AWS Recent Announcements

Amazon RDS io2 Block Express volumes are now available in AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. Amazon RDS io2 Block Express volumes provide consistent sub-millisecond latency for mission critical workloads. Amazon RDS io2 Block Express volumes are designed for all your critical database workloads that demand high performance, high throughput, and consistently low latency. io2 Block Express storage has the lowest p99.9 I/O latency and the best outlier latency control among major cloud providers, making it ideal for the most I/O-intensive, mission-critical database workloads. io2 Block Express supports 99.999% durability, up to 64 TiB volumes, 4,000 MB/s throughput, and up to 256,000 Provisioned IOPS for your most demanding database needs for the same price as Amazon RDS io1 volumes. You can upgrade from an Amazon RDS io1 volume to an Amazon RDS io2 Block Express without any downtime using the ModifyDBInstance API. To learn more about Amazon RDS storage, visit the Amazon RDS User’s Guide. Create or update a fully managed Amazon RDS database with an io2 Block Express volume or modify an existing io1, gp2, or gp3 volume type without disruptions in the Amazon RDS Management Console.

Today, AWS announced the opening of a new AWS Direct Connect location within the Equinix BA1 data center near Barcelona, Spain. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. This site is the first AWS Direct Connect location in Barcelona and the third AWS Direct connect location within Spain. This Direct Connect location offers dedicated 10 Gbps and 100 Gbps connections with MACsec encryption available. The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.  For more information on the over 143 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.

Amazon QuickSight has increased the limits on number of calculated fields allowed in an analysis from 500 to 2000, and from 200 to 500 per dataset. This update enables authors and data curators to create more transformations on their data and draw additional complex insights. This is especially useful for authors and data curators who work with really large datasets and cater to multiple end user personas. In regions where Amazon Q in QuickSight is available, users can also use natural language to build calculations using Q. The new calculated fields limits are now available in all supported Amazon QuickSight regions. To learn more about calculated fields and other QuickSight limits, visit item limits for analysis.

Amazon Connect now supports recurring activities in agent schedules, making it easier for you to add repeating events in a few clicks. With this launch, you can now schedule activities such as daily stand-up at 8 a.m. or team meeting every Monday at 9 a.m. as a series that automatically gets added to agent schedules. You can schedule these as individual recurring series for each agent or a shared recurring series across multiple agents. This launch eliminates the need for manually creating each occurrence as a separate activity and ensures timely addition of activities to agent schedules, thus improving manager productivity and ensuring agent schedules are up to date. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

You can now easily deliver task and email based customer experiences on your websites and applications using the new contact form option in the Amazon Connect communication widget. For example, you can add the communication widget to your website and give customers the ability to submit callback requests outside business hours or send emails through webforms. Supervisors and managers can configure customer-facing forms using the drag and drop editor and generate code snippets for seamless website integration. This expanded capability gives customers more flexible engagement options while enabling you to manage all engagements through existing Amazon Connect workflows. For region availability, please see the availability of Amazon Connect features by Region. To learn more, see our documentation. To learn more about Amazon Connect, the easy-to-use cloud contact center, visit the Amazon Connect website.

Starting today, long-term support (LTS) will also be provided on Aurora MySQL 3.10 (compatible with MySQL 8.0.42) minor version. Database clusters that use LTS releases can stay on the same minor version for at least three years or until end of standard support for the major version, whichever is sooner. During the lifetime of an Aurora MySQL LTS release, new patches introduce fixes for select high severity security and operational issues. These patches don’t include any new features. For more details about Aurora MySQL 3.10, refer to the Aurora MySQL 3.10 launch announcement and release notes. This is the second minor version designated as LTS on Aurora MySQL-Compatible Edition 3 in addition to Aurora MySQL 3.04 (compatible with MySQL 8.0.28) minor version. This LTS version does not change the end of life schedules for other LTS versions or engine major versions. For more details about LTS and how to stay on the LTS minor version, refer to LTS documentation. This LTS release is available in all AWS regions where Aurora MySQL is available. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.

