diff --git a/README.md b/README.md index 8d7daff8e..76e8e8183 100644 --- a/README.md +++ b/README.md @@ -7,44 +7,61 @@ The **Amazon Web Services (AWS) JDBC Driver** has been redesigned as an advanced JDBC wrapper. -The wrapper is complementary to an existing JDBC driver and aims to extend the functionality of the driver to enable applications to take full advantage of the features of clustered databases such as Amazon Aurora. In other words, the AWS JDBC Driver does not connect directly to any database, but enables support of AWS and Aurora functionalities on top of an underlying JDBC driver of the user's choice. +The wrapper is complementary to an existing JDBC driver and aims to extend the functionality of the driver to enable applications to take full advantage of the features of clustered databases such as Amazon Aurora. In other words, the AWS JDBC Driver does not connect directly to any database, but enables support of AWS and Aurora functionalities on top of an underlying JDBC driver of the user's choice. This approach enables service-specific enhancements, without requiring users to change their workflow and existing JDBC driver tooling. The AWS JDBC Driver is targeted to work with **any** existing JDBC driver. Currently, the AWS JDBC Driver has been validated to support the [PostgreSQL JDBC Driver](https://github.com/pgjdbc/pgjdbc), [MySQL JDBC Driver](https://github.com/mysql/mysql-connector-j), and [MariaDB JDBC Driver](https://github.com/mariadb-corporation/mariadb-connector-j). -In conjunction with the JDBC Drivers for PostgreSQL, MySQL, and MariaDB, the AWS JDBC Driver enables functionalities from Amazon Aurora such as fast failover for PostgreSQL and MySQL Aurora clusters. It also introduces integration with AWS authentication services such as [AWS Identity and Access Management (IAM)](https://aws.amazon.com/iam/) and [AWS Secrets Manager](https://aws.amazon.com/secrets-manager/). +The AWS JDBC Driver provides modular functionality through feature plugins, with each plugin being relevant to specific database services based on their architecture and capabilities. For example, [AWS Identity and Access Management (IAM)](https://aws.amazon.com/iam/) authentication is supported across multiple services, while [AWS Secrets Manager](https://aws.amazon.com/secrets-manager/) applies to services that support password-based authentication. The fast failover plugin provides reduced recovery time during failover for Aurora PostgreSQL and Aurora MySQL clusters. -## About the Wrapper -Hosting a database cluster in the cloud via Aurora is able to provide users with sets of features and configurations to obtain maximum performance and availability, such as database failover. However, at the moment, most existing drivers do not currently support those functionalities or are not able to entirely take advantage of it. +## Benefits of the AWS JDBC Driver for All Aurora and RDS Database Services -The main idea behind the AWS JDBC Driver is to add a software layer on top of an existing JDBC driver that would enable all the enhancements brought by Aurora, without requiring users to change their workflow with their databases and existing JDBC drivers. +### Seamless AWS Authentication Service Integration -### What is Failover? -In an Amazon Aurora database cluster, **failover** is a mechanism by which Aurora automatically repairs the cluster status when a primary DB instance becomes unavailable. It achieves this goal by electing an Aurora Replica to become the new primary DB instance, so that the DB cluster can provide maximum availability to a primary read-write DB instance. The AWS JDBC Driver is designed to understand the situation and coordinate with the cluster in order to provide minimal downtime and allow connections to be very quickly restored in the event of a DB instance failure. +Built-in support for AWS Identity and Access Management (IAM) authentication eliminates the need to manage database passwords, while AWS Secrets Manager integration provides secure credential management for services that require password-based authentication. -### Benefits of the AWS JDBC Driver -Although Aurora is able to provide maximum availability through the use of failover, existing client drivers do not currently support this functionality. This is partially due to the time required for the DNS of the new primary DB instance to be fully resolved in order to properly direct the connection. The AWS JDBC Driver allows customers to continue using their existing community drivers in addition to having the AWS JDBC Driver fully exploit failover behavior by maintaining a cache of the Aurora cluster topology and each DB instance's role (Aurora Replica or primary DB instance). This topology is provided via a direct query to the Aurora DB, essentially