Amazon Aurora DSQL change data capture (CDC) is now generally available, enabling you to stream real-time database changes to Amazon Kinesis Data Streams for event-driven architectures and data integration workflows.

Aurora DSQL CDC automatically captures the results of insert, update, and delete operations as change events and delivers them to Kinesis Data Streams with no infrastructure to manage. You can use CDC to synchronize data across microservices, trigger AWS Lambda functions, or deliver changes to Amazon S3, Amazon Redshift, and Amazon OpenSearch Service via Amazon Data Firehose. CDC streaming is designed to have zero impact on your database workload performance.

CDC streaming is available in all AWS Regions where Aurora DSQL is available. Get started with Aurora DSQL for free with the AWS Free Tier. To learn more about CDC in Aurora DSQL, visit the documentation page.

 

​Amazon Aurora DSQL change data capture (CDC) is now generally available, enabling you to stream real-time database changes to Amazon Kinesis Data Streams for event-driven architectures and data integration workflows. Aurora DSQL CDC automatically captures the results of insert, update, and delete operations as change events and delivers them to Kinesis Data Streams with no infrastructure to manage. You can use CDC to synchronize data across microservices, trigger AWS Lambda functions, or deliver changes to Amazon S3, Amazon Redshift, and Amazon OpenSearch Service via Amazon Data Firehose. CDC streaming is designed to have zero impact on your database workload performance. CDC streaming is available in all AWS Regions where Aurora DSQL is available. Get started with Aurora DSQL for free with the AWS Free Tier. To learn more about CDC in Aurora DSQL, visit the documentation page.  

Today, AWS Security Hub introduces Network Scanning, a capability that identifies resources in your environment that are reachable from the public internet.  Network Scanning probes your resources from the internet to detect actual reachability, not just what could be reachable based on security group rules and route tables. It discovers public IP addresses, virtual machines, and load balancers across your AWS and Azure environments, identifies reachable ports, and determines what services are running behind them. This complements Security Hub’s existing network reachability findings, which identify configurations that could make a resource reachable from the internet.  Network Scanning confirms actual reachability from the internet. Each reachable port generates a Security Hub finding with evidence of the port and service discovered. Security Hub Exposures then automatically correlates these findings with other findings and resource configurations to determine broader risk.

 

​Today, AWS Security Hub introduces Network Scanning, a capability that identifies resources in your environment that are reachable from the public internet.  Network Scanning probes your resources from the internet to detect actual reachability, not just what could be reachable based on security group rules and route tables. It discovers public IP addresses, virtual machines, and load balancers across your AWS and Azure environments, identifies reachable ports, and determines what services are running behind them. This complements Security Hub’s existing network reachability findings, which identify configurations that could make a resource reachable from the internet.  Network Scanning confirms actual reachability from the internet. Each reachable port generates a Security Hub finding with evidence of the port and service discovered. Security Hub Exposures then automatically correlates these findings with other findings and resource configurations to determine broader risk.  

Amazon Redshift now supports Graviton-based RG instances on the trailing track. Starting July 7, 2026, rg.4xlarge and rg.xlarge instance types are available for customers running workloads on the trailing track (P201).

The trailing track is designed for customers who prioritize stability for production workloads, running on a version already validated through the leading track. With RG instances now available on both tracks, customers can take advantage of AWS Graviton-powered performance – delivering up to 2.4x faster query performance than RA3 instances at 30% lower price per vCPU.

To get started, customers can provision a new cluster or resize an existing cluster to an rg.4xlarge or rg.xlarge instance type on the trailing track (P201) in the AWS Management Console, AWS CLI, or AWS SDKs.

For more information, see Amazon Redshift cluster versions.

 

​Amazon Redshift now supports Graviton-based RG instances on the trailing track. Starting July 7, 2026, rg.4xlarge and rg.xlarge instance types are available for customers running workloads on the trailing track (P201).
The trailing track is designed for customers who prioritize stability for production workloads, running on a version already validated through the leading track. With RG instances now available on both tracks, customers can take advantage of AWS Graviton-powered performance – delivering up to 2.4x faster query performance than RA3 instances at 30% lower price per vCPU. To get started, customers can provision a new cluster or resize an existing cluster to an rg.4xlarge or rg.xlarge instance type on the trailing track (P201) in the AWS Management Console, AWS CLI, or AWS SDKs. For more information, see Amazon Redshift cluster versions.  