Anthropic’s Claude Sonnet 4 and OpenAI’s GPT-OSS 120B and 20B models are now available for Batch inference in Amazon Bedrock. With Batch inference, you can run multiple inference requests asynchronously, improving performance on large datasets at 50% of the on-demand inference pricing. Amazon Bedrock offers select foundation models (FMs) from leading AI providers such as Anthropic, OpenAI, Meta, and Amazon for batch inference, making it easier and more cost-effective to process high-volume workloads. With Batch inference on Claude Sonnet 4 and OpenAI GPT-OSS models, you can process large datasets for scenarios such as document and customer feedback analysis, bulk content generation (e.g., marketing copy, product descriptions), large-scale prompt or output evaluations, automated summarization of knowledge bases and archives, mass categorization of support tickets or emails, and extraction of structured data from unstructured text—at scale and with lower costs. We’ve optimized our Batch offering to deliver higher overall batch throughput on these newer models compared to previous ones. In addition, you can now track your Batch workload progress at the AWS account level with Amazon CloudWatch metrics. For all models, these metrics include total pending records, processed records and tokens per minute, and for Claude models, they also include tokens pending processing. To learn more about Batch inference in Amazon Bedrock, visit the Batch inference documentation. You can visit Supported Regions and models for batch inference page for more details on supported models and follow Amazon Bedrock API reference to get started with Batch inference. 

As of today, AWS Batch has introduced two new instance type options for allowed instance types in Compute Environment default-x86_64 (default) and default-arm64. These new options will automatically select the most cost-effective instance type across different generations, based on your job queue requirements, where AWS Batch previously supported only optimal instance type. This makes it easier to run your Batch workloads with newer generation EC2 instance families and can provide better performance at a lower cost. As new instance types become available in a region, they’ll be automatically added to the corresponding default pool. To get started, you can select default-x86_64 or default-arm64 in the instanceType parameter for managed compute environments. There is no need to create a new compute environment—the existing ‘optimal’ option (which applies to M, C, and R EC2 instance familes) will continue to be supported and is not being deprecated, no action is needed. However, please be aware that only ENABLED and VALID Compute Environments (CEs) will be automatically updated with new instance types. If you have any DISABLED or INVALID CEs, they will receive updates once they are re-enabled and set to a VALID state. This capability is now available for AWS Batch in all commercial and the AWS GovCloud (US) Regions. To learn more, see our launch blog, visit Batch’s documentation page or the Batch troubleshooting User Guide.

Amazon S3 provides a new way to verify the content of stored datasets. You can efficiently verify billions of objects and automatically generate integrity reports to prove that your datasets remain intact over time using S3 Batch Operations. This capability works with any object stored in S3, regardless of storage class or object size, without the need to restore or download data. Whether you’re verifying objects for data preservation, accuracy checks, or compliance requirements, you can reduce the cost, time, and effort required. With S3 Batch Operations, you can create a compute checksum job for your objects. To get started, provide a list of objects (called a manifest) or specify the bucket with filters like prefix or suffix. Then choose “Compute checksum” as the operation type and select from supported algorithms including SHA-1, SHA-256, CRC32, CRC32C, CRC64, and MD5. When the job completes, you receive a detailed report with checksum information for all processed objects. You can use this report for compliance or audit purposes. This capability complements S3’s built-in validation, letting you independently verify your stored data any time. This new data verification, compute checksum operation, is now available in all AWS Regions. For pricing details, visit the S3 pricing page. To learn more, visit the S3 User Guide.

AWS Marketplace now offers a streamlined fulfillment experience for Amazon Machine Image (AMI) and AMI with CloudFormation products across both the AWS Marketplace website and console. Additionally, users can now also access the new launch experience for container products directly within AWS Marketplace console. The new fulfillment experience in AWS Marketplace simplifies product deployment for AMI products by combining the configuration and fulfillment experience into a single page, clearly presenting fulfillment options and AWS services available for purchased products. Users will also have access to new resources, including detailed guides from AWS Marketplace Sellers. The new experience is available through both the AWS Marketplace website and console, in all AWS Marketplace supported commercial regions and languages, delivering a consistent experience worldwide. To learn more about the new fulfillment experience for AMI-based products in AWS Marketplace and how it can benefit your organization, visit the AWS Marketplace Buyer Guide or start exploring AMI products in AWS Marketplace today.

