Amazon Aurora PostgreSQL-Compatible Edition now supports pgvector 0.8.0, an open-source extension for PostgreSQL for storing vector embeddings in your database. pgvector provides vector similarity search capabilities that enables Aurora use in generative artificial intelligence (AI) semantic search and retrieval-augemented generation (RAG) applications. pgvector 0.8.0 includes improvements to PostgreSQL query planner’s selection of index when filters are present, which can deliver better query performance and improve search result quality.

pgvector 0.8.0 improves data filtering using conditions in WHERE clauses and joins that can improve query performance and usability. Additionally, the iterative index scans help prevent ‘overfiltering’, ensuring generation of sufficient results to satisfy the conditions of a query. If an initial index scan doesn’t satisfy the query conditions, pgvector will continue to search the index until it hits a configurable threshold. pgvector 0.8.0 also has performance improvements for searching and building HNSW indexes.

pgvector 0.8.0 is available in Amazon Aurora clusters running PostgreSQL 16.8, 15.12, 14.17, and 13.20 and higher in all AWS Regions including AWS GovCloud (US) Regions, except China. You can initiate a minor version upgrade by modifying your DB cluster. Please review the Aurora documentation to learn more.

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.

 

​Amazon Aurora PostgreSQL-Compatible Edition now supports pgvector 0.8.0, an open-source extension for PostgreSQL for storing vector embeddings in your database. pgvector provides vector similarity search capabilities that enables Aurora use in generative artificial intelligence (AI) semantic search and retrieval-augemented generation (RAG) applications. pgvector 0.8.0 includes improvements to PostgreSQL query planner’s selection of index when filters are present, which can deliver better query performance and improve search result quality. pgvector 0.8.0 improves data filtering using conditions in WHERE clauses and joins that can improve query performance and usability. Additionally, the iterative index scans help prevent ‘overfiltering’, ensuring generation of sufficient results to satisfy the conditions of a query. If an initial index scan doesn’t satisfy the query conditions, pgvector will continue to search the index until it hits a configurable threshold. pgvector 0.8.0 also has performance improvements for searching and building HNSW indexes. pgvector 0.8.0 is available in Amazon Aurora clusters running PostgreSQL 16.8, 15.12, 14.17, and 13.20 and higher in all AWS Regions including AWS GovCloud (US) Regions, except China. You can initiate a minor version upgrade by modifying your DB cluster. Please review the Aurora documentation to learn more. 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.  

Today, AWS announces a new fulfillment experience for container products in AWS Marketplace, enhancing the deployment and management of container-based software from AWS Partners.

The new fulfillment experience helps to reduce complexity and improve workflow efficiency by making it easier to understand available deployment options, and providing explanations of each option’s purpose and implications. The fulfillment experience also offers readily accessible help resources, including detailed guides from AWS Marketplace sellers. The experience is available across all AWS Regions and in local languages, delivering a consistent experience worldwide.

To learn more about the new fulfillment experience for container products in AWS Marketplace and how it can benefit your organization, visit the AWS Marketplace Buyer Guide or start exploring container products in AWS Marketplace today.
 

 

​Today, AWS announces a new fulfillment experience for container products in AWS Marketplace, enhancing the deployment and management of container-based software from AWS Partners. The new fulfillment experience helps to reduce complexity and improve workflow efficiency by making it easier to understand available deployment options, and providing explanations of each option’s purpose and implications. The fulfillment experience also offers readily accessible help resources, including detailed guides from AWS Marketplace sellers. The experience is available across all AWS Regions and in local languages, delivering a consistent experience worldwide. To learn more about the new fulfillment experience for container products in AWS Marketplace and how it can benefit your organization, visit the AWS Marketplace Buyer Guide or start exploring container products in AWS Marketplace today.    

The latest Well-Architected Framework update is now available in the Well-Architected Tool, featuring updates and improvements for 78 new best practices that offer actionable guidance to help organizations build more secure, resilient, scalable, and sustainable workloads.

With this release, the Well-Architected Framework has refreshed 100% of each pillar, including the Reliability Pillar, with 14 of its best practices updated for the first time since major Framework improvements started in 2022.

With the refreshed AWS Well-Architected Framework, organizations can use our actionable guidance to help achieve more operable, secure, sustainable, scalable, and resilient environment and workload solutions.

The updated AWS Well-Architected Framework is available now for all AWS customers. To learn more about the AWS Well-Architected Framework, visit the AWS Well-Architected Framework documentation.

