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5. User Guide for Aurora
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AMAZON AURORA
USER GUIDE FOR AURORA
* What is Aurora?
* Aurora DB clusters
* Aurora versions
* Regions and Availability Zones
* Supported Aurora features by Region and engine
* Blue/Green Deployments
* Aurora cluster configurations
* Database activity streams in Aurora
* Exporting cluster data to Amazon S3
* Exporting snapshot data to Amazon S3
* Aurora global databases
* IAM database authentication in Aurora
* Kerberos authentication with Aurora
* Aurora machine learning
* Performance Insights with Aurora
* Zero-ETL integrations
* Amazon RDS Proxy
* Secrets Manager integration
* Aurora Serverless v2
* Aurora Serverless v1
* Data API for Aurora Serverless v1
* Zero-downtime patching (ZDP)
* Engine-native features
* Aurora connection management
* DB instance classes
* Aurora storage and reliability
* Aurora security
* High availability for Amazon Aurora
* Replication with Aurora
* DB instance billing for Aurora
* On-Demand DB instances
* Reserved DB instances
* Setting up your environment
* Getting started
* Creating and connecting to an Aurora MySQL DB cluster
* Creating and connecting to an Aurora PostgreSQL DB cluster
* Tutorial: Create a web server and an Amazon Aurora DB cluster
* Launch an EC2 instance
* Create a DB cluster
* Install a web server
* Tutorials and sample code
* Configuring your Aurora DB cluster
* Creating a DB cluster
* Creating resources with AWS CloudFormation
* Connecting to a DB cluster
* Working with parameter groups
* Overview of parameter groups
* Working with DB cluster parameter groups
* Working with DB parameter groups
* Comparing parameter groups
* Specifying DB parameters
* Migrating data to a DB cluster
* Creating an ElastiCache cluster from Amazon RDS
* Managing an Aurora DB cluster
* Stopping and starting a cluster
* Connecting an AWS compute resource
* Connecting an EC2 instance
* Connecting a Lambda function
* Modifying an Aurora DB cluster
* Adding Aurora Replicas
* Managing performance and scaling
* Cloning a volume for an Aurora DB cluster
* Integrating with AWS services
* Using Auto Scaling with Aurora Replicas
* Using machine learning with Aurora
* Maintaining an Aurora DB cluster
* Rebooting an Aurora DB cluster or instance
* Deleting Aurora clusters and instances
* Tagging RDS resources
* Working with ARNs
* Aurora updates
* Using Extended Support
* Using Blue/Green Deployments for database updates
* Overview of Amazon RDS Blue/Green Deployments
* Creating a blue/green deployment
* Viewing a blue/green deployment
* Switching a blue/green deployment
* Deleting a blue/green deployment
* Backing up and restoring an Aurora DB cluster
* Overview of backing up and restoring
* Backup storage
* Creating a DB cluster snapshot
* Restoring from a DB cluster snapshot
* Copying a DB cluster snapshot
* Sharing a DB cluster snapshot
* Exporting DB cluster data to Amazon S3
* Exporting DB cluster snapshot data to Amazon S3
* Point-in-time recovery
* Deleting a DB cluster snapshot
* Tutorial: Restore a DB cluster from a snapshot
* Monitoring metrics in an Aurora DB cluster
* Overview of monitoring
* Viewing cluster status and recommendations
* Viewing metrics in the Amazon RDS console
* Viewing combined metrics in the Amazon RDS console
* Monitoring Aurora with CloudWatch
* Overview of Amazon Aurora and Amazon CloudWatch
* Viewing CloudWatch metrics
* Exporting Performance Insights metrics to CloudWatch
* Creating CloudWatch alarms
* Monitoring DB load with Performance Insights
* Overview of Performance Insights
* Database load
* Maximum CPU
* Amazon Aurora DB engine, Region, and instance class support for
Performance Insights
* Pricing and data retention for Performance Insights
* Turning Performance Insights on and off
* Turning on the Performance Schema for Aurora MySQL