providing a shortcut to bypass the delays caused by DNS resolution. With this knowledge, the AWS JDBC Driver can more closely monitor the Aurora DB cluster status so that a connection to the new primary DB instance can be established as fast as possible. +### Preserve Existing Workflows -### Enhanced Failure Monitoring -Since a database failover is usually identified by reaching a network or a connection timeout, the AWS JDBC Driver introduces an enhanced and customizable manner to faster identify a database outage. +The wrapper design allows developers to continue using their preferred JDBC drivers and existing database code while gaining service-specific enhancements. No application rewrites are required. -Enhanced Failure Monitoring (EFM) is a feature available from the [Host Monitoring Connection Plugin](./docs/using-the-jdbc-driver/using-plugins/UsingTheHostMonitoringPlugin.md#enhanced-failure-monitoring) that periodically checks the connected database node's health and availability. If a database node is determined to be unhealthy, the connection is aborted (and potentially routed to another healthy node in the cluster). +### Modular Plugin Architecture -### Using the AWS JDBC Driver with RDS Multi-AZ DB Clusters -The [AWS RDS Multi-AZ DB Clusters](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/multi-az-db-clusters-concepts.html) are capable of switching over the current writer node to another node in the cluster within approximately 1 second or less, in case of minor engine version upgrade or OS maintenance operations. -The AWS JDBC Driver has been optimized for such fast failover when working with AWS RDS Multi-AZ DB Clusters. +The plugin-based design ensures applications only load the functionality they need, reducing dependencies and overhead. + +## Benefits of the AWS JDBC Driver for Aurora PostgreSQL, Aurora MySQL, and RDS + +### Faster Failover and Reduced Downtime + +For Aurora PostgreSQL, Aurora MySQL, and RDS Multi-AZ DB clusters, the driver significantly reduces connection recovery time during [database failovers](./docs/using-the-jdbc-driver/WhatIsFailover.md). By maintaining a real-time cache of cluster topology and bypassing DNS resolution delays, applications can reconnect to healthy database instances in seconds rather than minutes. + +### Enhanced Failure Detection + +The driver includes Enhanced Failure Monitoring (EFM) that proactively monitors database node health, detecting failures faster than traditional timeout-based approaches. This allows applications to respond to issues before they impact end users. + +## Using the AWS JDBC Driver with... + +### Amazon Aurora PostgreSQL and Aurora MySQL + +The AWS JDBC Driver provides fast failover capabilities for Aurora PostgreSQL and Aurora MySQL clusters, significantly reducing connection recovery time during database failovers. + +Visit [this page](./docs/using-the-jdbc-driver/using-plugins/UsingTheFailover2Plugin.md) for more details. + +### Amazon RDS Multi-AZ DB Clusters + +The [AWS RDS Multi-AZ DB Clusters](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/multi-az-db-clusters-concepts.html) are capable of switching over the current writer node to another node in the cluster within approximately 1 second or less, in case of minor engine version upgrade or OS maintenance operations. The AWS JDBC Driver has been optimized for such fast failover when working with AWS RDS Multi-AZ DB Clusters. With the `failover` plugin, the downtime during certain DB cluster operations, such as engine minor version upgrades, can be reduced to one second or even less with finely tuned parameters. It supports both MySQL and PostgreSQL clusters. Visit [this page](./docs/using-the-jdbc-driver/SupportForRDSMultiAzDBCluster.md) for more details. -### Using the AWS JDBC Driver with plain RDS databases +### Plain Amazon RDS databases + The AWS JDBC Driver also works with RDS provided databases that are not Aurora. -Please visit [this page](./docs/using-the-jdbc-driver/UsingTheJdbcDriver.md#using-the-aws-jdbc-driver-with-plain-rds-databases) for more information. +Visit [this page](./docs/using-the-jdbc-driver/UsingTheJdbcDriver.md#using-the-aws-jdbc-driver-with-plain-rds-databases) for more details. ## Getting Started -For more information on how to download the AWS JDBC Driver, minimum requirements to use it, -and how to integrate it within your project and with your JDBC driver of choice, please visit the +For more information on how to download the AWS JDBC Driver, minimum requirements to use it, +and how to integrate it within your project and with your JDBC driver of choice, please visit the [Getting Started page](./docs/GettingStarted.md). ### Maven Central @@ -144,30 +161,31 @@ This driver currently does not support `planned failover` or `switchover` of Ama ## Examples -| Description | Examples | -|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| -| Using the AWS JDBC Driver to get a simple connection | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/PgConnectionSample.java) | -| Using the AWS JDBC Driver with failover handling | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/PgFailoverSample.java) | -| Using the AWS IAM Authentication Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationPostgresqlExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationMysqlExample.java)
