Amazon RDS for PostgreSQL 19 Beta 2 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 2 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database.

PostgreSQL 19 introduces parallel autovacuum with configurable worker limits, so routine maintenance no longer bottlenecks large databases. The new REPACK CONCURRENTLY command rebuilds tables and reclaims storage online, keeping production databases accessible without third-party extensions. Native SQL Property Graph Queries (SQL/PGQ) let you express relationship traversals directly in standard SQL, eliminating separate application logic. Logical replication now synchronizes sequence values automatically and can be enabled dynamically without a server restart, reducing planned downtime. Beta 2 adds bug fixes and stability improvements from the Beta 1 testing period, including refinements to parallel autovacuum worker coordination and REPACK CONCURRENTLY lock handling. Please refer to PostgreSQL community announcement for more details.

Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment.

Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.

 

​Amazon RDS for PostgreSQL 19 Beta 2 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 2 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database. PostgreSQL 19 introduces parallel autovacuum with configurable worker limits, so routine maintenance no longer bottlenecks large databases. The new REPACK CONCURRENTLY command rebuilds tables and reclaims storage online, keeping production databases accessible without third-party extensions. Native SQL Property Graph Queries (SQL/PGQ) let you express relationship traversals directly in standard SQL, eliminating separate application logic. Logical replication now synchronizes sequence values automatically and can be enabled dynamically without a server restart, reducing planned downtime. Beta 2 adds bug fixes and stability improvements from the Beta 1 testing period, including refinements to parallel autovacuum worker coordination and REPACK CONCURRENTLY lock handling. Please refer to PostgreSQL community announcement for more details. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment. Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.  

Amazon Redshift announces the general availability of two new RG instance sizes – rg.large and rg.12xlarge. These new sizes deliver the same Graviton-powered performance benefits as existing RG instances, including up to 2.4x faster query performance than previous-generation RA3 instances at 30% lower price per vCPU, giving you more flexibility to right-size your provisioned clusters for any workload.

rg.large and rg.12xlarge instance sizes are available on the current track (P202) only. Customers on the trailing track (P201) can continue to use rg.xlarge and rg.4xlarge. Existing RA3 clusters can migrate to RG instances using Snapshot and Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with No Upfront payment.

The new rg.large and rg.12xlarge instance sizes are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), Mexico (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Thailand), and Asia Pacific (Melbourne).

To get started, refer to the following resources:

• Amazon Redshift node types
• RA3 to RG upgrade guide
• Amazon Redshift cluster versions
• Amazon Redshift pricing

 

​Amazon Redshift announces the general availability of two new RG instance sizes – rg.large and rg.12xlarge. These new sizes deliver the same Graviton-powered performance benefits as existing RG instances, including up to 2.4x faster query performance than previous-generation RA3 instances at 30% lower price per vCPU, giving you more flexibility to right-size your provisioned clusters for any workload. rg.large and rg.12xlarge instance sizes are available on the current track (P202) only. Customers on the trailing track (P201) can continue to use rg.xlarge and rg.4xlarge. Existing RA3 clusters can migrate to RG instances using Snapshot and Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with No Upfront payment.
The new rg.large and rg.12xlarge instance sizes are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), Mexico (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Thailand), and Asia Pacific (Melbourne). To get started, refer to the following resources:

Amazon Redshift node types
RA3 to RG upgrade guide
Amazon Redshift cluster versions
Amazon Redshift pricing  

Amazon EC2 now surfaces the AWS Systems Manager (SSM) Parameter Store parameters associated with public AMIs directly in the AMI metadata. When you describe a public AMI, the response includes the associated public SSM parameter, making it easy to discover and reference in your configurations.

Previously, finding the SSM parameter associated with a public AMI required searching through SSM parameter namespaces manually. Now, when you describe a public AMI, the response includes the public SSM parameter it is associated with. This allows you to discover the SSM parameter for a public AMI easily and use it as an alias that always resolves to the latest version, simplifying AMI updates across your infrastructure.