* Performance Insights policies
* Analyzing metrics with the Performance Insights dashboard
* Overview of the dashboard
* Accessing the dashboard
* Analyzing DB load
* Analyzing database performance for a period of time
* Analyzing queries
* Overview of the Top SQL tab
* Accessing more SQL text
* Viewing SQL statistics
* Retrieving metrics with the Performance Insights API
* Logging Performance Insights calls using AWS CloudTrail
* Analyzing performance with DevOps Guru for RDS
* Monitoring threats with GuardDuty RDS Protection
* Monitoring the OS with Enhanced Monitoring
* Overview of Enhanced Monitoring
* Setting up and enabling Enhanced Monitoring
* Viewing OS metrics in the RDS console
* Viewing OS metrics using CloudWatch Logs
* Aurora metrics reference
* CloudWatch metrics for Aurora
* CloudWatch dimensions for Aurora
* Availability of Aurora metrics in the Amazon RDS console
* CloudWatch metrics for Performance Insights
* Counter metrics for Performance Insights
* SQL statistics for Performance Insights
* SQL statistics for Aurora MySQL
* SQL statistics for Aurora PostgreSQL
* OS metrics in Enhanced Monitoring
* Monitoring events, logs, and database activity streams
* Viewing logs, events, and streams in the Amazon RDS console
* Monitoring Aurora events
* Overview of events for Aurora
* Viewing Amazon RDS events
* Working with Amazon RDS event notification
* Overview of Amazon RDS event notification
* Granting permissions
* Subscribing to Amazon RDS event notification
* Amazon RDS event notification tags and attributes
* Listing Amazon RDS event notification subscriptions
* Modifying an Amazon RDS event notification subscription
* Adding a source identifier to an Amazon RDS event notification
subscription
* Removing a source identifier from an Amazon RDS event notification
subscription
* Listing the Amazon RDS event notification categories
* Deleting an Amazon RDS event notification subscription
* Creating a rule that triggers on an Amazon Aurora event
* Amazon RDS event categories and event messages
* Monitoring Aurora logs
* Viewing and listing database log files
* Downloading a database log file
* Watching a database log file
* Publishing to CloudWatch Logs
* Reading log file contents using REST
* MySQL database log files
* Overview of Aurora MySQL database logs
* Publishing Aurora MySQL logs to Amazon CloudWatch Logs
* Managing table-based Aurora MySQL logs
* Configuring Aurora MySQL binary logging
* Accessing MySQL binary logs
* PostgreSQL database log files
* Monitoring Aurora API calls in CloudTrail
* Monitoring Aurora with Database Activity Streams
* Overview
* Aurora MySQL network prerequisites
* Starting a database activity stream
* Getting the activity stream status
* Stopping a database activity stream
* Monitoring activity streams
* Managing access to activity streams
* Working with Aurora MySQL
* Overview of Aurora MySQL
* Aurora MySQL version 3 compatible with MySQL 8.0
* New temporary table behavior in Aurora MySQL version 3
* Comparison of Aurora MySQL version 2 and Aurora MySQL version 3
* Comparison of Aurora MySQL version 3 and MySQL 8.0 Community Edition
* Upgrading to Aurora MySQL version 3
* Aurora MySQL version 2 compatible with MySQL 5.7
* Security with Aurora MySQL
* Updating applications for new TLS certificates
* Using Kerberos authentication for Aurora MySQL
* Setting up Kerberos authentication for Aurora MySQL
* Connecting to Aurora MySQL with Kerberos authentication
* Managing a DB cluster in a domain
* Migrating data to Aurora MySQL
* Migrating from an external MySQL database to Aurora MySQL
* Physical migration using Percona XtraBackup and Amazon S3
* Reducing the physical migration time
* Logical migration using mysqldump
* Migrating from a MySQL DB instance to Aurora MySQL
* Migrating an RDS for MySQL snapshot to Aurora
* Migrating from RDS for MySQL to Aurora MySQL using a read replica