Amazon Connect Customer now supports forecasting, capacity planning, and scheduling for Tasks and Emails, enabling you to plan and optimize your workforce across all workloads (Voice, Chat, Tasks, Emails). Connect Customer accounts for the unique characteristics of each channel, including concurrent work handling, duration of work from minutes to months, and distinct service level requirements, so your forecasts and schedules reflect how your operation actually runs. For example, if your agents handle email inquiries or tasks such as case processing alongside voice calls, you can now generate a unified forecast that accounts for all of these workloads and create schedules that efficiently allocate agents across channels. Thus enabling end-to-end workforce optimization within a single solution and ensuring consistent service levels across all customer interaction channels.

This feature is available in all AWS Regions where Amazon Connect Customer agent scheduling is available. To learn more about Amazon Connect Customer agent scheduling, click here.

 

​Amazon Connect Customer now supports forecasting, capacity planning, and scheduling for Tasks and Emails, enabling you to plan and optimize your workforce across all workloads (Voice, Chat, Tasks, Emails). Connect Customer accounts for the unique characteristics of each channel, including concurrent work handling, duration of work from minutes to months, and distinct service level requirements, so your forecasts and schedules reflect how your operation actually runs. For example, if your agents handle email inquiries or tasks such as case processing alongside voice calls, you can now generate a unified forecast that accounts for all of these workloads and create schedules that efficiently allocate agents across channels. Thus enabling end-to-end workforce optimization within a single solution and ensuring consistent service levels across all customer interaction channels. This feature is available in all AWS Regions where Amazon Connect Customer agent scheduling is available. To learn more about Amazon Connect Customer agent scheduling, click here.  

Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the AWS Europe (Zurich) region. U7i instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment.

U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using 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 U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the AWS Europe (Zurich) region. U7i instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment.
U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using 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 GameLift Streams now supports Stream Session Admin Shell, a secure terminal connection to the live runtime environment of a stream session for real-time troubleshooting. You can inspect logs, query running processes, check GPU utilization, and examine application state — all without managing SSH keys, open ports, or infrastructure credentials.

Stream Session Admin Shell provides a terminal connection with the same level of access as your Amazon GameLift Streams applications. To connect, call the new CreateStreamSessionAdminShell API with your stream group and stream session identifiers, then use the returned credentials with the SSM Session Manager plugin for the AWS CLI. The feature supports Linux (Ubuntu 22.04), Proton, and Windows Server 2022 runtimes. The terminal connection is scoped to your application environment and automatically closes when the stream session ends.

Stream Session Admin Shell is available at no additional cost in all AWS Regions where Amazon GameLift Streams is offered. For a full list of supported Regions, see the AWS Region table.

To get started, see the Stream Session Admin Shell developer guide and CreateStreamSessionAdminShell API reference.

 

​Amazon GameLift Streams now supports Stream Session Admin Shell, a secure terminal connection to the live runtime environment of a stream session for real-time troubleshooting. You can inspect logs, query running processes, check GPU utilization, and examine application state — all without managing SSH keys, open ports, or infrastructure credentials. Stream Session Admin Shell provides a terminal connection with the same level of access as your Amazon GameLift Streams applications. To connect, call the new CreateStreamSessionAdminShell API with your stream group and stream session identifiers, then use the returned credentials with the SSM Session Manager plugin for the AWS CLI. The feature supports Linux (Ubuntu 22.04), Proton, and Windows Server 2022 runtimes. The terminal connection is scoped to your application environment and automatically closes when the stream session ends. Stream Session Admin Shell is available at no additional cost in all AWS Regions where Amazon GameLift Streams is offered. For a full list of supported Regions, see the AWS Region table. To get started, see the Stream Session Admin Shell developer guide and CreateStreamSessionAdminShell API reference.  

Amazon S3 Vectors is now available in AWS GovCloud (US-East) and AWS GovCloud (US-West).

Amazon S3 Vectors is purpose-built vector storage for AI agents, inference, Retrieval Augmented Generation (RAG), and semantic search at billion-vector scale. S3 Vectors is designed to provide the same elasticity, durability, and availability as Amazon S3, with a dedicated set of APIs that let you store, access, and query vectors without provisioning any infrastructure.

For a full list of AWS Regions where Amazon S3 Vectors is available, see AWS Regions and endpoints. To learn more, visit the product page, documentation, and the Amazon S3 pricing page.

