- and MySQL-compatible editions), Amazon RDS for PostgreSQL, MySQL, MariaDB, SQL Server and Oracle.

With seven days of free performance history retention, users can track down and solve a variety of issues. The Amazon Web Services API and SDK enables integration of Performance Insights into on-premises and third-party monitoring tools. For longer-term retention, the user can choose to pay for up to two years of performance history retention.

Performance Insights is started from the Amazon RDS Management Console, where the user can enable Performance Insights when creating or modifying an instance of a supported RDS engine. From the Performance Insights dashboard, the user can start monitoring performance.

Categories & Use Cases

Database Performance Monitoring

Fabricio Zubelli

DevOps Engineer in Engineering at Kea (51-200 employees employees)

Use Cases and Deployment Scope

We leverage Amazon RDS Performance Insights to better understand the load on our Postgres RDS instance and to find queries or jobs with room for improvement in regards to performance. Amazon RDS Performance Insights also brings a lot of out of the box metrics and data that help us make decisions on how to break our DB management and how to scale it.

Pros

RDS Infrastructure Metrics
RDS Logical Metrics
Real time visualization of query load
Identify Performance Bottlenecks
Historical Performance Analysis of load

Cons

Easier way to identify to which service the query comes from
Easier way to identify correlation between metrics
More customization, right now it is too restricted
The interval could be smaller between data points for peaks of usage

Return on Investment

Help Optimize Query and app performance
Help better plan capacity for the DB
Improved the company capacity on troubleshooting problems in DBs

Alternatives Considered

Prometheus and Datadog

Other Software Used

Datadog, HashiCorp Vault, Amazon Redshift