* Managing Aurora MySQL
* Managing performance and scaling for Amazon Aurora MySQL
* Backtracking a DB cluster
* Testing Amazon Aurora MySQL using fault injection queries
* Altering tables in Amazon Aurora using Fast DDL
* Displaying volume status for an Aurora DB cluster
* Tuning Aurora MySQL
* Essential concepts for Aurora MySQL tuning
* Tuning Aurora MySQL with wait events
* cpu
* io/aurora_redo_log_flush
* io/aurora_respond_to_client
* io/socket/sql/client_connection
* io/table/sql/handler
* synch/cond/innodb/row_lock_wait
* synch/cond/innodb/row_lock_wait_cond
* synch/cond/mysys/my_thread_var::suspend
* synch/cond/sql/MDL_context::COND_wait_status
* synch/mutex/innodb/aurora_lock_thread_slot_futex
* synch/mutex/innodb/buf_pool_mutex
* synch/mutex/innodb/fil_system_mutex
* synch/mutex/innodb/trx_sys_mutex
* synch/sxlock/innodb/hash_table_locks
* Tuning Aurora MySQL with thread states
* creating sort index
* sending data
* Tuning Aurora MySQL with Amazon DevOps Guru proactive insights
* The InnoDB history list length increased significantly
* Database is creating temporary tables on disk
* Parallel query for Aurora MySQL
* Advanced Auditing with Aurora MySQL
* Replication with Aurora MySQL
* Using local write forwarding
* Cross-Region replication
* Using binary log (binlog) replication
* Using GTID-based replication
* Integrating Aurora MySQL with AWS services
* Authorizing Aurora MySQL to access AWS services
* Setting up IAM roles to access AWS services
* Creating an IAM policy to access Amazon S3
* Creating an IAM policy to access Lambda
* Creating an IAM policy to access CloudWatch Logs
* Creating an IAM policy to access AWS KMS
* Creating an IAM role to access AWS services
* Associating an IAM role with a DB cluster
* Enabling network communication to AWS services
* Loading data from text files in Amazon S3
* Saving data into text files in Amazon S3
* Invoking a Lambda function from Aurora MySQL
* Publishing Aurora MySQL logs to CloudWatch Logs
* Using Aurora machine learning with Aurora MySQL
* Aurora MySQL lab mode
* Best practices with Amazon Aurora MySQL
* Amazon Aurora MySQL reference
* Configuration parameters
* Wait events
* Thread states
* Isolation levels
* Hints
* Stored procedures
* Configuring
* Ending a session or query
* Logging
* Managing the Global Status History
* Replicating
* information_schema tables
* Aurora MySQL updates
* Version Numbers and Special Versions
* Preparing for Aurora MySQL version 2 end of life
* Preparing for Aurora MySQL version 1 end of life
* Upgrading Amazon Aurora MySQL DB clusters
* Upgrading the minor version or patch level of an Aurora MySQL DB
cluster
* Upgrading the Aurora MySQL major version of a DB cluster
* Database engine updates for Amazon Aurora MySQL version 3
* Database engine updates for Amazon Aurora MySQL version 2
* Database engine updates for Amazon Aurora MySQL version 1
* Database engine updates for Aurora MySQL Serverless clusters
* MySQL bugs fixed by Aurora MySQL database engine updates
* Security vulnerabilities fixed in Amazon Aurora MySQL
* Working with Aurora PostgreSQL
* The database preview environment
* Security with Aurora PostgreSQL
* Understanding PostgreSQL roles and permissions
* Updating applications for new SSL/TLS certificates
* Using Kerberos authentication
* Setting up
* Managing a DB cluster in a Domain
* Connecting with Kerberos authentication
* Migrating data to Aurora PostgreSQL
* Improving query performance with Aurora Optimized Reads
* Using Babelfish for Aurora PostgreSQL
* Babelfish limitations
* Understanding Babelfish architecture and configuration
* Babelfish architecture
* DB cluster parameter group settings for Babelfish
* Collations supported by Babelfish
* Managing collations
* Collation limitations and differences
* Managing Babelfish error handling
* Creating a Babelfish for Aurora PostgreSQL DB cluster