 

​Amazon S3 Vectors is now available in AWS GovCloud (US-East) and AWS GovCloud (US-West).
Amazon S3 Vectors is purpose-built vector storage for AI agents, inference, Retrieval Augmented Generation (RAG), and semantic search at billion-vector scale. S3 Vectors is designed to provide the same elasticity, durability, and availability as Amazon S3, with a dedicated set of APIs that let you store, access, and query vectors without provisioning any infrastructure.
For a full list of AWS Regions where Amazon S3 Vectors is available, see AWS Regions and endpoints. To learn more, visit the product page, documentation, and the Amazon S3 pricing page.  

Today, AWS announces that AWS Security Hub now monitors Microsoft Azure resources, extending risk analytics, cloud security posture management, vulnerability management, and security response management across both clouds. Many AWS customers running workloads in AWS and Azure have had to operate separate security tools for each environment, making it difficult to prioritize risks holistically or respond consistently. Security Hub now provides a single, unified experience to detect and respond to risks across your AWS and Azure environments.

Security Hub automatically discovers Azure resources, including Azure Virtual Machines (VMs), Azure Container Registry (ACR) container images, Azure Function Apps, and Azure identities, and evaluates them for misconfigurations, internet exposure, and software vulnerabilities. You receive posture checks against security standards including the CIS Benchmarks™ for Microsoft Azure Foundations, unified resource inventory, risk and exposure analysis, and automated response through existing EventBridge integrations. AWS and Azure findings appear in the same prioritized view with the same finding formats and automation workflows, so security teams can operate from one console rather than switching between tools.

Security Hub includes an independent 30-day free trial to monitor Azure resources that begins once you create your integration with Microsoft Azure. After the trial, you pay the same price for monitoring Azure resources and equivalent AWS resources. You can create an integration to Azure from all AWS Regions where Security Hub is available except Middle East (UAE), Middle East (Bahrain), Asia Pacific (Taipei), and Asia Pacific (New Zealand). You can also create integrations to Microsoft Azure for AWS Security Hub CSPM for posture management checks and Amazon Inspector for vulnerability management independently from AWS Security Hub. To learn more, see AWS Security Hub Pricing and AWS Security Hub documentation.

 

​Today, AWS announces that AWS Security Hub now monitors Microsoft Azure resources, extending risk analytics, cloud security posture management, vulnerability management, and security response management across both clouds. Many AWS customers running workloads in AWS and Azure have had to operate separate security tools for each environment, making it difficult to prioritize risks holistically or respond consistently. Security Hub now provides a single, unified experience to detect and respond to risks across your AWS and Azure environments. Security Hub automatically discovers Azure resources, including Azure Virtual Machines (VMs), Azure Container Registry (ACR) container images, Azure Function Apps, and Azure identities, and evaluates them for misconfigurations, internet exposure, and software vulnerabilities. You receive posture checks against security standards including the CIS Benchmarks™ for Microsoft Azure Foundations, unified resource inventory, risk and exposure analysis, and automated response through existing EventBridge integrations. AWS and Azure findings appear in the same prioritized view with the same finding formats and automation workflows, so security teams can operate from one console rather than switching between tools. Security Hub includes an independent 30-day free trial to monitor Azure resources that begins once you create your integration with Microsoft Azure. After the trial, you pay the same price for monitoring Azure resources and equivalent AWS resources. You can create an integration to Azure from all AWS Regions where Security Hub is available except Middle East (UAE), Middle East (Bahrain), Asia Pacific (Taipei), and Asia Pacific (New Zealand). You can also create integrations to Microsoft Azure for AWS Security Hub CSPM for posture management checks and Amazon Inspector for vulnerability management independently from AWS Security Hub. To learn more, see AWS Security Hub Pricing and AWS Security Hub documentation.  

Amazon Redshift RG instances, powered by AWS Graviton processors, are now available in the AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. RG instances deliver better performance, running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 instances, at 30% lower price per vCPU. RG instances include Redshift’s custom-built vectorized data lake query engine that processes Apache Iceberg and Parquet data on your cluster nodes, enabling you to run SQL analytics across your data warehouse and data lake using a single engine.

RG instances are available in two instance sizes, rg.xlarge and rg.4xlarge. Customers with existing RA3 clusters can upgrade them to RG using Snapshot & 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 All Upfront, Partial Upfront, and No Upfront payment options. For pricing details, visit the Amazon Redshift pricing page.