[MariaDB](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationMariadbExample.java) | -| Using the AWS Secrets Manager Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsSecretsManagerConnectionPluginPostgresqlExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsSecretsManagerConnectionPluginMySQLExample.java) | -| Using the AWS Credentials Manager to configure an alternative AWS credentials provider. | [PostgreSQL and MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsCredentialsManagerExample.java) | -| Using the AWS JDBC Driver with `AWSWrapperDatasource` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/DatasourceExample.java) | +| Description | Examples | +|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| +| Using the AWS JDBC Driver to get a simple connection | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/PgConnectionSample.java) | +| Using the AWS JDBC Driver with failover handling | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/PgFailoverSample.java) | +| Using the AWS IAM Authentication Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationPostgresqlExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationMysqlExample.java)
[MariaDB](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationMariadbExample.java) | +| Using the AWS IAM Authentication Plugin with `DataSource` | [PostgreSQL and MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsIamAuthenticationDatasourceExample.java) | +| Using the AWS Secrets Manager Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsSecretsManagerConnectionPluginPostgresqlExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsSecretsManagerConnectionPluginMySQLExample.java) | +| Using the AWS Credentials Manager to configure an alternative AWS credentials provider. | [PostgreSQL and MySQL](examples/AWSDriverExample/src/main/java/software/amazon/AwsCredentialsManagerExample.java) | +| Using the AWS JDBC Driver with `AWSWrapperDatasource` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/DatasourceExample.java) | | Using the Driver Metadata Plugin to override driver name, this plugin [enables specific database features that may only be available to target drivers](https://github.com/aws/aws-advanced-jdbc-wrapper/issues/370) | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/DriverMetaDataConnectionPluginExample.java) | -| Using the Read/Write Splitting Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingPostgresExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingMySQLExample.java) | -| Using the Read/Write Splitting Plugin with Spring | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingSpringJdbcTemplatePostgresExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingSpringJdbcTemplateMySQLExample.java) | -| Using HikariCP with the `AWSWrapperDatasource` | [PostgreSQL](examples/HikariExample/src/main/java/software/amazon/HikariExample.java) | -| Using HikariCP with the `AWSWrapperDatasource` with failover handling | [PostgreSQL](examples/HikariExample/src/main/java/software/amazon/HikariFailoverExample.java) | -| Using Spring and HikariCP with the AWS JDBC Driver | [PostgreSQL](examples/SpringBootHikariExample/README.md) | -| Using Spring and HikariCP with the AWS JDBC Driver and failover handling | [PostgreSQL](examples/SpringTxFailoverExample/README.md) | -| Using Spring and Hibernate with the AWS JDBC Driver | [PostgreSQL](examples/SpringHibernateExample/README.md) | -| Using Spring and Wildfly with the AWS JDBC Driver | [PostgreSQL](examples/SpringWildflyExample/README.md) | -| Using Vert.x and c3p0 with the AWS JDBC Driver | [PostgreSQL](examples/VertxExample/README.md) | -| Using the AWS JDBC Driver with Telemetry and using the AWS Distro for OpenTelemetry Collector | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/TelemetryMetricsOTLPExample.java) | -| Using the AWS JDBC Driver with Telemetry and using the AWS X-Ray Daemon | [PostgreSQL](./examples/AWSDriverExample/src/main/java/software/amazon/TelemetryTracingXRayExample.java) | +| Using the Read/Write Splitting Plugin with `DriverManager` | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingPostgresExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingMySQLExample.java) | +| Using the Read/Write Splitting Plugin with Spring | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingSpringJdbcTemplatePostgresExample.java)
