![]() However, the mariadb:aurora parameter avoids the automatic DNS scan for failover targets, thereby eliminating the scanning, which causes a delay in establishing the connection. Always close a connection, including in the event of an exceptionĬonnecting to an Amazon Serverless DB clusterĪ DNS scan is necessary for the custom implementation of a connection failover.Retrieve a connection from the pool as late as possible and return it as soon as possible.Ensure appropriate timeouts and health checks.If connection pooling suits your use case, make sure you follow general best practices: Lastly, connections in the pool are automatically closed if they aren’t used for a certain time. It also avoids unnecessarily keeping the database cluster at a higher capacity because you maintain only as many connections as you need. Connection pooling can enhance your application’s performance and scalability because it reduces the number of times new connections are created and it quickens the process of getting a connection. When the application closes the connection, the connection is returned to the pool instead of being closed. When you need a new connection, you get an already established connection from the pool. Connection pooling reduces the number of times new connections are opened with the database. Application connection poolingĬonnection pooling is a good solution for some applications, such as long-running programs, applications that don’t need scale the application layer, and applications with steady traffic. You have two choices with Aurora Serverless v1: manage your own application connection pooling or use the Amazon RDS Data API. By following the best practices for connection management, you can appropriately scale the database cluster, lower costs, and improve performance. The capacity allocated to your Aurora Serverless v1 DB cluster seamlessly scales up and down based on the load (the CPU utilization and the number of connections) generated by your application. This can have a negative impact on the database and lead to slower performance. Serverless applications can open a large number of database connections or frequently open and close connections. Establishing such a connection consumes valuable compute and memory resources on the database server. An application communicates with a database by establishing connections. One key challenge for modern serverless applications is connection management. ![]() In this post, we describe some of the important best practices for Aurora Serverless v1 such as operational debugging tools, security, and monitoring. With Aurora Serverless v1, you should be mindful of a few things, such as connection management and cold starts. ![]() Arranging to have just the right amount of capacity for these workloads can be a lot of work paying for it on a steady-state basis might not be sensible. Some examples are development and test databases that are infrequently used, ecommerce applications occasionally running flash sales, or new applications you can’t predict capacity for. This blog post focuses on best practices for working with Aurora Serverless v1 databases.Īurora Serverless v1 is suitable for workloads that have intermittent, infrequent, or unpredictable bursts of requests. Amazon Aurora Serverless v1 is a simple, cost-effective option for infrequent, intermittent, or unpredictable workloads. As it scales, it adjusts capacity in fine-grained increments to provide just the right amount of database resources and supports all manners of database workloads. Amazon Aurora Serverless v1 scales instantly from hundreds to hundreds-of-thousands of transactions in a fraction of a second. ![]() November 2022: This post was reviewed and updated for accuracy.Īmazon Aurora Serverless v1 is an on-demand, auto-scaling configuration for Amazon Aurora.
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