Amazon S3 Express One Zone, a high-performance S3 storage class for latency-sensitive applications, now supports resilience testing with AWS Fault Injection Service (FIS). With this launch, you can use the FIS network disruption action to test the failover response and recovery of your latency-sensitive applications in the unlikely event of a disruption to an Availability Zone (AZ) that impairs access to your data. You can use the results of FIS experiments to verify your monitoring, test recovery processes, and improve application resilience. With FIS, you can disrupt connectivity to your S3 Express One Zone data in S3 directory buckets, helping you validate application resilience. During the FIS experiment, data plane requests made to directory buckets will timeout. This fault action is also included in the FIS AZ Availability: Power Interruption scenario, so you can test the resilience of your applications when an AZ event impacts multiple AWS services. You can use the updated FIS network disruption action for S3 Express One Zone data in all AWS Regions where the storage class is available. To get started with testing the resilience of applications that store data in S3 Express One Zone, you can use the AWS Management Console, AWS CLI, or FIS API. For pricing information, visit the FIS pricing page. To learn more, visit the AWS FIS user guide.

Amazon Athena now supports CREATE TABLE AS SELECT (CTAS) statements with Amazon S3 Tables. Using CTAS statements makes it simple to create a new table and populate it with data using the results of a SELECT query. You can now use CTAS statements in Athena to query existing datasets and create a new table in S3 Tables with the query results, all in a single SQL statement. S3 Tables deliver the first cloud object store with built-in Apache Iceberg support and streamline storing tabular data at scale. With today’s launch, you can quickly and efficiently convert existing datasets stored in Parquet, CSV, JSON, and other formats, including Apache Iceberg, Hudi, and Delta Lake, into fully-managed tables that are continually optimized for performance and cost. Once created, use Athena to analyze your data, JOIN it with other datasets, and evolve it over time using INSERT and UPDATE operations. Using CTAS, you can partition the data on the fly, giving you flexibility to optimize query performance for different use cases. You can use CTAS to create S3 Tables in all AWS Regions where both Athena and S3 Tables are supported. To learn more, see the Amazon Athena User Guide.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS Asia Pacific (Jakarta)region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

DynamoDB now supports more granular throttling exceptions along with their corresponding Amazon CloudWatch metrics. The additional fields in the new throttling exceptions identify the specific resources and reasons for throttling events, making it easier to understand and diagnose throttling-related issues. You can see the new Amazon CloudWatch metrics immediately, and upon upgrading your SDK to the newest version, you will also see the new granular throttling exceptions. Every throttling exception now contains a list of reasons why the request was throttled, as well as the Amazon Resource Name (ARN) of the table or index that was throttled. These new throttle exception reasons help you understand why you were throttled and enable you to take corrective actions like adjusting your configured throughput, switching your table to on-demand capacity mode, or optimizing data access patterns. The more granular throttling exceptions and their respective metrics are available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. To get started see the following list of resources: Diagnosing throttling issues in the DynamoDB developer guide Enhanced throttling observability in Amazon DynamoDB blog post Troubleshooting throttling in the DynamoDB developer guide

DynamoDB now supports the ability to selectively emit events for throttled keys to CloudWatch Contributor Insights, enabling you to monitor throttled keys without emitting events for all accessed keys. By emitting events for throttled keys exclusively, you no longer need to pay for all of your successful request events. Cloudwatch Contributor Insights for DynamoDB can help you understand your traffic patterns by providing information about your most accessed and throttled keys in a table or global secondary index. This information can be used to understand your application usage patterns or diagnose throttling-related issues. By choosing to only emit events for throttled keys, you can reduce the amount you spend to receive these insights. The new mode to exclusively emit throttled key events to CloudWatch Contributor Insights is available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. To get started, see the following list of resources: CloudWatch Contributor Insights for DynamoDB in the DynamoDB developer guide Enhanced throttling observability in Amazon DynamoDB blog post Troubleshooting throttling in the DynamoDB developer guide