* Migrating a SQL Server database to Babelfish
* Database authentication with Babelfish for Aurora PostgreSQL
* Connecting to a Babelfish DB cluster
* Creating C# or JDBC client connections to Babelfish
* Using a SQL Server client to connect to your DB cluster
* Using a PostgreSQL client to connect to your DB cluster
* Working with Babelfish
* Getting information from the Babelfish system catalog
* Differences between Babelfish for Aurora PostgreSQL and SQL Server
* T-SQL differences in Babelfish
* Using Babelfish features with limited implementation
* Improving Babelfish query performance
* Using explain plan to improve query performance
* Using T-SQL query hints to improve Babelfish query performance
* Using Aurora PostgreSQL extensions with Babelfish
* Babelfish supports linked servers
* Troubleshooting Babelfish
* Turning off Babelfish
* Babelfish versions
* Identifying your version of Babelfish
* Upgrading Babelfish to a new version
* Using Babelfish product version parameter
* Babelfish reference
* Unsupported functionality
* Supported functionality by Babelfish version
* Babelfish procedure reference
* Managing Aurora PostgreSQL
* Testing Amazon Aurora PostgreSQL by using fault injection queries
* Displaying volume status for an Aurora DB cluster
* Specifying the RAM disk for the stats_temp_directory
* Managing temporary files with PostgreSQL
* Tuning with wait events for Aurora PostgreSQL
* Essential concepts for Aurora PostgreSQL tuning
* Aurora PostgreSQL wait events
* Client:ClientRead
* Client:ClientWrite
* CPU
* IO:BufFileRead and IO:BufFileWrite
* IO:DataFileRead
* IO:XactSync
* IPC:DamRecordTxAck
* Lock:advisory
* Lock:extend
* Lock:Relation
* Lock:transactionid
* Lock:tuple
* LWLock:buffer_content (BufferContent)
* LWLock:buffer_mapping
* LWLock:BufferIO (IPC:BufferIO)
* LWLock:lock_manager
* LWLock:MultiXact
* Timeout:PgSleep
* Tuning Aurora PostgreSQL with Amazon DevOps Guru proactive insights
* Database has long running idle in transaction connection
* Best practices with Aurora PostgreSQL
* Diagnosing table and index bloat
* Improved memory management in Aurora PostgreSQL
* Fast failover
* Fast recovery after failover
* Managing connection churn
* Tuning memory parameters for Aurora PostgreSQL
* Analyze resource usage with CloudWatch metrics
* Using logical replication for a major version upgrade
* Troubleshooting storage issues
* Replication with Aurora PostgreSQL
* Using logical replication
* Integrating Aurora PostgreSQL with AWS services
* Importing data from Amazon S3 into Aurora PostgreSQL
* Exporting PostgreSQL data to Amazon S3
* Invoking a Lambda function from Aurora PostgreSQL
* Lambda function reference
* Publishing Aurora PostgreSQL logs to CloudWatch Logs
* Using Aurora machine learning with Aurora PostgreSQL
* Managing query execution plans for Aurora PostgreSQL
* Overview of Aurora PostgreSQL query plan management
* Best practices for Aurora PostgreSQL query plan management
* Understanding query plan management
* Capturing Aurora PostgreSQL execution plans
* Using Aurora PostgreSQL managed plans
* Examining Aurora PostgreSQL query plans in the dba_plans view
* Maintaining Aurora PostgreSQL execution plans
* Reference
* Parameter reference for Aurora PostgreSQL query plan management
* Function reference for Aurora PostgreSQL query plan management
* Reference for the apg_plan_mgmt.dba_plans view
* Advanced features in Query Plan Management
* Capturing Aurora PostgreSQL execution plans in Replicas
* Supporting table partition by Query Plan Management
* Working with extensions and foreign data wrappers
* Managing large objects more efficiently with the lo module
* Managing spatial data with PostGIS
* Managing partitions with the pg_partman extension
* Scheduling maintenance with the pg_cron extension
* Supported foreign data wrappers
* Working with Trusted Language Extensions for PostgreSQL
