Personal blog of Yzmir Ramirez

Please join Autodesk’s Senior Database Engineer, Vineet Khanna, and Percona’s Sr. MySQL DBA, Tate McDaniel as they present Migrating to Aurora and Monitoring with PMM on Thursday, August 9th, 2018, at 10:00 AM PDT (UTC-7) / 1:00 PM EDT (UTC-4).

Amazon Web Services (AWS) Aurora is one of the most popular cloud-based RDBMS solutions. The main reason for Aurora’s success is because it’s based on InnoDB storage engine.

In this session, we will talk about how you can efficiently plan for migration to Aurora using Terraform and Percona products and solutions. We will share our Terraform code for launching AWS Aurora clusters, look at tricks for checking data consistency, verify migration paths and effectively monitor the environment using PMM.

The topics in this session include:

• Why AWS Aurora? What is the future of AWS Aurora?
• Build Aurora Infrastructure
• Using Terraform (Without Data)
• Restore Using Terraform & Percona XtraBackup (Using AWS S3 Bucket)
• Verify data consistency
• Aurora migration
• 1:1 migration
• Many:1 migration using Percona Server multi-source replication
• Show benchmarks and PMM dashboard
• Demo

Register Now

Vineet Khanna, Senior Database Engineer, Autodesk

Vineet Khanna, Senior Database Engineer at Autodesk, has 10+ years of experience as a MySQL DBA. His main professional interests are managing complex database environments, improving database performance, architecting High Availability solutions for MySQL. He has handled database environments of organizations like Chegg, Zendesk, Adobe.

Tate Mcdaniel, Sr. MySQL DBA

Tate joined Percona in June 2017 as a Remote MySQL DBA. He holds a Bachelors degree in Information Systems and Decision Strategies from LSU. He has 10+ years of experience working with MySQL and operations management. His great love is application query tuning. In his off time, he races sailboats, travels the Caribbean by sailboat, and
drives all over in an RV.

The post Webinar Thursday Aug 9: Migrating to AWS Aurora, Monitoring AWS Aurora with PMM appeared first on Percona Database Performance Blog.

In this blog post, we’ll review additional Amazon Aurora MySQL monitoring capabilities we’ve added in Percona Monitoring and Management (PMM) 1.7.0. You can see them in action in the MySQL Amazon Aurora Metrics dashboard.

Amazon Aurora MySQL Transaction Commits

This graph looks at the number of commits the Amazon Aurora engine performed, as well as the average commit latency. As you can see from this graph, latency does not always correlate with the number of commits performed and can be quite high in certain situations.

Amazon Aurora MySQL Load

In Percona Monitoring and Management, we often use the concept of “Load” – which roughly corresponds to the number of operations of a type in progress. This graph shows us what statements contribute the most load on the system, as well as what load corresponds to the Amazon Aurora transaction commits (which we observed in the graph before).

Amazon Aurora MySQL Memory Usage

This graph is pretty self-explanatory. It shows how much memory is used by the Amazon Aurora lock manager, as well as the amount of memory used by Amazon Aurora to store Data Dictionary.

Amazon Aurora MySQL Statement Latency

This graph shows the average latency for the most important types of statements. Latency spikes, as shown in this example, are often indicative of the instance overload.

Amazon Aurora MySQL Special Command Counters

Amazon Aurora MySQL allows a number of commands that are not available in standard MySQL. This graph shows the usage of such commands. Regular “unit_test” calls can be seen in the default Amazon Aurora install, and the rest depends on your workload.

Amazon Aurora MySQL Problems

This graph is where you want to see a flat line. It shows different kinds of internal Amazon Aurora MySQL problems, which in normal operation should generally be zero.

I hope you find these Amazon Aurora MySQL monitoring improvements useful. Let us know if there is any other Amazon Aurora information that would be helpful to display!