Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g and R8g instances are available in AWS Asia Pacific (Hong Kong) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. 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. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors.

To learn more, see Amazon EC2 M8g Instances and 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.

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g and R8g instances are available in AWS Asia Pacific (Hong Kong) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. 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. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. To learn more, see Amazon EC2 M8g Instances and 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.  

AWS Glue now offers a new native connector for Microsoft Dynamics 365, enabling data engineers to easily integrate data from this enterprise resource planning (ERP) and customer relationship management (CRM) platform. This connector allows AWS Glue users to build efficient extract, transform, and load (ETL) jobs that seamlessly connect to Microsoft Dynamics 365 as a data source.

With this new connector, users can streamline their data integration processes, reducing the complexity and time required to incorporate Microsoft Dynamics 365 data into their AWS-based analytics and business intelligence workflows. Organizations can now leverage the power of AWS Glue’s fully-managed ETL service in conjunction with their Microsoft Dynamics 365 data, enabling more comprehensive insights and data-driven decision-making.

The AWS Glue connector for Microsoft Dynamics 365 is available in all regions where AWS Glue is supported.

To learn more about this new connector and how to get started, visit the AWS Glue documentation.

​AWS Glue now offers a new native connector for Microsoft Dynamics 365, enabling data engineers to easily integrate data from this enterprise resource planning (ERP) and customer relationship management (CRM) platform. This connector allows AWS Glue users to build efficient extract, transform, and load (ETL) jobs that seamlessly connect to Microsoft Dynamics 365 as a data source. With this new connector, users can streamline their data integration processes, reducing the complexity and time required to incorporate Microsoft Dynamics 365 data into their AWS-based analytics and business intelligence workflows. Organizations can now leverage the power of AWS Glue’s fully-managed ETL service in conjunction with their Microsoft Dynamics 365 data, enabling more comprehensive insights and data-driven decision-making. The AWS Glue connector for Microsoft Dynamics 365 is available in all regions where AWS Glue is supported. To learn more about this new connector and how to get started, visit the AWS Glue documentation.  

AWS is expanding service reference information to include information about which service actions are supported by the IAM Last Accessed and IAM Access Analyzer Policy Generation features. IAM Last Accessed and Policy Generator features help you journey towards least privilege permissions, and now you can easily reference which service actions are supported by these features in machine-readable files.

You can automate the retrieval of service reference information, eliminating manual effort and ensuring your policies align with the latest service updates. You can also incorporate this service reference directly into your policy management tools and processes for a seamless integration. This feature is offered at no additional cost. To get started, refer to the documentation on programmatic service reference information.

​AWS is expanding service reference information to include information about which service actions are supported by the IAM Last Accessed and IAM Access Analyzer Policy Generation features. IAM Last Accessed and Policy Generator features help you journey towards least privilege permissions, and now you can easily reference which service actions are supported by these features in machine-readable files. You can automate the retrieval of service reference information, eliminating manual effort and ensuring your policies align with the latest service updates. You can also incorporate this service reference directly into your policy management tools and processes for a seamless integration. This feature is offered at no additional cost. To get started, refer to the documentation on programmatic service reference information.  

Amazon ElastiCache now supports Bloom filters as a new data type in ElastiCache version 8.1 for Valkey and above. Bloom filters are a space efficient probabilistic data structure that lets you quickly check whether an item is possibly in a set. This new feature is fully compatible with the valkey-bloom module and API compatible with the Bloom filter command syntax of the Valkey client libraries, such as valkey-py, valkey-java, and valkey-go. Previously, to find whether elements were added to your cache, you used the Set data type to write items to a set and then check if that item already existed. Bloom filters achieve the same outcome using a probabilistic approach and are over 98% more memory efficient than using sets without compromising performance.

Bloom filters are available today in Amazon ElastiCache version 8.1 for Valkey in all AWS Regions and for serverless and node-based offerings at no additional cost. To learn more about Bloom filters on ElastiCache for Valkey, check out the ElastiCache documentation. For the full documentation and list of supported commands, see the Bloom filter documentation. 

​Amazon ElastiCache now supports Bloom filters as a new data type in ElastiCache version 8.1 for Valkey and above. Bloom filters are a space efficient probabilistic data structure that lets you quickly check whether an item is possibly in a set. This new feature is fully compatible with the valkey-bloom module and API compatible with the Bloom filter command syntax of the Valkey client libraries, such as valkey-py, valkey-java, and valkey-go. Previously, to find whether elements were added to your cache, you used the Set data type to write items to a set and then check if that item already existed. Bloom filters achieve the same outcome using a probabilistic approach and are over 98% more memory efficient than using sets without compromising performance. Bloom filters are available today in Amazon ElastiCache version 8.1 for Valkey in all AWS Regions and for serverless and node-based offerings at no additional cost. To learn more about Bloom filters on ElastiCache for Valkey, check out the ElastiCache documentation. For the full documentation and list of supported commands, see the Bloom filter documentation.   

