AWS RDS Postgres monitoring - definition & overview

As with other database monitoring systems and procedures, Postgres monitoring for AWS RDS DB instances helps to ensure their reliability, availability, and performance. AWS monitoring is an automatic procedure that may be performed every five minutes or 60 seconds depending on your need.

The Amazon Web Service (AWS) Relational Database Service is a program that enables users to create, scale, manage, and generally operate collections of interrelated datasets within the Amazon Cloud. A DB instance is an “isolated database environment running in the cloud.” In other words, it is a discrete data system that exists as a basic component of RDS and can include either a single or multiple databases on which users can run their cloud-based applications.

Users can engage the engine of their choice to operate a DB instance. Each involves unique features and parameters which help the database run according to the functionality of that language. AWS currently allows five languages, including:

• MySQL, 40 instances enabled.
• MariaDB, 40 instances enabled.
• PostgreSQL, 40 instances enabled.
• Oracle, 10 instances enabled with pre-existing license model, 40 enabled with the bring-your-own-license model.
• Microsoft SQL Server, 10 instances enabled with the preexisting license model.

RDS additionally enables 10 instances for SQL Server bases including the Enterprise, Standard, Web, and Express editions.

Amazon RDS easily connects to PostgreSQL databases which can then export logs to Amazon CloudWatch for easy reference of instance metrics. This helps to debug multipoint failures, and collect data across all parts of the AWS solution.

Tracking these vital insights will help you to understand the current health of your DB instances, avoid critical failures, and maintain optimal functionality at all times.

1. High CPU or RAM consumption
   Especially if you are running multiple servers, instances, or databases within an instance, it is important to track the speed, performance, and volume of your memory, and S + P of your CPU as both of these directly correlate to the overall performance of your greater instance. Inadequate performance of either will drastically slow response time and can lead to application crashes.
2. Disk space consumption
   Growing databases will be “crushed” if adequate space is not allowed for new incoming datasets. Monitoring this metric lets you know if and when you need to scale your database to make room for more data. AWS allows you to enable auto-scaling for your DB instances. However, this does represent an additional cost to you.
3. Network traffic
   Monitoring this metric can help you determine if an instance’s poor performance is external versus internal. Poor or diminished network traffic may indicate the database is inaccessible due to a misconfiguration or potentially an attack.
4. DB connections, DB load
   Each instance allows for a limited amount of internal DB connections. When that limit is reached, RDS will automatically reject any input which follows. Tracking the number of connections against the DB instance’s capacity (load) allows you to avoid catastrophic data loss, and understand when you need to scale up or create a new database.
5. IOPS metrics
   Your read/ write IOPS (instance operations per second) can harm application performance, slowing or completely stalling activity if there are too few. However, you are billed based on IOPS volume and too many IOPS can result in an extraordinary price tag on operations. You should understand what IOPS level is optimal for your application and maintain that level for the best performance at cost.

Here are a few key tools to help you track top metrics and manage your DB instances.

• Instance status
  Automatic status checks examine the overall performance of your DB instances and return failed status checks with specific messaging if an issue is found. These messages will state either Ok, Warning, Impaired, or Insufficient Data to indicate performance and potential problems.
• RDS recommendations
  This AWS RDS feature examines your custom and automatic parameters against performance data and other information and generates a suggested course of action or possible configurations to help your application and DB instance run at optimum capacity.
• Performance insights
  This tool provides a quick-reference dashboard of all key metrics relating to your DB instance to help you quickly assess potential problems and take action where necessary.
• Enhanced monitoring
  If you need to track how new processes impact performance, use this tool to track DB instance performance metrics in real-time.
• CloudWatch
  This AWS service intakes data from PostgreSQL logs and generates informational insights to allow you to better understand, troubleshoot, and manage your DB instances. You can also use CloudWatch to set up monitoring alerts based on custom parameters and automate responses.
• EventBridge
  This tool is an AWS event pipeline that more easily allows you to track events from your cloud-based application.
• CloudTrail
  Another native AWS service that automatically tracks events, activities, and other data from multiple DB instances existing within a single account for comparative and big-picture reference.
  
  

Amazon has everything you need, both on and offline. Monitoring your AWS applications may be done exclusively from the Amazon Cloud, but this means finding, learning, and using every component Amazon has to offer. Or, you can choose a third-party application to do it for you.

Sumo Logic is the first enterprise-grade, cloud-based monitoring service that helps you manage and analyze collected data and provide real-time insight on operational or security concerns on all your cloud and internet-connected applications.

And Sumo Logic seamlessly integrates with Amazon AWS, making monitoring and managing your database instance even easier and more intuitive.

Learn more about Sumo Logic's AWS RDS Monitoring solution.