Author: Dave Cramer

Learn how to configure connection pooling for the AWS Advanced JDBC Wrapper on Amazon Aurora and Amazon RDS. This post explains how the wrapper’s external and internal pooling differ, how to choose between them, and how the JDBC-WRAPPER-CONFIGURATION-ASSISTANT helps you build the right configuration.

Building upon our work with the Advanced JDBC (Java Database Connectivity) Wrapper Driver, we are continuing to enhance the scalability and resiliency of today’s modern applications that are built with Python. The Advanced Python Wrapper Driver has been released as an open-source project under the Apache 2.0 License. You can find the project on GitHub. In this post, we provide details on how to use some of the features of the Advanced Python Wrapper Driver.

When upgrading minor versions of RDS Multi-AZ clusters the connections are switched from the current writer to a newly upgraded reader. Clients have the option to connect to either the cluster writer endpoint or the cluster reader endpoint. Normally, they would connect to the writer endpoint. This endpoint is directed to the current writer instance. […]

Today’s modern applications are expected to be scalable and resilient. The top of this list is scalability, which depending on the size of the application workload could mean the ability to handle millions of users on demand. With stateful applications such as eCommerce, Financial Services and Games, this means having highly available databases. With the release of Amazon Aurora in 2015, customers could run relational databases in an Aurora cluster comprising of one writer and up to 15 low-latency reader nodes. This enables applications to scale reads significantly. However, as with any database supporting multiple instances, developers have built complex application logic to deal with special events such as switchover or failover.