Amazon Aurora PostgreSQL Limitless Database is now available in the US West (N. California), Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Thailand), Canada (Central), Canada West (Calgary), Europe (London, Milan, Paris, Spain, Zurich), Israel (Tel Aviv), Mexico (Central), Middle East (Bahrain, UAE), and South America (Sao Paulo) Regions.

Aurora PostgreSQL Limitless Database makes it easy for you to scale your relational database workloads by providing a serverless endpoint that automatically distributes data and queries across multiple Amazon Aurora Serverless instances while maintaining the transactional consistency of a single database. Aurora PostgreSQL Limitless Database offers capabilities such as distributed query planning and transaction management, removing the need for you to create custom solutions or manage multiple databases to scale. As your workloads increase, Aurora PostgreSQL Limitless Database adds additional compute resources while staying within your specified budget, so there is no need to provision for peak, and compute automatically scales down when demand is low.

Aurora PostgreSQL Limitless Database is available with PostgreSQL 16.6 and 16.8 compatibility in these regions.

For pricing details and Region availability, visit Amazon Aurora pricing. To learn more, read the Aurora PostgreSQL Limitless Database documentation and get started by creating an Aurora PostgreSQL Limitless Database in only a few steps in the Amazon RDS console.

​Amazon Aurora PostgreSQL Limitless Database is now available in the US West (N. California), Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Thailand), Canada (Central), Canada West (Calgary), Europe (London, Milan, Paris, Spain, Zurich), Israel (Tel Aviv), Mexico (Central), Middle East (Bahrain, UAE), and South America (Sao Paulo) Regions.
Aurora PostgreSQL Limitless Database makes it easy for you to scale your relational database workloads by providing a serverless endpoint that automatically distributes data and queries across multiple Amazon Aurora Serverless instances while maintaining the transactional consistency of a single database. Aurora PostgreSQL Limitless Database offers capabilities such as distributed query planning and transaction management, removing the need for you to create custom solutions or manage multiple databases to scale. As your workloads increase, Aurora PostgreSQL Limitless Database adds additional compute resources while staying within your specified budget, so there is no need to provision for peak, and compute automatically scales down when demand is low.
Aurora PostgreSQL Limitless Database is available with PostgreSQL 16.6 and 16.8 compatibility in these regions.
For pricing details and Region availability, visit Amazon Aurora pricing. To learn more, read the Aurora PostgreSQL Limitless Database documentation and get started by creating an Aurora PostgreSQL Limitless Database in only a few steps in the Amazon RDS console.  

The post Estrella en ascenso: Conozcan a Dylan, el investigador de seguridad más joven de MSRC appeared first on Source LATAM.

​The post Estrella en ascenso: Conozcan a Dylan, el investigador de seguridad más joven de MSRC appeared first on Source LATAM.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8g instances are available in US East (Ohio) region. These instances are powered by AWS Graviton4 processors and deliver up to 60% better performance than AWS Graviton2-based Amazon EC2 X2gd instances. X8g instances offer up to 3 TiB of total memory and increased memory per vCPU compared to other Graviton4-based instance. They have the best price performance among EC2 X-series instances, and are ideal for memory-intensive workloads such as electronic design automation (EDA) workloads, in-memory databases (Redis, Memcached), relational databases (MySQL, PostgreSQL), real-time big data analytics, real-time caching servers, and memory-intensive containerized applications.

X8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 3TiB) than Graviton2-based X2gd instances. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Elastic Fabric Adapter (EFA) networking support is offered on 24xlarge, 48xlarge, and bare metal sizes, and Elastic Network Adapter (ENA) Express support is available on instance sizes larger than 12xlarge.

X8g instances are currently available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt).

To learn more, see Amazon EC2 X8g Instances. To quickly migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program. To get started, see the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs. 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8g instances are available in US East (Ohio) region. These instances are powered by AWS Graviton4 processors and deliver up to 60% better performance than AWS Graviton2-based Amazon EC2 X2gd instances. X8g instances offer up to 3 TiB of total memory and increased memory per vCPU compared to other Graviton4-based instance. They have the best price performance among EC2 X-series instances, and are ideal for memory-intensive workloads such as electronic design automation (EDA) workloads, in-memory databases (Redis, Memcached), relational databases (MySQL, PostgreSQL), real-time big data analytics, real-time caching servers, and memory-intensive containerized applications. X8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 3TiB) than Graviton2-based X2gd instances. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Elastic Fabric Adapter (EFA) networking support is offered on 24xlarge, 48xlarge, and bare metal sizes, and Elastic Network Adapter (ENA) Express support is available on instance sizes larger than 12xlarge. X8g instances are currently available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt). To learn more, see Amazon EC2 X8g Instances. To quickly migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program. To get started, see the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.   

Amazon CloudWatch adds support for Internet Protocol version 6 (IPv6) addresses to ingest and query metrics, as well as manage alarms, dashboards, and Observability Access Manager (OAM) cross-account observability settings. Customers moving to IPv6 can simplify their network stack by running their CloudWatch monitoring on a dual-stack network that supports both IPv4 and IPv6.

