AWS announces https://aws.amazon.com/hpc/dcv/ support for https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-mac-instances.html powered by Apple silicon, bringing high-performance remote desktop capabilities to macOS workloads in the cloud. You can now access your EC2 Mac instances with the same security and performance that Amazon DCV provides across other platforms. This integration is specifically designed for EC2 Mac instances running on Apple silicon processors. With Amazon DCV, you can connect to your EC2 Mac instances from Windows, Linux, macOS, or web clients with support for 4K resolution, multiple monitors, and smooth 60 FPS performance. The support includes essential productivity features like time zone redirection and audio output, making remote Mac development seamless. Amazon DCV's proven security architecture and optimized streaming protocols ensure your macOS applications run efficiently while maintaining data protection standards. Amazon DCV support for EC2 Mac instances is available in all AWS Regions where https://docs.aws.amazon.com/ec2/latest/instancetypes/ec2-instance-regions.html. To get started, see the https://docs.aws.amazon.com/dcv/latest/adminguide/what-is-dcv.html for installing and configuring DCV server on EC2 Mac instances.

来館案内 目次   時間・休館日 【開館時間】 10:00〜17:00（入館は16:30まで）※展帆日は9:30開館となります。   【休館日（2025年度）】   入館料等 ※１団体割引料... Read more »

Starting today, you can add warm pools to Auto Scaling groups (ASGs) that have https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-mixed-instances-groups.html. With warm pools, customers can improve the elasticity of their applications by creating a pool of pre-initialized EC2 instances that are ready to quickly serve application traffic. By combining warm pools with instance type flexibility, an ASG can rapidly scale out to its maximum size at any time, deploying applications across multiple instance types to enhance availability. Warm pools are particularly beneficial for applications with lengthy initialization processes, such as writing large amounts of data to disk, running complex custom scripts, or other time-consuming setup procedures that can take several minutes or longer to serve traffic. With this new release, the warm pool feature now works seamlessly with ASGs configured for multiple On-Demand instance types, whether specified through manual instance type lists or attribute-based instance type selection. The combination of instance type flexibility and warm pools provides a powerful solution that helps customers scale out efficiently while maximizing availability. The warm pool feature is available through the https://console.aws.amazon.com/console/home, the https://aws.amazon.com/tools/, and the https://aws.amazon.com/cli/. It is available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ and https://aws.amazon.com/govcloud-us/ Regions. To learn more about warm pools, visit this https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-warm-pools.html.

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Describes the operators that you can use in the Condition element of the IAM JSON policy language.

AWS Transfer Family https://docs.aws.amazon.com/transfer/latest/userguide/creating-connectors.html can now connect to remote SFTP servers through your Amazon Virtual Private Cloud (VPC). This enables you to transfer files between Amazon S3 and any SFTP server, whether privately or publicly hosted, while leveraging the security controls and network configurations already defined in your VPC. By utilizing your NAT Gateways' bandwidth for file transfers over SFTP, you can achieve improved transfer performance and ensure compatibility with remote firewalls. https://aws.amazon.com/aws-transfer-family/ provides fully managed file transfers over SFTP, FTP, FTPS, AS2 and web-browser based interfaces. You can now use Transfer Family SFTP connectors to connect with SFTP servers that are only accessible from your VPC, including on-premises systems, external servers shared over private networks, or in-VPC servers. You can present the IP addresses from your VPC’s CIDR range for compatibility with IP controls, and achieve higher bandwidth for large-scale transfers via your NAT gateways when connecting over the internet. All connections are routed through your VPC’s existing networking and security controls, such as AWS Transit Gateway, centralized firewalls and traffic inspection points, helping you meet data security mandates. SFTP connectors support for VPC-based connectivity is available in select AWS Regions. To get started, visit the AWS Transfer Family console, or use AWS CLI/SDK. To learn more, read the https://aws.amazon.com/blogs/aws/aws-transfer-family-sftp-connectors-now-support-vpc-based-connectivity or visit the https://docs.aws.amazon.com/transfer/latest/userguide/create-vpc-sftp-connector-procedure.html.

https://docs.aws.amazon.com/neptune-analytics/latest/userguide/what-is-neptune-analytics.html is now available in the AWS Canada (Central) and Australia (Sydney) Regions. You can now create and manage Neptune Analytics graphs in the AWS Canada (Central) and Australia (Sydney) Regions and run advanced graph analytics and vector similarity search. Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements https://docs.aws.amazon.com/neptune/latest/userguide/intro.html, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that's stored in Amazon S3. To get started, you can create a new Neptune Analytics graphs using the https://ca-central-1.console.aws.amazon.com/neptune/home?region=ca-central-1#analytics-graphs:, https://docs.aws.amazon.com/cli/latest/reference/neptune-graph/. For more information on pricing and region availability, refer to the https://aws.amazon.com/neptune/pricing/ and https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/. 