* Functions reference for Trusted Language Extensions
* pgtle.available_extensions
* pgtle.available_extension_versions
* pgtle.extension_update_paths
* pgtle.install_extension
* pgtle.install_update_path
* pgtle.register_feature
* pgtle.register_feature_if_not_exists
* pgtle.set_default_version
* pgtle.uninstall_extension
* pgtle.uninstall_extension
* pgtle.uninstall_extension_if_exists
* pgtle.uninstall_update_path
* pgtle.uninstall_update_path_if_exists
* pgtle.unregister_feature
* pgtle.unregister_feature_if_exists
* Hooks reference for Trusted Language Extensions
* Password check hook (passcheck)
* Aurora PostgreSQL reference
* Collations supported in Aurora PostgreSQL
* Aurora PostgreSQL functions reference
* aurora_db_instance_identifier
* aurora_ccm_status
* aurora_global_db_instance_status
* aurora_global_db_status
* aurora_list_builtins
* aurora_replica_status
* aurora_stat_backend_waits
* aurora_stat_bgwriter
* aurora_stat_database
* aurora_stat_dml_activity
* aurora_stat_get_db_commit_latency
* aurora_stat_logical_wal_cache
* aurora_stat_memctx_usage
* aurora_stat_optimized_reads_cache
* aurora_stat_reset_wal_cache
* aurora_stat_statements
* aurora_stat_system_waits
* aurora_stat_wait_event
* aurora_stat_wait_type
* aurora_version
* aurora_volume_logical_start_lsn
* aurora_wait_report
* Aurora PostgreSQL parameters
* Aurora PostgreSQL wait events
* Aurora PostgreSQL updates
* Identifying versions of Amazon Aurora PostgreSQL
* Aurora PostgreSQL releases
* Extension versions for Aurora PostgreSQL
* Upgrading Amazon Aurora PostgreSQL DB clusters
* Using a long-term support (LTS) release
* Using Aurora global databases
* Getting started with Aurora global databases
* Managing an Aurora global database
* Connecting to an Aurora global database
* Using write forwarding in an Aurora global database
* Using write forwarding in Aurora MySQL
* Using write forwarding in Aurora PostgreSQL
* Using switchover or failover in an Aurora global database
* Monitoring an Aurora global database
* Using Aurora global databases with other AWS services
* Upgrading an Amazon Aurora global database
* Using RDS Proxy
* Planning where to use RDS Proxy
* RDS Proxy concepts and terminology
* Getting started with RDS Proxy
* Managing an RDS Proxy
* Working with RDS Proxy endpoints
* Monitoring RDS Proxy with CloudWatch
* Working with RDS Proxy events
* RDS Proxy examples
* Troubleshooting RDS Proxy
* Using RDS Proxy with AWS CloudFormation
* Using RDS Proxy with Aurora global databases
* Working with zero-ETL integrations
* Getting started with zero-ETL integrations
* Creating zero-ETL integrations
* Adding and querying data
* Viewing and monitoring zero-ETL integrations
* Deleting zero-ETL integrations
* Troubleshooting zero-ETL integrations
* Using Aurora Serverless v2
* How Aurora Serverless v2 works
* Requirements for Aurora Serverless v2
* Getting started with Aurora Serverless v2
* Creating a cluster for Aurora Serverless v2
* Managing Aurora Serverless v2
* Performance and scaling for Aurora Serverless v2
* Using Aurora Serverless v1
* How Aurora Serverless v1 works
* Creating an Aurora Serverless v1 DB cluster
* Restoring an Aurora Serverless v1 DB cluster
* Modifying an Aurora Serverless v1 DB cluster
* Scaling Aurora Serverless v1 DB cluster capacity manually
* Viewing Aurora Serverless v1 DB clusters
* Deleting an Aurora Serverless v1 DB cluster
* Aurora Serverless v1 and Aurora database engine versions
* Using the Data API
* Logging Data API calls with AWS CloudTrail
* Using the query editor
* DBQMS API reference
* Code examples
* Actions
* Create a DB cluster
* Create a DB cluster parameter group
* Create a DB cluster snapshot
* Create a DB instance in a DB cluster
* Delete a DB cluster
* Delete a DB cluster parameter group
* Delete a DB instance
* Describe DB cluster parameter groups
* Describe DB cluster snapshots