[MySQL](examples/AWSDriverExample/src/main/java/software/amazon/ReadWriteSplittingSpringJdbcTemplateMySQLExample.java) | +| Using HikariCP with the `AWSWrapperDatasource` | [PostgreSQL](examples/HikariExample/src/main/java/software/amazon/HikariExample.java) | +| Using HikariCP with the `AWSWrapperDatasource` with failover handling | [PostgreSQL](examples/HikariExample/src/main/java/software/amazon/HikariFailoverExample.java) | +| Using Spring and HikariCP with the AWS JDBC Driver | [PostgreSQL](examples/SpringBootHikariExample/README.md) | +| Using Spring and HikariCP with the AWS JDBC Driver and failover handling | [PostgreSQL](examples/SpringTxFailoverExample/README.md) | +| Using Spring and Hibernate with the AWS JDBC Driver | [PostgreSQL](examples/SpringHibernateExample/README.md) | +| Using Spring and Wildfly with the AWS JDBC Driver | [PostgreSQL](examples/SpringWildflyExample/README.md) | +| Using Vert.x and c3p0 with the AWS JDBC Driver | [PostgreSQL](examples/VertxExample/README.md) | +| Using the AWS JDBC Driver with Telemetry and using the AWS Distro for OpenTelemetry Collector | [PostgreSQL](examples/AWSDriverExample/src/main/java/software/amazon/TelemetryMetricsOTLPExample.java) | +| Using the AWS JDBC Driver with Telemetry and using the AWS X-Ray Daemon | [PostgreSQL](./examples/AWSDriverExample/src/main/java/software/amazon/TelemetryTracingXRayExample.java) | ## Getting Help and Opening Issues If you encounter a bug with the AWS JDBC Driver, we would like to hear about it. -Please search the [existing issues](https://github.com/aws/aws-advanced-jdbc-wrapper/issues) to see if others are also experiencing the issue before reporting the problem in a new issue. GitHub issues are intended for bug reports and feature requests. +Please search the [existing issues](https://github.com/aws/aws-advanced-jdbc-wrapper/issues) to see if others are also experiencing the issue before reporting the problem in a new issue. GitHub issues are intended for bug reports and feature requests. When opening a new issue, please fill in all required fields in the issue template to help expedite the investigation process. @@ -175,11 +193,11 @@ For all other questions, please use [GitHub discussions](https://github.com/aws/ ## How to Contribute 1. Set up your environment by following the directions in the [Development Guide](docs/development-guide/DevelopmentGuide.md). -2. To contribute, first make a fork of this project. +2. To contribute, first make a fork of this project. 3. Make any changes on your fork. Make sure you are aware of the requirements for the project (e.g. do not require Java 7 if we are supporting Java 8 and higher). -4. Create a pull request from your fork. +4. Create a pull request from your fork. 5. Pull requests need to be approved and merged by maintainers into the main branch.
-**Note:** Before making a pull request, [run all tests](./docs/development-guide/DevelopmentGuide.md#running-the-tests) and verify everything is passing. + **Note:** Before making a pull request, [run all tests](./docs/development-guide/DevelopmentGuide.md#running-the-tests) and verify everything is passing. ### Code Style The project source code is written using the [Google checkstyle](https://github.com/google/styleguide/blob/gh-pages/intellij-java-google-style.xml), and the style is strictly enforced in our automation pipelines. Any contribution that does not respect/satisfy the style will automatically fail at build time. diff --git a/docs/using-the-jdbc-driver/WhatIsFailover.md b/docs/using-the-jdbc-driver/WhatIsFailover.md new file mode 100644 index 000000000..dbd9039f0 --- /dev/null +++ b/docs/using-the-jdbc-driver/WhatIsFailover.md @@ -0,0 +1,20 @@ +# What is Failover? + +In AWS database clusters, **failover** is a mechanism that automatically repairs cluster availability when a primary +database instance becomes unavailable. This process ensures minimal downtime by promoting a replica instance to become +the new primary. + +## Aurora Clusters + +In an Amazon Aurora database cluster, failover works by electing an Aurora Replica to become the new primary DB +instance, ensuring the cluster maintains maximum availability for read-write operations. + +## RDS Multi-AZ DB Clusters + +In Amazon RDS Multi-AZ DB clusters, failover automatically promotes one of the two readable standby instances to become +the new primary when the original primary fails. + +# Additional Resources + +- [Failing over an Amazon Aurora DB cluster](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-failover.html) +- [RDS Multi-AZ DB clusters](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/multi-az-db-clusters-concepts.html)