To get started, refer to the following resources:

• Amazon Redshift RG Instance Documentation
• RA3 to RG Upgrade Guide
• Amazon Redshift Pricing

 

​Amazon Redshift RG instances, powered by AWS Graviton processors, are now available in the AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. RG instances deliver better performance, running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 instances, at 30% lower price per vCPU. RG instances include Redshift’s custom-built vectorized data lake query engine that processes Apache Iceberg and Parquet data on your cluster nodes, enabling you to run SQL analytics across your data warehouse and data lake using a single engine. RG instances are available in two instance sizes, rg.xlarge and rg.4xlarge. Customers with existing RA3 clusters can upgrade them to RG using Snapshot & 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 All Upfront, Partial Upfront, and No Upfront payment options. For pricing details, visit the Amazon Redshift pricing page. To get started, refer to the following resources:

Amazon Redshift RG Instance Documentation
RA3 to RG Upgrade Guide
Amazon Redshift Pricing  

Amazon RDS for Oracle now supports Oracle Database 26ai, Oracle’s latest Long Term Support Release, with Amazon Bedrock integration which provides access to foundation models such as Anthropic Claude, Amazon Nova, and Meta Llama. With Oracle Database 26ai, you can leverage Oracle’s Select AI feature to generate and run SQL queries from natural language prompts, increasing productivity for both developers and business users. You can also implement retrieval augmented generation (RAG) directly from SQL using Oracle AI Vector Search without moving data out of their database.

Oracle Database 26ai also includes AI Vector Search for storing vector embeddings alongside relational data and performing semantic similarity and hybrid searches without a separate vector database, JSON Relational Duality Views for accessing the same underlying data as either JSON documents or relational tables, and SQL Property Graphs for in-database graph analytics. You can create new DB instances running Oracle Database 26ai or upgrade from Oracle Database 19c or 21c container databases (CDBs). Oracle Database 26ai is available in Enterprise Edition only. To create a new Oracle Database 26ai instance, use the AWS Management Console, AWS CLI, or AWS SDK and select an Oracle 26.0.0.0 engine version. To upgrade existing Oracle Database 19c or 21c CDB instances, use the Modify DB Instance workflow and select a 26.0.0.0 engine version. If your DB instance runs Oracle Database 19c as a non-CDB, you must first convert it to the CDB architecture before upgrading to 26ai. For more information, see Converting a non-CDB to a CDB.

Amazon RDS for Oracle Database 26ai is available in all commercial AWS Regions and the AWS GovCloud (US) Regions. For more information, see Oracle Database 26ai with Amazon RDS and Amazon Bedrock integration for RDS for Oracle. 

 

​Amazon RDS for Oracle now supports Oracle Database 26ai, Oracle’s latest Long Term Support Release, with Amazon Bedrock integration which provides access to foundation models such as Anthropic Claude, Amazon Nova, and Meta Llama. With Oracle Database 26ai, you can leverage Oracle’s Select AI feature to generate and run SQL queries from natural language prompts, increasing productivity for both developers and business users. You can also implement retrieval augmented generation (RAG) directly from SQL using Oracle AI Vector Search without moving data out of their database. Oracle Database 26ai also includes AI Vector Search for storing vector embeddings alongside relational data and performing semantic similarity and hybrid searches without a separate vector database, JSON Relational Duality Views for accessing the same underlying data as either JSON documents or relational tables, and SQL Property Graphs for in-database graph analytics. You can create new DB instances running Oracle Database 26ai or upgrade from Oracle Database 19c or 21c container databases (CDBs). Oracle Database 26ai is available in Enterprise Edition only. To create a new Oracle Database 26ai instance, use the AWS Management Console, AWS CLI, or AWS SDK and select an Oracle 26.0.0.0 engine version. To upgrade existing Oracle Database 19c or 21c CDB instances, use the Modify DB Instance workflow and select a 26.0.0.0 engine version. If your DB instance runs Oracle Database 19c as a non-CDB, you must first convert it to the CDB architecture before upgrading to 26ai. For more information, see Converting a non-CDB to a CDB. Amazon RDS for Oracle Database 26ai is available in all commercial AWS Regions and the AWS GovCloud (US) Regions. For more information, see Oracle Database 26ai with Amazon RDS and Amazon Bedrock integration for RDS for Oracle.