This capability is available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions. To learn more, please visit the documentation.

 

​Amazon EC2 now surfaces the AWS Systems Manager (SSM) Parameter Store parameters associated with public AMIs directly in the AMI metadata. When you describe a public AMI, the response includes the associated public SSM parameter, making it easy to discover and reference in your configurations.
Previously, finding the SSM parameter associated with a public AMI required searching through SSM parameter namespaces manually. Now, when you describe a public AMI, the response includes the public SSM parameter it is associated with. This allows you to discover the SSM parameter for a public AMI easily and use it as an alias that always resolves to the latest version, simplifying AMI updates across your infrastructure. This capability is available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions. To learn more, please visit the documentation.  

Amazon S3 Event Notifications now include system-generated tags in events delivered to all destinations including Amazon EventBridge, Amazon SQS, Amazon SNS, and AWS Lambda. System-generated tags are metadata labels attached to your bucket by AWS services. You can use these tags to filter events from thousands of buckets with a single EventBridge rule, instead of listing each bucket name individually.

To get started, enable S3 Event Notifications on your general purpose buckets through the AWS Management Console, AWS SDK, or AWS CLI. If AWS services like AWS CloudFormation have already applied system-generated tags to your buckets, S3 automatically includes them in new event notifications. System-generated tags in S3 Event Notifications are available at no additional cost in all AWS Regions and require no changes to existing configurations. To learn more, visit the S3 Event Notifications documentation.

 

​Amazon S3 Event Notifications now include system-generated tags in events delivered to all destinations including Amazon EventBridge, Amazon SQS, Amazon SNS, and AWS Lambda. System-generated tags are metadata labels attached to your bucket by AWS services. You can use these tags to filter events from thousands of buckets with a single EventBridge rule, instead of listing each bucket name individually. To get started, enable S3 Event Notifications on your general purpose buckets through the AWS Management Console, AWS SDK, or AWS CLI. If AWS services like AWS CloudFormation have already applied system-generated tags to your buckets, S3 automatically includes them in new event notifications. System-generated tags in S3 Event Notifications are available at no additional cost in all AWS Regions and require no changes to existing configurations. To learn more, visit the S3 Event Notifications documentation.  

Amazon EC2 High Memory U7in-24TB instances (u7in-24tb.224xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances.

U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.

To learn more about U7i instances, visit the High Memory instances page.

 

​Amazon EC2 High Memory U7in-24TB instances (u7in-24tb.224xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7in-24TB instances offer 24 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances.
U7in-24TB instances deliver 896 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 200 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.
To learn more about U7i instances, visit the High Memory instances page.  

AWS Control Tower Account Factory for Terraform (AFT) can now automatically re-apply an account’s customizations when that account moves to a different Organizational Unit (OU). Previously, moving an enrolled account between OUs required manually triggering customization re-application, creating operational overhead and risk of configuration drift. With this capability, you can opt in to automatic re-application in your AFT deployment, so accounts stay consistent with their OU-specific configuration as soon as they’re moved.

To enable this capability, set aft_customization_triggers = [«account_move»] in your AFT configuration. The re-application workflow skips the bootstrap and provisioning phases, running only global and account-level customizations for faster execution. Individual accounts can be excluded from this behavior by setting account_skip_customization_triggers = «true», giving teams precise control over which accounts participate in automated re-application.

This release also includes additional improvements: support for custom Terraform Cloud and Enterprise workspace naming variables, tighter access controls on the AFT logging bucket, and improved scaling for large-scale AWS Enterprise Support enrollment. Organizations enforcing compliance or security baselines tied to OU membership will benefit most from these combined enhancements.

This capability is available today across all AWS regions where AWS Control Tower Account Factory for Terraform is offered. To learn more about enabling automatic customization re-application and upgrading to the latest AFT release, visit the AFT documentation and review the AFT release notes on GitHub.