 

​The latest Well-Architected Framework update is now available in the Well-Architected Tool, featuring updates and improvements for 78 new best practices that offer actionable guidance to help organizations build more secure, resilient, scalable, and sustainable workloads. With this release, the Well-Architected Framework has refreshed 100% of each pillar, including the Reliability Pillar, with 14 of its best practices updated for the first time since major Framework improvements started in 2022. With the refreshed AWS Well-Architected Framework, organizations can use our actionable guidance to help achieve more operable, secure, sustainable, scalable, and resilient environment and workload solutions. The updated AWS Well-Architected Framework is available now for all AWS customers. To learn more about the AWS Well-Architected Framework, visit the AWS Well-Architected Framework documentation.  

Amazon OpenSearch Service expands its modernized operational analytics experience to the AWS Europe (Stockholm) and Asia Pacific (Hong Kong) Regions, 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 SQL and Piped-Processing-Language (PPL), 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 serverless collections. It is now available in 15 AWS commercial regions. To get started, create an OpenSearch application in AWS Management Console. Learn more at Amazon OpenSearch Service Developer Guide.

 

​Amazon OpenSearch Service expands its modernized operational analytics experience to the AWS Europe (Stockholm) and Asia Pacific (Hong Kong) Regions, 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 SQL and Piped-Processing-Language (PPL), 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 serverless collections. It is now available in 15 AWS commercial regions. To get started, create an OpenSearch application in AWS Management Console. Learn more at Amazon OpenSearch Service Developer Guide.  

Today, Amazon Q Developer announced expanded multi-language support for the integrated development environment (IDE) and the Q Developer CLI. Among the many supported languages are Mandarin, French, German, Italian, Japanese, Spanish, Korean, Hindi and Portuguese, with more languages available.

To get started, simply start a conversation with Q Developer using your preferred language. Q Developer will then automatically detect it and provide answers, code suggestions, and responses in the appropriate language, making development more accessible and efficient for global teams.

This update is available in all AWS Regions where Amazon Q Developer is available. To get started visit Amazon Q Developer or read the blog.
 

 

​Today, Amazon Q Developer announced expanded multi-language support for the integrated development environment (IDE) and the Q Developer CLI. Among the many supported languages are Mandarin, French, German, Italian, Japanese, Spanish, Korean, Hindi and Portuguese, with more languages available. To get started, simply start a conversation with Q Developer using your preferred language. Q Developer will then automatically detect it and provide answers, code suggestions, and responses in the appropriate language, making development more accessible and efficient for global teams. This update is available in all AWS Regions where Amazon Q Developer is available. To get started visit Amazon Q Developer or read the blog.    

Starting today, PartyRock is supporting an image playground that uses the Amazon Nova Canvas foundation model to transform your ideas into customizable images. You can access the image playground directly through the «Images» section, featuring an intuitive interface and comprehensive customization options.

This new capability enhances PartyRock’s existing image generation features. While you could previously generate images using widgets in your apps, you can now also create images through the dedicated image playground. The playground offers configuration options including orientation choices (landscape, portrait, square), resolution sizes, and color guidance. The image playground comes with pre-filled prompts to help you get started, and provides suggested prompts after each generation to help refine and customize your images further.

We welcome your feedback and contributions to help shape our roadmap as we continue to enhance PartyRock’s capabilities for improving everyday productivity. You can experiment with PartyRock using a free daily use grant, without worrying about exhausting free trial credits. To begin creating with the image playground, try PartyRock today.
 

 

​Starting today, PartyRock is supporting an image playground that uses the Amazon Nova Canvas foundation model to transform your ideas into customizable images. You can access the image playground directly through the «Images» section, featuring an intuitive interface and comprehensive customization options. This new capability enhances PartyRock’s existing image generation features. While you could previously generate images using widgets in your apps, you can now also create images through the dedicated image playground. The playground offers configuration options including orientation choices (landscape, portrait, square), resolution sizes, and color guidance. The image playground comes with pre-filled prompts to help you get started, and provides suggested prompts after each generation to help refine and customize your images further. We welcome your feedback and contributions to help shape our roadmap as we continue to enhance PartyRock’s capabilities for improving everyday productivity. You can experiment with PartyRock using a free daily use grant, without worrying about exhausting free trial credits. To begin creating with the image playground, try PartyRock today.    

AWS announces the availability of Pixtral Large 25.02 in Amazon Bedrock, a 124B parameter model with multimodal capabilities that combines state-of-the-art image understanding with powerful text processing. AWS is the first cloud provider to deliver Pixtral Large 25.02 as a fully managed, serverless model. This model delivers frontier-class performance across document analysis, chart interpretation, and natural image understanding tasks, while maintaining the advanced text capabilities of Mistral Large 2.

With a 128K context window, Pixtral Large 25.02 achieves best-in-class performance on key benchmarks including MathVista, DocVQA, and VQAv2. The model features comprehensive multilingual support across dozens of languages and is trained on over 80 programming languages. Key capabilities include advanced mathematical reasoning, native function calling, JSON outputting, and robust context adherence for Retrieval Augmented Generation (RAG) applications.