AWS Certificate Manager (ACM) now supports AWS PrivateLink so that you can access ACM APIs from your Amazon Virtual Private Cloud (VPC) without traversing the public internet. This feature can help you meet compliance requirements by allowing you to access and use ACM APIs entirely within the AWS network. ACM simplifies the process of provisioning and managing public and private TLS certificates, wherever you need to securely terminate traffic; Whether it’s with integrated AWS services such as Amazon CloudFront, Load Balancing or with hybrid workloads. You can now create interface endpoints in AWS Private Link to connect your VPC to ACM. Communication between your VPC and ACM is then conducted entirely within the AWS network, providing a secure pathway for your data. To get started, you can create an AWS PrivateLink to connect to ACM using the AWS Management Console or AWS Command Line Interface (AWS CLI) commands or AWS CloudFormation. This new feature is available in all AWS Regions including AWS GovCloud (US) and China Regions where AWS Certificate Manager Service and AWS PrivateLink are available. For more information, please refer to the AWS PrivateLink documentation.

Amazon Managed Service for Prometheus, a fully managed Prometheus-compatible monitoring service, now supports resource-based policies, making it easier to build applications that work across accounts. With resource-based policies, you can specify which Identity and Access Management (IAM) principals have access to ingest or query your Amazon Managed Service for Prometheus workspace. To allow cross-account ingestion into an Amazon Managed Service for Prometheus workspace or query the metrics using PromQL from a different account, customers so far had to assume an IAM role in the workspace owner account. With this launch, you now can attach a resource-based policy to an Amazon Managed Service for Prometheus workspace and allow-list non-workspace owner to perform any actions using Prometheus-compatible APIs. This feature is now available in all regions where Amazon Managed Service for Prometheus is generally available. To learn more about Amazon Managed Service for Prometheus collector, visit the user guide or product page.

Starting today, customers can view 6 new recommended actions added to the existing list of 15 recommended actions available in the AWS Billing and Cost Management Console recommended actions widget. These recommended actions include notifications across AWS payments and tax settings, such as an expired payment method or if tax registration numbers are invalid. All recommended actions are now categorized as critical, advisory, or informational, enabling customers to prioritize and timely resolve any identified billing issues.  Using recommended actions on the AWS Billing and Cost Management Console, customers can quickly learn of and mitigate AWS billing or payment issues, identify cost saving opportunities, and avoid surprises by acting on time-sensitive information. Each recommended action includes a specific call-to-action, which allows customers to optimize their AWS spend and prevent any disruptions to their AWS account and billing status. Customers can access these recommendation actions through the recommended actions widget in the console or via a new public API at no additional cost. The recommended actions widget and API is available in all AWS commercial regions, excluding China. To get started with new recommended actions, visit the recommended actions widgets on the AWS Billing and Cost Management Console. To learn more, see recommended actions in the AWS Billing and Cost Management user guide

Amazon Relational Database Service (RDS) for Db2 now supports cross-region automated backups for encrypted databases, providing customers with an additional layer of data protection while safeguarding their mission critical Db2 workloads against regional outages. Customers can now securely copy encrypted database snapshots to regions outside of their primary AWS region for improved disaster recovery. The feature can be enabled by simply turning on encryption for RDS for Db2 instances, and configuring backup replication to the desired AWS region. To learn more about Amazon RDS for Db2 cross-region automated backups and the supported destination regions, visit the documentation page. Amazon RDS for Db2 makes it simple to set up, operate, and scale Db2 deployments in the cloud. See Amazon RDS for Db2 Pricing for up-to-date pricing of instances, storage, backup, data transfer, and regional availability.