* Describe DB clusters
* Describe DB instances
* Describe database engine versions
* Describe options for DB instances
* Describe parameters from a DB cluster parameter group
* Update parameters in a DB cluster parameter group
* Scenarios
* Get started with DB clusters
* Cross-service examples
* Create a lending library REST API
* Create an Aurora Serverless work item tracker
* Best practices with Aurora
* Performing an Aurora proof of concept
* Security
* Database authentication
* Password management with Aurora and Secrets Manager
* Data protection
* Data encryption
* Encrypting Amazon Aurora resources
* AWS KMS key management
* Using SSL/TLS to encrypt a connection
* Rotating your SSL/TLS certificate
* Internetwork traffic privacy
* Identity and access management
* How Amazon Aurora works with IAM
* Identity-based policy examples
* AWS managed policies
* Policy updates
* Cross-service confused deputy prevention
* IAM database authentication
* Enabling and disabling
* Creating and using an IAM policy for IAM database access
* Creating a database account using IAM authentication
* Connecting to your DB cluster using IAM authentication
* Connecting using IAM: AWS CLI and mysql client
* Connecting using IAM authentication from the command line: AWS
CLI and psql client
* Connecting using IAM authentication and the AWS SDK for .NET
* Connecting using IAM authentication and the AWS SDK for Go
* Connecting using IAM authentication and the AWS SDK for Java
* Connecting using IAM authentication and the AWS SDK for Python
(Boto3)
* Troubleshooting
* Logging and monitoring
* Compliance validation
* Resilience
* Infrastructure security
* VPC endpoints (AWS PrivateLink)
* Security best practices
* Controlling access with security groups
* Master user account privileges
* Service-linked roles
* Using Amazon Aurora with Amazon VPC
* Working with a DB cluster in a VPC
* Scenarios for accessing a DB cluster in a VPC
* Tutorial: Create a VPC for use with a DB cluster (IPv4 only)
* Tutorial: Create a VPC for use with a DB cluster (dual-stack mode)
* Quotas and constraints
* Troubleshooting
* Amazon RDS API reference
* Using the Query API
* Troubleshooting applications
* Document history
* AWS Glossary
IAM database authentication - Amazon Aurora
AWSDocumentationAmazon RDSUser Guide for Aurora
Region and version availabilityCLI and SDK
supportLimitationsRecommendationsUnsupported AWS global condition context keys
IAM DATABASE AUTHENTICATION
PDFRSS
You can authenticate to your DB cluster using AWS Identity and Access Management
(IAM) database authentication. IAM database authentication works with Aurora
MySQL, and Aurora PostgreSQL. With this authentication method, you don't need to
use a password when you connect to a DB cluster. Instead, you use an
authentication token.
An authentication token is a unique string of characters that Amazon Aurora
generates on request. Authentication tokens are generated using AWS Signature
Version 4. Each token has a lifetime of 15 minutes. You don't need to store user
credentials in the database, because authentication is managed externally using
IAM. You can also still use standard database authentication. The token is only
used for authentication and doesn't affect the session after it is established.
IAM database authentication provides the following benefits:
* Network traffic to and from the database is encrypted using Secure Socket
Layer (SSL) or Transport Layer Security (TLS). For more information about
using SSL/TLS with Amazon Aurora, see Using SSL/TLS to encrypt a connection
to a DB cluster.
* You can use IAM to centrally manage access to your database resources,
instead of managing access individually on each DB cluster.
* For applications running on Amazon EC2, you can use profile credentials
specific to your EC2 instance to access your database instead of a password,
for greater security.