Pixtral Large 25.02 is now available in Amazon Bedrock in seven AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Dublin), Europe (Paris), and Europe (Stockholm). For more information on supported Regions, visit the Amazon Bedrock Model Support by Regions guide. 

To learn more about Pixtral Large 25.02 and its capabilities, visit the Mistral AI product page. To get started with Pixtral Large 25.02 in Amazon Bedrock, visit the Amazon Bedrock console.

 

​AWS announces the availability of Pixtral Large 25.02 in Amazon Bedrock, a 124B parameter model with multimodal capabilities that combines state-of-the-art image understanding with powerful text processing. AWS is the first cloud provider to deliver Pixtral Large 25.02 as a fully managed, serverless model. This model delivers frontier-class performance across document analysis, chart interpretation, and natural image understanding tasks, while maintaining the advanced text capabilities of Mistral Large 2.
With a 128K context window, Pixtral Large 25.02 achieves best-in-class performance on key benchmarks including MathVista, DocVQA, and VQAv2. The model features comprehensive multilingual support across dozens of languages and is trained on over 80 programming languages. Key capabilities include advanced mathematical reasoning, native function calling, JSON outputting, and robust context adherence for Retrieval Augmented Generation (RAG) applications.
Pixtral Large 25.02 is now available in Amazon Bedrock in seven AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Dublin), Europe (Paris), and Europe (Stockholm). For more information on supported Regions, visit the Amazon Bedrock Model Support by Regions guide. 
To learn more about Pixtral Large 25.02 and its capabilities, visit the Mistral AI product page. To get started with Pixtral Large 25.02 in Amazon Bedrock, visit the Amazon Bedrock console.  

Amazon S3 Tables are now available in four additional AWS Regions: Asia Pacific (Osaka), Europe (Paris), Europe (Spain), and US West (N. California). S3 Tables deliver the first cloud object store with built-in Apache Iceberg support, and the easiest way to store tabular data at scale.

With this expansion, S3 Tables are now generally available in nineteen AWS Regions. To learn more, visit the product page, documentation, and the S3 pricing page.
 

 

​Amazon S3 Tables are now available in four additional AWS Regions: Asia Pacific (Osaka), Europe (Paris), Europe (Spain), and US West (N. California). S3 Tables deliver the first cloud object store with built-in Apache Iceberg support, and the easiest way to store tabular data at scale. With this expansion, S3 Tables are now generally available in nineteen AWS Regions. To learn more, visit the product page, documentation, and the S3 pricing page.    

Starting today, customers can use Amazon OpenSearch Ingestion in Europe(Spain) region for ingesting data into their Amazon OpenSearch Service managed clusters or serverless collections.

Amazon OpenSearch Ingestion is a fully managed data ingestion tier that allows you to ingest and process data before indexing it in Amazon OpenSearch managed clusters or serverless collections. Amazon OpenSearch Ingestion provides a no-code experience to filter, transform, redact, and route data into Amazon OpenSearch Service. Amazon OpenSearch Ingestion automatically provisions and scales the underlying resources to meet the fluctuating demands of your workloads.

With this launch, Amazon OpenSearch Ingestion is now generally available in 16 AWS regions: US East (Ohio), US East (N. Virginia), US West (Oregon), US West (N. California), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe(Spain), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Asia Pacific (Seoul), Canada (Central), South America (Sao Paulo), and Europe (Stockholm).

To learn more, see the Amazon OpenSearch Ingestion webpage and the Amazon OpenSearch Ingestion Developer Guide.

 

​Starting today, customers can use Amazon OpenSearch Ingestion in Europe(Spain) region for ingesting data into their Amazon OpenSearch Service managed clusters or serverless collections.
Amazon OpenSearch Ingestion is a fully managed data ingestion tier that allows you to ingest and process data before indexing it in Amazon OpenSearch managed clusters or serverless collections. Amazon OpenSearch Ingestion provides a no-code experience to filter, transform, redact, and route data into Amazon OpenSearch Service. Amazon OpenSearch Ingestion automatically provisions and scales the underlying resources to meet the fluctuating demands of your workloads. With this launch, Amazon OpenSearch Ingestion is now generally available in 16 AWS regions: US East (Ohio), US East (N. Virginia), US West (Oregon), US West (N. California), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe(Spain), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Asia Pacific (Seoul), Canada (Central), South America (Sao Paulo), and Europe (Stockholm). To learn more, see the Amazon OpenSearch Ingestion webpage and the Amazon OpenSearch Ingestion Developer Guide.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Asia Pacific (Mumbai) and AWS Asia Pacific (Hyderabad) regions. 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. 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 Amazon M7g 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. M8g 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 M8g 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 instances are available in AWS Asia Pacific (Mumbai) and AWS Asia Pacific (Hyderabad) regions. 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. 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 Amazon M7g 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. M8g 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 M8g 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.