Today, AWS Marketplace announces enhanced https://docs.aws.amazon.com/marketplace/latest/userguide/saas-subscriptions.html#:~:text=Each%20Pricing%20Dimension%20represents%20a%20feature%20or%20service%20that%20you%20can%20set%20a%20per%2Dunit%20price%20for.%20Examples%20of%20dimensions%20include%20users%2C%20hosts%20scanned%2C%20and%20GB%20of%20logs%20ingested capabilities, increasing limits and improving flexibility for sellers managing their product pricing. These enhancements increase the maximum pricing dimensions from 24 to 200, enable immediate use of new SaaS dimensions, and remove the 90-day price update restriction for dimensions without active subscriptions. These enhancements address key product pricing needs for sellers offering complex enterprise software. With 200 dimensions each for contract and usage-based pricing, sellers can now fully represent pricing across multiple features, user types, and consumption metrics in a single listing; matching the same pricing structures they offer outside of AWS Marketplace. When sellers add new usage dimensions to their public offers, these become available immediately for use. For instance, when a seller launches a new feature, subscribers can now instantly access it. Similarly, for dimensions without active subscriptions, sellers can adjust prices to align with their external pricing strategies without waiting through multiple 90-day periods. These enhancements to pricing dimensions are now available in all https://docs.aws.amazon.com/marketplace/latest/buyerguide/supported-regions.html where AWS Marketplace is supported. To learn more, visit the https://docs.aws.amazon.com/marketplace/latest/userguide/saas-subscriptions.html#, or access the https://aws.amazon.com/marketplace/management/offers/ to try the new capabilities.

https://docs.aws.amazon.com/neptune-analytics/latest/userguide/what-is-neptune-analytics.html is now available in the Asia Pacific (Mumbai) Region. You can now create and manage Neptune Analytics graphs in the Asia Pacific (Mumbai) Region and run advanced graph analytics. Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that's stored in Amazon S3. To get started, you can create a new Neptune Analytics graphs using the https://ap-south-1.console.aws.amazon.com/neptune/home?region=ap-south-1#analytics-graphs:, or AWS CLI. For more information on pricing and region availability, refer to the https://aws.amazon.com/neptune/pricing/.

Derivative is a software company that offers TouchDesigner, a visual development platform.

https://aws.amazon.com/rds/postgresql/ 18.0 is now available in thehttps://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/create-db-instance-in-preview-environment.html allowing you to evaluate the latest PostgreSQL features while leveraging the benefits of a fully managed database service. This preview environment provides you a sandbox where you can test applications and explore new PostgreSQL 18.0 capabilities before they become generally available. PostgreSQL 18.0 includes "skip scan" support for multicolumn B-tree indexes and improves WHERE clause handling for OR and IN conditions. It introduces parallel Generalized Inverted Index (GIN) builds and updates join operations. It now supports Universally Unique Identifiers Version 7 (UUIDv7), which combines timestamp-based ordering with traditional UUID uniqueness to boost performance in high-throughput distributed systems. Observability improvements show buffer usage counts and index lookups during query execution, along with per-connection I/O utilization metric. Please refer to the https://docs.aws.amazon.com/AmazonRDS/latest/PostgreSQLReleaseNotes/postgresql-versions.html#postgresql-version18 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 https://aws.amazon.com/rds/postgresql/pricing/ in the US East (Ohio) Region.

https://aws.amazon.com/rds/postgresql/ 18 Release Candidate 1 (RC1) is now available in thehttps://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/create-db-instance-in-preview-environment.html allowing you to evaluate the pre-release of PostgreSQL 18 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 18 RC1 in the https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/create-db-instance-in-preview-environment.htmlthat has the benefits of a fully managed database. PostgreSQL 18 includes "skip scan" support for multicolumn B-tree indexes and improves WHERE clause handling for OR and IN conditions. It introduces parallel GIN (Generalized Inverted) Index builds and updates join operations. Observability improvements show buffer usage counts and index lookups during query execution, along with per-connection I/O utilization metric. Please refer the https://docs.aws.amazon.com/AmazonRDS/latest/PostgreSQLReleaseNotes/postgresql-versions.html#postgresql-version18 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 https://aws.amazon.com/rds/postgresql/pricing/ in the US East (Ohio) Region.

AWS today launched three new condition keys that help administrators govern https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys.html. The new condition keys help you control the generation, expiration, and the type of API keys allowed. Amazon Bedrock supports two types of API keys: short-term API keys valid for up to 12 hours or long-term API keys which are https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_service-specific-creds.html for use with Bedrock only. The new iam:ServiceSpecificCredentialServiceName condition key lets you control what target AWS services are allowed when creating IAM service-specific credentials. For example, you could allow the creation of Bedrock long-term API keys but not credentials for AWS CodeCommit or Amazon Keyspaces. The new iam:ServiceSpecificCredentialAgeDays condition key lets you control the maximum duration of Bedrock long-term API keys at creation. The new bedrock:BearerTokenType condition key let’s you allow or deny Bedrock requests based on whether the API key is short-term or long-term. These new condition keys are available in all AWS Regions. To learn more about using the new condition keys, visit the https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_iam-condition-keys.html#available-keys-for-iam or https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys-permissions.html.

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