The addition of IPv6 support provides customers with a vastly expanded address space, eliminating concerns about address exhaustion and simplifying network architecture for IPv6-native applications. With simultaneous support for both IPv4 and IPv6 clients on CloudWatch public endpoints, customers can gradually transition from IPv4 to IPv6-based systems and applications without needing to switch all systems at once. This enhancement is particularly valuable for modern cloud-native applications and organizations transitioning to IPv6 as part of their modernization efforts.

Support for IPv6 on CloudWatch endpoints is now available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions.

To start using CloudWatch IPv6 on endpoints related to metrics, alarms, dashboards, or OAM settings, you simply need to update your network configuration and the URL of the CloudWatch endpoints or CloudWatch OAM endpoints you connect to. Please refer to AWS service endpoints documentation for the updated URL endpoint syntax. For use within a VPC, please refer to how to add IPv6 support for your VPC.

​Amazon CloudWatch adds support for Internet Protocol version 6 (IPv6) addresses to ingest and query metrics, as well as manage alarms, dashboards, and Observability Access Manager (OAM) cross-account observability settings. Customers moving to IPv6 can simplify their network stack by running their CloudWatch monitoring on a dual-stack network that supports both IPv4 and IPv6. The addition of IPv6 support provides customers with a vastly expanded address space, eliminating concerns about address exhaustion and simplifying network architecture for IPv6-native applications. With simultaneous support for both IPv4 and IPv6 clients on CloudWatch public endpoints, customers can gradually transition from IPv4 to IPv6-based systems and applications without needing to switch all systems at once. This enhancement is particularly valuable for modern cloud-native applications and organizations transitioning to IPv6 as part of their modernization efforts. Support for IPv6 on CloudWatch endpoints is now available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions. To start using CloudWatch IPv6 on endpoints related to metrics, alarms, dashboards, or OAM settings, you simply need to update your network configuration and the URL of the CloudWatch endpoints or CloudWatch OAM endpoints you connect to. Please refer to AWS service endpoints documentation for the updated URL endpoint syntax. For use within a VPC, please refer to how to add IPv6 support for your VPC.  

Starting today, Amazon EC2 gives customers the option to skip the graceful operating system (OS) shutdown during an instance stop or terminate. Previously, customers waited by default for a graceful OS shutdown attempt when stopping or terminating their instances. Customers can now skip the graceful operating system shutdown attempt during stop or terminate for a faster application recovery when instance data preservation is not critical. For example, customers with high-availability clusters where instance data is replicated elsewhere can skip the graceful OS shutdown during failover, enabling faster instance state transitions. Customers can enable the option to skip the graceful OS shutdown when stopping or terminating instances using the AWS CLI or EC2 Console. To learn more, please refer to our documentation here for StopInstances and here for TerminateInstances.

​Starting today, Amazon EC2 gives customers the option to skip the graceful operating system (OS) shutdown during an instance stop or terminate. Previously, customers waited by default for a graceful OS shutdown attempt when stopping or terminating their instances. Customers can now skip the graceful operating system shutdown attempt during stop or terminate for a faster application recovery when instance data preservation is not critical. For example, customers with high-availability clusters where instance data is replicated elsewhere can skip the graceful OS shutdown during failover, enabling faster instance state transitions. Customers can enable the option to skip the graceful OS shutdown when stopping or terminating instances using the AWS CLI or EC2 Console. To learn more, please refer to our documentation here for StopInstances and here for TerminateInstances.  

Amazon RDS for Oracle zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) to analyze petabytes of transactional data in Amazon Redshift without complex data pipelines for extract-transform-load (ETL) operations. Within seconds of data being written to Amazon RDS for Oracle, the data is replicated to Amazon Redshift. With Zero-ETL integrations, analyzing data from Amazon RDS for Oracle is simple, helping you derive holistic insights across many applications.

With this launch, you can use the AWS management console, API, CLI, and AWS CloudFormation to create and manage zero-ETL integrations between RDS for Oracle and Amazon Redshift. You can choose specific pluggable databases (PDBs) to selectively replicate them. In addition, you can choose specific tables and tailor replication to your needs.

RDS for Oracle zero-ETL integration with Redshift is available with Oracle Database versions 19c in supported AWS Regions. To learn more, referAmazon RDS and Amazon Redshift documentation. 

​Amazon RDS for Oracle zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) to analyze petabytes of transactional data in Amazon Redshift without complex data pipelines for extract-transform-load (ETL) operations. Within seconds of data being written to Amazon RDS for Oracle, the data is replicated to Amazon Redshift. With Zero-ETL integrations, analyzing data from Amazon RDS for Oracle is simple, helping you derive holistic insights across many applications. With this launch, you can use the AWS management console, API, CLI, and AWS CloudFormation to create and manage zero-ETL integrations between RDS for Oracle and Amazon Redshift. You can choose specific pluggable databases (PDBs) to selectively replicate them. In addition, you can choose specific tables and tailor replication to your needs. RDS for Oracle zero-ETL integration with Redshift is available with Oracle Database versions 19c in supported AWS Regions. To learn more, referAmazon RDS and Amazon Redshift documentation.