Today, we’re announcing the integration of Amazon Neptune Analytics with Cognee, a leading agentic memory framework designed to help AI agents structure, retrieve, and reason over information. With this launch, customers can use Neptune as the graph store behind Cognee’s memory layer, enabling long-term memory and reasoning capabilities for agentic AI applications. This integration allows Cognee users to store and query memory graphs at scale, unlocking advanced use cases where AI agents become more personalized and effective over time by learning from ongoing interactions. Neptune supports multi-hop graph reasoning and hybrid retrieval across graph, vector, and keyword modalities—helping Cognee deliver richer, more context-aware AI experiences. Cognee enables a self-improving memory system that helps developers build cost-efficient, personalized generative AI applications. To learn more about the Neptune–Cognee integration, visit the User Guide and the sample notebook.

Amazon Connect Cases now supports Contact Lens Rules that automatically update cases when created, streamlining case workflows and reducing manual tasks. For example, you can configure rules to auto-assign refund cases to the billing team, auto-close cases that don’t require follow-up, or automatically set priority based on case reason. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.

Amazon VPC now allows customers to route inbound internet traffic destined for large pools of public IP addresses, to a single elastic network interface (ENI) within a VPC. Prior to this enhancement, internet gateways only accepted traffic destined to public IP addresses that were associated with network interfaces in the VPC. There are limits to the number of IP addresses that can be associated with network interfaces. These limits depend on the instance type and can be found in our documentation. There are use cases in Telco, Internet of Things (IoT) and other industries that require customers to route inbound traffic destined for public IP pools, larger than the allowed limits, to a single network interface. Customers would earlier perform address translation to consolidate traffic for such large number of IP addresses. This enhancement removes the need to perform address translation on inbound internet connections for these Telco and IoT use cases. Customers can bring their own public IP pools (BYOIP documentation) and configure their VPC Internet Gateway to accept traffic belonging to this BYOIP pool and route it to a network interface. They can also use this feature with VPC Route Server and dynamically update their routes in events of failure. Refer to our public documentation for details on VPC Route Server. This enhancement is now available across all AWS commercial, AWS China and GovCloud regions. To learn more about this feature, please refer to our documentation.

Amazon Relational Database Service (Amazon RDS) for MariaDB now supports community MariaDB minor versions 11.4.8, 10.11.14 and 10.6.23. We recommend that you upgrade to the latest minor versions to fix known security vulnerabilities in prior versions of MariaDB, and to benefit from the bug fixes, performance improvements, and new functionality added by the MariaDB community. You can leverage automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also leverage Amazon RDS Managed Blue/Green deployments for safer, simpler, and faster updates to your MariaDB instances. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments, in the Amazon RDS User Guide. Amazon RDS for MariaDB makes it straightforward to set up, operate, and scale MariaDB deployments in the cloud. Learn more about pricing details and regional availability at Amazon RDS for MariaDB. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console.

AWS has increased the account sharing limits for AWS Managed Microsoft AD directory sharing, allowing customers to share their directories with significantly more AWS accounts. The Standard Edition limit has increased from 5 to 25 accounts, while the Enterprise Edition limit has expanded from 125 to 500 accounts. These enhanced limits remove previous technical constraints and enable organizations to scale their directory infrastructure more effectively across their AWS environments. The increased limits help enterprise customers consolidate their Active Directory infrastructure and reduce operational complexity by supporting larger AWS account footprints from a single managed directory. Organizations can now centralize authentication and management across hundreds of AWS accounts, which in turn helps eliminate the need for complex workarounds with multiple directory deployments. This feature enhancement is available in all AWS Regions where AWS Managed Microsoft AD is currently supported. To learn more about AWS Managed Microsoft AD directory sharing, see the AWS Directory Service documentation . For detailed information about directory sharing capabilities and setup, visit the AWS Managed Microsoft AD directory sharing page . For regional availability, see the AWS Region table.