 

​AWS Control Tower Account Factory for Terraform (AFT) can now automatically re-apply an account’s customizations when that account moves to a different Organizational Unit (OU). Previously, moving an enrolled account between OUs required manually triggering customization re-application, creating operational overhead and risk of configuration drift. With this capability, you can opt in to automatic re-application in your AFT deployment, so accounts stay consistent with their OU-specific configuration as soon as they’re moved.
To enable this capability, set aft_customization_triggers = [«account_move»] in your AFT configuration. The re-application workflow skips the bootstrap and provisioning phases, running only global and account-level customizations for faster execution. Individual accounts can be excluded from this behavior by setting account_skip_customization_triggers = «true», giving teams precise control over which accounts participate in automated re-application.
This release also includes additional improvements: support for custom Terraform Cloud and Enterprise workspace naming variables, tighter access controls on the AFT logging bucket, and improved scaling for large-scale AWS Enterprise Support enrollment. Organizations enforcing compliance or security baselines tied to OU membership will benefit most from these combined enhancements.
This capability is available today across all AWS regions where AWS Control Tower Account Factory for Terraform is offered. To learn more about enabling automatic customization re-application and upgrading to the latest AFT release, visit the AFT documentation and review the AFT release notes on GitHub.  

Amazon CloudWatch Logs Insights query language now supports 25 new commands and functions that expand your ability to query, transform, correlate, and analyze logs. Customers analyzing logs in CloudWatch Logs Insights often need to perform statistical aggregation, handle null values in time-series data, compare logs across time windows, detect outliers, and enrich events with lookup data.

With this launch, CloudWatch Logs Insights adds type conversion and encoding functions (hexToAscii, hexToDec, decToHex), date and time functions (parseDate, formatDate, queryStartTime, queryEndTime, queryTimeRange), string functions (messageSize), JSON inspection functions (jsonArraySize, jsonArrayContains), and a conditional validation function (isNumeric). It also introduces statistical commands (variance, topk, countFrequent), row-sequencing and null-handling commands (autoregress, accum, filldown, fillmissing), sessionization and time-comparison commands (sessionize, logcompare), a data analysis command (outlier), query-composition and join commands (where, appendcols), and a lookup enrichment command (cidrlookup).

These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.

 

​Amazon CloudWatch Logs Insights query language now supports 25 new commands and functions that expand your ability to query, transform, correlate, and analyze logs. Customers analyzing logs in CloudWatch Logs Insights often need to perform statistical aggregation, handle null values in time-series data, compare logs across time windows, detect outliers, and enrich events with lookup data. With this launch, CloudWatch Logs Insights adds type conversion and encoding functions (hexToAscii, hexToDec, decToHex), date and time functions (parseDate, formatDate, queryStartTime, queryEndTime, queryTimeRange), string functions (messageSize), JSON inspection functions (jsonArraySize, jsonArrayContains), and a conditional validation function (isNumeric). It also introduces statistical commands (variance, topk, countFrequent), row-sequencing and null-handling commands (autoregress, accum, filldown, fillmissing), sessionization and time-comparison commands (sessionize, logcompare), a data analysis command (outlier), query-composition and join commands (where, appendcols), and a lookup enrichment command (cidrlookup). These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in the AWS Europe (Frankfurt, Stockholm) and Asia Pacific (Mumbai) Regions. G7e instances offer up to 2.3x inference performance compared to G6e.

Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads.

You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain, London, Frankfurt, Stockholm) and Asia Pacific (Tokyo, Seoul, Mumbai). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans.

To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in the AWS Europe (Frankfurt, Stockholm) and Asia Pacific (Mumbai) Regions. G7e instances offer up to 2.3x inference performance compared to G6e.
Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads.
You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain, London, Frankfurt, Stockholm) and Asia Pacific (Tokyo, Seoul, Mumbai). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans.
To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.  

Amazon CloudWatch Logs now supports intelligent storage tiering, which automatically classifies your log data across three storage tiers – Standard (existing), Infrequent Access, and Archive Instant Access based on access patterns. This allows you to store logs in Amazon CloudWatch for extended periods at lower-cost tiers without any operational overhead.

