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November 27, 2018 By Nitin Pande

Complete Visibility of Amazon Aurora Databases with Sumo Logic

Sumo Logic provides digital businesses a powerful and complete view of modern applications and cloud infrastructures such as AWS. Today, we’re pleased to announce complete visibility into performance, health and user activity of the leading Amazon Aurora database via two new applications – the Sumo Logic MySQL ULM application and the Sumo Logic PostgreSQL ULM application.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database available on the AWS RDS platform. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases.

By providing complete visibility across your Amazon Aurora databases with these two applications, Sumo Logic provides the following benefits via advanced visualizations:

  1. Optimize your databases by understanding query performance, bottlenecks and system utilization
  2. Detect and troubleshoot problems by identifying new errors, failed connections, database activity, warnings and system events
  3. Monitor user activity by detecting unusual logins, failed events and geo-locations

In the following sections of this blog post, we discuss details how these applications provide value to customers.

Amazon Aurora Logs and Metrics Sources

Amazon provides a rich set of log and metrics sources for monitoring and managing Aurora databases.

The Sumo Logic Aurora MySQL ULM app works on the following three log types:

  • AWS CloudTrail event logs
  • AWS CloudWatch metrics
  • AWS CloudWatch logs

For Aurora MySQL databases, error logs are enabled by default to be pushed to CloudWatch. Aurora MySQL also supports slow query logs, audit logs, and general logs to be pushed to CloudWatch, however, you need to select this feature on CloudWatch.

The Sumo Logic Aurora PostgreSQL ULM app works on the following log types:

  • AWS Cloud Trail event logs
  • AWS CloudWatch metrics

For more details on setting up logs, please check the documentation for the Amazon Aurora PostgreSQL app and the Amazon Aurora MySQL app.

Installing the Apps for Amazon Aurora

Analyzing each of the above logs in isolation to debug a problem, or understand how your database environments are performing can be a daunting and time-consuming task. With the two new Sumo applications, you can instantly get complete visibility into all aspects of running your Aurora databases.

Once you have configured your log sources, the Sumo Logic apps can be installed. Navigate to the Apps Catalog in your Sumo Logic instance and add the “Aurora MySQL ULM” or “Aurora PostgreSQL ULM” apps to your library after providing references to sources configured in the previous step.

Optimizing Database Performance

As part of running today’s digital businesses, customer experiences is a key outcome and towards that end closely monitoring the health of your databases is critical.

The following dashboards provide an instant view on how your Amazon Aurora MySQL and PostGreSQL databases are performing across various important metrics. Using the queries from these dashboards, you can build scheduled searches and real-time alerts to quickly detect common performance problems.

The Aurora MySQL ULM Logs – Slow Query Dashboard allows you to view log details on slow queries, including the number of slow queries, trends, execution times, time comparisons, command types, users, and IP addresses.

The Aurora MySQL ULM Metric – Resource Utilization Monitoring dashboard allows you to view analysis of resource utilization, including usage, latency, active and blocked transactions, and login failures.

The Aurora PostgreSQL ULM Metric – Latency, Throughput, and IOPS Monitoring Dashboard allows you to view granular details of database latency, throughput, IOPS and disk queue depth. It is important to monitor the performance of database queries. Latency and throughput are the key performance metrics.

Detect and Troubleshoot Errors

To provide the best service to your customers, you need to take care of issues quickly and minimize impacts to your users. Database errors can be hard to detect and sometimes surface only after users report application errors.

The following set of dashboards help quickly surface unusual or new activity across your AWS Aurora databases.

The Aurora MySQL ULM Logs – Error Logs Analysis Dashboard allows you to view details for error logs, including failed authentications, error outliers, top and recent warnings, log levels, and aborted connections.

Monitor user activity

With cloud environments, its becoming even more critical to investigate user behavior patterns and make sure your database is being accessed by the right staff.

The following set of dashboards track all user and database activity and can help prioritize and identify patterns of unusual behavior for security and compliance monitoring.

The Aurora MySQL ULM Logs – Audit Log Analysis Dashboard allows you to view an analysis of events, including accessed resources, destination and source addresses, timestamps, and user login information. These logs are specifically enabled to audit activities that are of interest from an audit and compliance perspective.

The Aurora MySQL Logs – Audit Log SQL Statements Dashboard allows you to view details for SQL statement events, including Top SQL commands and statements, trends, user management, and activity for various types of SQL statements. You can drill deeper into various SQL statements and commands executed by clicking on the “Top SQL Commands” panel in the dashboard. This will open up the Aurora MySQL ULM – Logs – Audit Log SQL Statements dashboard, which will help with identifying trends, specific executions, user management activities performed and dropped objects.

The Aurora PostgreSQL ULM CloudTrail Event – Overview Dashboard allows you to view details for event logs, including geographical locations, trends, successful and failed events, user activity, and error codes. In case you need to drill down for details, the CloudTrail Event – Details dashboard will help you with monitoring the most recent changes made to resources in your Aurora database ecosystem, including creation, modification, deletion and , reboot of Aurora clusters and or instances.

Get Started Now!

The Sumo Logic apps for Amazon Aurora helps optimize, troubleshoot and secure your AWS Aurora database environments.

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Nitin Pande

Nitin Pande is a solutions architect at Sumo Logic with over 15 years of experience in developing and deploying complex analytics, PCI and security solutions for startups all the way up to mid-sized and Fortune 500 companies to help strengthen their IT security and compliance policies. He is passionate about Python, data analytics and machine learning.

More posts by Nitin Pande.