aws·Jun 5, 2026·2 min readCurated summary

Try the new console experience in Amazon Bedrock, optimized for Anthropic- and OpenAI-compatible APIs | Amazon Web Services

Amazon Bedrock introduces a refreshed console centered on the `bedrock-mantle` inference engine, which supports Anthropic Messages, OpenAI Responses, and OpenAI Chat Completions APIs. The experience is designed to streamline model discovery, evaluation, application development, and production setup for GPT, Claude, and open-weight models. It complements the existing console, which remains available for features such as Agents, Knowledge Bases, Guardrails, fine-tuning, and `bedrock-runtime` APIs. ## Model Catalog and Comparison - Browse supported models in a unified catalog. - Compare up to three models by: - Capabilities and modalities - Context window and token limits - Pricing and input/output costs - Service quotas - Regional availability - Use side-by-side evaluations with identical prompts to compare model responses. ## Project-Based Workflow - Create projects that organize model assignments, evaluations, API keys, and application setup. - The project dashboard displays: - Inference requests and errors over selected date ranges - Recently used models - Total token usage - Tokens per minute - Requests per minute - Tokens per inference request - These metrics can guide model selection, prompt optimization, and workload consistency. ## Application Setup and Live Documentation - The console provides project-specific setup instructions for Anthropic and OpenAI SDKs. - Developers can select an SDK, programming language, and authentication method. - It generates terminal commands, `.env` configuration, and sample requests for quick testing. - Live API documentation automatically inserts the project’s model ID, Region, `bedrock-mantle` endpoint, and API key reference. - Documentation updates automatically when project models or settings change. ## AI Coding Agent Integration - Projects can connect coding agents such as Claude Code, Cline, Codex, Cursor, and OpenCode. - Setup instructions cover: - Installing the selected agent - Using AWS IAM credentials or Bedrock API keys - Configuring environment variables - Routing agent requests through Bedrock ## Availability The new console is available in Regions offering `bedrock-mantle`, including locations in the United States, Asia Pacific, Europe, and South America. Users can access it through the existing Bedrock console by selecting **Try the Bedrock Mantle Console**, while the traditional console remains available for fully managed Bedrock capabilities. Developers building with Anthropic- or OpenAI-compatible APIs can use the new console to move from model evaluation to application testing and deployment with less manual configuration.

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AI AgentsGenerative AIAmazon BedrockAws Sdk+3

aws·Jun 3, 2026·3 min readCurated summary

Improve your application resilience with Amazon Cognito multi-Region replication | Amazon Web Services

Amazon Cognito multi-Region replication improves authentication resilience by maintaining synchronized user data, credentials, configurations, and machine secrets in a secondary AWS Region. During a regional outage, applications can redirect traffic while users continue using existing credentials and sessions, though registration and profile updates are unavailable during failover. The feature also adds customer managed AWS KMS keys for consistent, customer-controlled encryption across Regions. ## Challenges with Regional Failover - Custom replication solutions previously required significant engineering effort. - Manual user-data transfers introduced security and consistency risks. - Users could be forced to reset passwords or authenticate again after a regional switch. - Machine-to-machine systems required new app clients, application reconfiguration, and updated OAuth resource trust settings. ## How Multi-Region Replication Works - Replication is one-way, from a primary Region to a secondary Region. - The replica includes: - User profiles and credentials - User pool configuration - Machine-to-machine secrets - The secondary pool is read-only and remains available for authentication. - Existing sessions continue uninterrupted. - Users can authenticate with existing credentials, and either Region recognizes access tokens issued by the other. - Supported authentication methods include: - Social identity providers - SAML and OIDC federation - API authorization flows - Machine-to-machine authentication - New registrations and profile changes are unavailable while operating from the replica. ## Customer Managed KMS Keys - A multi-Region customer managed key is required before replication can be configured. - The key must be replicated into both the primary and secondary Regions. - Its policy must grant Amazon Cognito permission to use the key. - Customer managed keys provide consistent encryption across Regions and greater control over encryption policies. ## Configuration Process - The console guides administrators through three main steps: - Select and configure the customer managed KMS key. - Configure multi-Region OIDC issuer endpoints. - Select and create the replica Region. - Client applications must be updated with the new OIDC endpoints. - Server-side applications require redeployment, while mobile applications require updated store submissions. - After the replica is prepared, an administrator must manually activate it. ## Additional Regional Resources - Lambda functions used for custom authentication, SMS, or email must be deployed and configured in the secondary Region. - Logging and AWS WAF settings must also be recreated there. - Teams should verify that all supporting authentication infrastructure is available before failover. ## Health Checks and Failover - Both regional endpoints remain active and ready to serve traffic. - Applications should define health checks based on error rates, latency, or service alerts. - DNS can redirect traffic to the secondary Region when failover criteria are met. - Teams should test failover during low-traffic periods, potentially routing only a small percentage of traffic initially. - Managed login and federation with custom domains can use Amazon Route 53 health checks for built-in traffic routing. ## Pricing and Availability - Replication is available as an add-on for Cognito Essentials and Plus tiers. - User authentication costs: - $0.0045 per monthly active user per replica Region for Essentials - $0.006 per monthly active user per replica Region for Plus - M2M replication adds 30% to standard successful-token pricing. - The feature is available across selected Regions in North America, Europe, Asia Pacific, Canada, Africa, and South America. Organizations needing resilient authentication should pair Cognito replication with multi-Region KMS keys, replicated supporting services, tested health checks, and an automated or well-practiced DNS failover process.

