Amazon Aurora Monitoring Tool

Optimize Aurora database engine performance with 24/7 monitoring

Fully functional for 30 days

Identify problems fast with Amazon Aurora monitoring

Maintaining Aurora performance means catching and resolving problems before they can have a serious impact. SolarWinds^® Database Observability offers 24/7 Aurora monitoring with both real-time and historical analysis to help you catch even the smallest problems as soon as they arise. Database Observability measures warnings, latency, errors, execution plans, throughput, and more to help you identify and address potential issues before they become outages.

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Fully functional for 30 days

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Collect and compare key Aurora metrics

SolarWinds Database Observability is built to collect more than 10,000 metrics a second from your systems. It collects key metrics tied to performance, errors, connections, and more, offering you the ability to view and compare individual metric. Go from a global view of your whole Aurora database engine to a granular view of a single metric within seconds.

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Visualize Aurora data with ease

Database Observability collects data about your Aurora database engine and makes the data easily accessible through intuitive dashboards through both pre-set and customizable charts. We present data graphically wherever possible to see outliers and metrics that might need your attention. Share your custom views with your entire team thanks to a full-set of collaboration tools.

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Get More on Aurora Monitoring

Do you find yourself asking…

What is Amazon Aurora?
How do you monitor Amazon Aurora performance?
How does Aurora work?
How does Aurora monitoring work in Database Observability?

What is Amazon Aurora?

Amazon Aurora is a fully managed relational database engine available as part of the Amazon Relational Database Service (RDS) from Amazon Web Services (AWS). Amazon RDS is a managed database service that simplifies the process of setting up, operating, and scaling a relational database in the cloud. It takes stress out of the many database management tasks that would otherwise take up a huge amount of time for an IT admin.

Aurora offers the simplicity and cost-efficiency of an open-source database while also providing the high-quality security, reliability, and availability you can expect from an enterprise-grade database. In fact, according to Amazon, Aurora can deliver as much as three times the throughput of PostgreSQL and up to five times the throughput of MySQL. Its database engines are customized to leverage rapid distributed storage to ensure fast response times. As with any database solution, it requires constant Aurora cloud monitoring to ensure optimal performance.

Amazon Aurora is a pay-as-you-go service and doesn’t come with any upfront fees. It has two different pricing structures depending on whether you use the MySQL-compatible version or the PostgreSQL-compatible version. Within those categories, you can choose if you want to invest in the standard instances option or the memory-optimized instances option. Aurora is highly scalable, making it a viable option for organizations that may grow in the future.

How do you monitor Amazon Aurora performance?

Amazon Aurora monitoring is critical for maintaining the performance and reliability of your database engine. Aurora cloud monitoring consists of continuously collecting and analyzing data from the database engine, so you can better identify and resolve problems as they arise.

When it comes to Aurora monitoring, there are several key categories of metrics you need to track. When any of these metrics fall outside their expected values, they can indicate a problem within the system that could lead to a deterioration in performance and reliability. The more closely you monitor the metrics, the faster you’ll be able to identify a potential problem, and the faster you’ll be able to address it.

The metric categories to keep an eye on:

Query throughput: Check to ensure your queries are being executed. Use Amazon CloudWatch Aurora to monitor the breakdown of read and write commands and identify potential bottlenecks.

Query performance: This includes metrics like latency—a critical database data point. Any instances of latency can lead to serious slowdowns and bottlenecks if they aren’t addressed as soon as they arise.

Resource utilization: Aurora needs four fundamental resources: memory, CPU, network, and disk. Any one of these can become a performance bottleneck if it isn’t being utilized properly. These metrics are usually the first place to turn if any database instances start having performance problems.

Connection: Aurora has a configurable connection limit, but you always want to make sure your max connections aren’t too low or too high.

CloudWatch Aurora metrics: You can obtain several metrics through Amazon CloudWatch. These include metrics related to RAM to help you ensure your working set resides almost completely in memory. When it doesn’t, your speeds are exponentially reduced, so you want to keep a close eye on metrics like BufferCacheHitRatio and BufferCacheHitRatio to make sure you have enough RAM allocated to Aurora.Tracking all these metrics manually can be a challenge. That’s why effective Aurora monitoring requires investment in a quality Aurora cloud monitoring tool designed to track all these metrics for you, aggregating and analyzing them, so you can easily see where the values indicate a potential problem.

What is Amazon Aurora?
Amazon Aurora is a fully managed relational database engine available as part of the Amazon Relational Database Service (RDS) from Amazon Web Services (AWS). Amazon RDS is a managed database service that simplifies the process of setting up, operating, and scaling a relational database in the cloud. It takes stress out of the many database management tasks that would otherwise take up a huge amount of time for an IT admin.
Aurora offers the simplicity and cost-efficiency of an open-source database while also providing the high-quality security, reliability, and availability you can expect from an enterprise-grade database. In fact, according to Amazon, Aurora can deliver as much as three times the throughput of PostgreSQL and up to five times the throughput of MySQL. Its database engines are customized to leverage rapid distributed storage to ensure fast response times. As with any database solution, it requires constant Aurora cloud monitoring to ensure optimal performance.
Amazon Aurora is a pay-as-you-go service and doesn’t come with any upfront fees. It has two different pricing structures depending on whether you use the MySQL-compatible version or the PostgreSQL-compatible version. Within those categories, you can choose if you want to invest in the standard instances option or the memory-optimized instances option. Aurora is highly scalable, making it a viable option for organizations that may grow in the future.

Optimize database performance with an Aurora monitoring

SolarWinds Observability SaaS

Gain 24/7 Aurora monitoring for real-time and historical analysis.
Leverage best practice recommendations for Aurora query and database optimization.
View an intuitive interface with customizable graphs and charts.

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Fully functional for 30 days

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