With today’s launch, customers can now retain high-volume verbose logs needed to be stored for longer periods at a lower cost in Amazon CloudWatch. Instead of filtering these logs or exporting them, you can now keep them natively in Amazon CloudWatch and benefit from the same query experience regardless of which tier your data resides in. Amazon CloudWatch monitors access patterns and automatically reclassifies data not accessed for 30 days to the Infrequent Access tier, and data not accessed for 90 days to the Archive Instant Access tier. When you access older data, it is automatically promoted back to the Standard tier for 30 days. By consolidating all your logs in CloudWatch, you get full visibility in one tool, thereby eliminating the operational overhead of managing multiple storage solutions and reducing your Mean Time to Resolution (MTTR) by analyzing, and alerting on all your logs in a single place.

Amazon CloudWatch Logs Intelligent-Tiering is available in all AWS commercial regions except Middle East (Bahrain) and Middle East (UAE). You can enable intelligent tiering at the account level in the AWS Management Console, AWS SDKs or through AWS CLI. Learn more about CloudWatch Logs intelligent tiering pricing and documentation.

 

​Amazon CloudWatch Logs now supports intelligent storage tiering, which automatically classifies your log data across three storage tiers – Standard (existing), Infrequent Access, and Archive Instant Access based on access patterns. This allows you to store logs in Amazon CloudWatch for extended periods at lower-cost tiers without any operational overhead.
With today’s launch, customers can now retain high-volume verbose logs needed to be stored for longer periods at a lower cost in Amazon CloudWatch. Instead of filtering these logs or exporting them, you can now keep them natively in Amazon CloudWatch and benefit from the same query experience regardless of which tier your data resides in. Amazon CloudWatch monitors access patterns and automatically reclassifies data not accessed for 30 days to the Infrequent Access tier, and data not accessed for 90 days to the Archive Instant Access tier. When you access older data, it is automatically promoted back to the Standard tier for 30 days. By consolidating all your logs in CloudWatch, you get full visibility in one tool, thereby eliminating the operational overhead of managing multiple storage solutions and reducing your Mean Time to Resolution (MTTR) by analyzing, and alerting on all your logs in a single place.
Amazon CloudWatch Logs Intelligent-Tiering is available in all AWS commercial regions except Middle East (Bahrain) and Middle East (UAE). You can enable intelligent tiering at the account level in the AWS Management Console, AWS SDKs or through AWS CLI. Learn more about CloudWatch Logs intelligent tiering pricing and documentation.  

Amazon Cognito now supports importing users with password hashes in CSV user imports. Previously, users imported from a CSV file had to reset their passwords on first sign-in. Now, you can include password hashes in your CSV file so that imported users can sign in immediately with their existing credentials.

When creating a CSV import, you specify the password hashing algorithm used by your source system. Amazon Cognito imports these users and verifies their password against the imported hash on first sign-in. Supported algorithms include bcrypt, scrypt, Argon2id, and PBKDF2 with SHA-256. All imported hashes receive an additional layer of cryptographic protection before storage.

Password hash import is available in all AWS Regions where Amazon Cognito is available. To get started, create a user import using the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kits (SDKs). See the developer guide for instructions.

 

​Amazon Cognito now supports importing users with password hashes in CSV user imports. Previously, users imported from a CSV file had to reset their passwords on first sign-in. Now, you can include password hashes in your CSV file so that imported users can sign in immediately with their existing credentials. When creating a CSV import, you specify the password hashing algorithm used by your source system. Amazon Cognito imports these users and verifies their password against the imported hash on first sign-in. Supported algorithms include bcrypt, scrypt, Argon2id, and PBKDF2 with SHA-256. All imported hashes receive an additional layer of cryptographic protection before storage. Password hash import is available in all AWS Regions where Amazon Cognito is available. To get started, create a user import using the AWS Management Console, AWS Command Line Interface (CLI), or AWS Software Development Kits (SDKs). See the developer guide for instructions.