In general, consider using IAM database authentication when your applications
create fewer than 200 connections per second, and you don't want to manage
usernames and passwords directly in your application code.
The AWS JDBC Driver for MySQL supports IAM database authentication. For more
information, see AWS IAM Database Authentication in the AWS JDBC Driver for
MySQL GitHub repository.
TOPICS
* Region and version availability
* CLI and SDK support
* Limitations for IAM database authentication
* Recommendations for IAM database authentication
* Unsupported AWS global condition context keys
* Enabling and disabling IAM database authentication
* Creating and using an IAM policy for IAM database access
* Creating a database account using IAM authentication
* Connecting to your DB cluster using IAM authentication
REGION AND VERSION AVAILABILITY
Feature availability and support varies across specific versions of each Aurora
database engine, and across AWS Regions. For more information on version and
Region availability with Aurora and IAM database authentication, see IAM
database authentication in Aurora.
For Aurora MySQL, all supported DB instance classes support IAM database
authentication, except for db.t2.small and db.t3.small. For information about
the supported DB instance classes, see Supported DB engines for DB instance
classes.
CLI AND SDK SUPPORT
IAM database authentication is available for the AWS CLI and for the following
language-specific AWS SDKs:
* AWS SDK for .NET
* AWS SDK for C++
* AWS SDK for Go
* AWS SDK for Java
* AWS SDK for JavaScript
* AWS SDK for PHP
* AWS SDK for Python (Boto3)
* AWS SDK for Ruby
LIMITATIONS FOR IAM DATABASE AUTHENTICATION
When using IAM database authentication, the following limitations apply:
* The maximum number of connections per second for your DB cluster might be
limited depending on its DB instance class and your workload.
* Currently, IAM database authentication doesn't support all global condition
context keys.
For more information about global condition context keys, see AWS global
condition context keys in the IAM User Guide.
* For PostgreSQL, if the IAM role (rds_iam) is added to a user (including the
RDS master user), IAM authentication takes precedence over password
authentication, so the user must log in as an IAM user.
* For Aurora PostgreSQL, you cannot use IAM authentication to establish a
replication connection.
* You cannot use a custom Route 53 DNS record instead of the DB cluster
endpoint to generate the authentication token.
RECOMMENDATIONS FOR IAM DATABASE AUTHENTICATION
We recommend the following when using IAM database authentication:
* Use IAM database authentication when your application requires fewer than 200
new IAM database authentication connections per second.
The database engines that work with Amazon Aurora don't impose any limits on
authentication attempts per second. However, when you use IAM database
authentication, your application must generate an authentication token. Your
application then uses that token to connect to the DB cluster. If you exceed
the limit of maximum new connections per second, then the extra overhead of
IAM database authentication can cause connection throttling.
Consider using connection pooling in your applications to mitigate constant
connection creation. This can reduce the overhead from IAM DB authentication
and allow your applications to reuse existing connections. Alternatively,
consider using RDS Proxy for these use cases. RDS Proxy has additional costs.
See RDS Proxy pricing.
* The size of an IAM database authentication token depends on many things
including the number of IAM tags, IAM service policies, ARN lengths, as well
as other IAM and database properties. The minimum size of this token is
generally about 1 KB but can be larger. Since this token is used as the
password in the connection string to the database using IAM authentication,
you should ensure that your database driver (e.g., ODBC) and/or any tools do
not limit or otherwise truncate this token due to its size. A truncated token
will cause the authentication validation done by the database and IAM to
fail.
* If you are using temporary credentials when creating an IAM database
authentication token, the temporary credentials must still be valid when
using the IAM database authentication token to make a connection request.
UNSUPPORTED AWS GLOBAL CONDITION CONTEXT KEYS
IAM database authentication does not support the following subset of AWS global
condition context keys.
* aws:Referer
* aws:SourceIp
* aws:SourceVpc
* aws:SourceVpce
* aws:UserAgent
* aws:VpcSourceIp
For more information, see AWS global condition context keys in the IAM User
Guide.
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Document Conventions
Cross-service confused deputy prevention
Enabling and disabling
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