SageMaker HyperPod task governance now supports fine-grained compute quota allocation of GPU, Trainium accelerator, vCPU, and vCPU memory within an instance. Administrators can allocate fine-grained compute quota across teams, optimizing compute resource distribution and staying within budget. Data scientists often execute LLM tasks, like training or inference, that do not require entire HyperPod instances, leading to underutilization of accelerated compute resources. HyperPod task governance enables administrators to manage compute quota allocation across teams. With this capability, administrators can now strategically allocate compute resources, ensuring fair access, preventing resource monopolization, and maximizing cluster utilization. This capability enables fine-grained compute quota allocation in addition to instance-level allocation, aligning with organizational workload demands. SageMaker HyperPod task governance is available in all AWS Regions where HyperPod is available: US East (N. Virginia), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), and South America (São Paulo). To learn more, visit SageMaker HyperPod webpage, and HyperPod task governance documentation.

Starting today, Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the US East (Ohio) region. U7i-12tb 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.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS Asia Pacific (Jakarta)region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

Amazon OpenSearch Service expands its modernized operational analytics experience to seven new regions, including Asia Pacific (Hyderabad), Asia Pacific (Osaka), Asia Pacific (Seoul), Europe (Milan), Europe (Zurich), Europe (Spain), and US-West (N. California) enabling users to gain insights across data spanning managed domains and serverless collections from a single endpoint. The expansion includes Workspaces to enhance collaboration and productivity, allowing teams to create dedicated spaces. Discover is revamped to provide a unified log exploration experience supporting languages such as Piped-Processing-Language (PPL) and SQL, in addition to DQL and Lucene. Discover now features a data selector to support multiple sources, new visual design and query autocomplete for improved usability. This experience ensures users can access the latest UI enhancements, regardless of version of underlying managed cluster or collection. The expanded OpenSearch analytics helps users gain insights from their operational data by providing purpose-built features for observability, security analytics, and search use cases. With the enhanced Discover interface, users can now analyze data from multiple sources without switching tools, improving efficiency. Workspaces enable better collaboration by creating dedicated environments for teams to work on dashboards, saved queries, and other relevant content. Availability of the latest UI updates across all versions ensures uninterrupted access to the newest features and tools. OpenSearch UI can connect to OpenSearch domains (above version 1.3) and OpenSearch serverless collections. It is now available in 22 AWS commercial regions. To get started, create an OpenSearch application in AWS Management Console. Learn more at Amazon OpenSearch Service Developer Guide.

Amazon Web Services (AWS) announces the availability of Amazon EC2 I7ie instances in the AWS Europe (Stockholm), Asia Pacific (Jakarta), and US West (N. California) regions. Designed for large storage I/O intensive workloads, these new instances are powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over previous generation I3en instances. I7ie instances offer up to 120TB local NVMe storage density—the highest available in the cloud for storage optimized instances—and deliver up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, these instances achieve up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances. Additionally, torn write prevention feature support up to 16KB block sizes, enables customers to eliminate performance bottlenecks for database workloads. I7ie instances are high-density storage-optimized instances, for workloads that demand rapid local storage with high random read/write performance and consistently low latency for accessing large data sets. These instances are offered in eleven different sizes including 2 metal sizes, providing flexibility for customers computational needs. They deliver up to 100 Gbps of network performance bandwidth, and 60 Gbps of dedicated bandwidth for Amazon Elastic Block Store (EBS), ensuring fast and efficient data transfer for applications. To learn more, visit the I7ie instances page.

SageMaker HyperPod task governance now supports Topology Aware Scheduling (TAS), enabling data scientists to schedule their large language model (LLM) tasks on an optimal network topology that minimizes network communication and enhances training efficiency. LLM training and fine-tuning tasks that are distributed across multiple accelerated compute instances frequently exchange large volumes of data between them. Multiple network hops between instances can result in higher communication latency, impacting LLM task performance. SageMaker HyperPod task governance now enables data scientists to use network topology information when scheduling tasks with specific topology preferences. Using network topology in HyperPod, SageMaker HyperPod task governance automatically schedules tasks in optimal locations, reducing instance-to-instance communication and enhancing training efficiency. SageMaker HyperPod task governance is available in all AWS Regions where HyperPod is available: US West (N. California), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm). To learn more, visit SageMaker HyperPod webpage, and SageMaker HyperPod task governance documentation.