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Aws LambdaOauthSamlOpenid Connect+4

aws·Jun 1, 2026·3 min readCurated summary

Get started with OpenAI GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock | Amazon Web Services

OpenAI GPT-5.5, GPT-5.4, and Codex are now generally available through Amazon Bedrock. GPT-5.5 targets the most demanding coding, reasoning, and agentic workloads, while GPT-5.4 emphasizes price-performance. Customers can access the models through the Responses API and use Codex across CLI, desktop, IDE, and Xcode integrations, with regional processing and token-based pricing. ## Model Access Through Amazon Bedrock - Models are served through Bedrock’s next-generation inference engine and the OpenAI Responses API. - GPT-5.5 is positioned for the hardest workloads; GPT-5.4 offers a balance of capability and cost. - Processing remains within the selected Bedrock Region, supporting data residency requirements. - Pricing is based on token usage, with no seat licenses or per-developer commitments. ## Calling GPT Models Programmatically - The OpenAI Python SDK can be configured with Bedrock’s OpenAI-compatible endpoint: - Install with `pip install -U openai`. - Set `OPENAI_BASE_URL`, `OPENAI_API_KEY`, and `BEDROCK_OPENAI_MODEL_ID`. - Applications can call `client.responses.create()` with: - Developer and user messages - Configurable reasoning effort - Output verbosity controls - The same endpoint can be called directly with `curl`. - The Responses API supports multi-turn state, hosted and function tools, tool orchestration, and background or long-running work. ## Using Codex with Bedrock - Codex is available through the Codex CLI, desktop app, VS Code, JetBrains, and Xcode integrations. - It supports: - A Bedrock API key via `AWS_BEARER_TOKEN_BEDROCK` - The AWS SDK credential chain as a fallback - Configure the model and Region in `~/.codex/config.toml`, for example: - Model: `openai.gpt-5.5` - Provider: `amazon-bedrock` - Region: `us-east-2` - Other supported model IDs include `openai.gpt-5.4`, `openai.gpt-oss-120b`, and `openai.gpt-oss-20b`. - Desktop and VS Code users can place environment variables in `~/.codex/.env`. - Applications must be restarted after configuration changes. ## Latency and Scaling Considerations - Actual latency depends on reasoning effort, response length, tool calls, background execution, Region, quotas, throttling, prompt size, and cache hits. - AWS recommends starting GPT-5.5 with medium reasoning effort. - GPT-5.4 should use an explicitly chosen effort level rather than relying on its default of `none`. - Bedrock’s inference engine is designed to provision capacity dynamically. - During demand spikes, requests may be queued instead of rejected. ## Regional Availability - GPT-5.5 is initially available in the US East (Ohio) Region. - GPT-5.4 is available in US East (Ohio) and US West (Oregon). - Additional Regions may be added over time. Teams needing advanced coding and reasoning capabilities can now use OpenAI models and Codex through Bedrock while retaining AWS authentication, regional processing, and usage-based pricing. Evaluate reasoning effort, latency, quotas, and regional availability before moving workloads into production.

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PythonAmazon BedrockAws SdkCurl+4

aws·Jun 1, 2026·4 min readCurated summary

AWS Weekly Roundup: Claude Opus 4.8 on AWS, Aurora MySQL with Kiro Powers, and more (June 1, 2026) | Amazon Web Services

AWS’s latest roundup highlights a rapid shift toward AI-augmented software development, illustrated by workshops where 17 teams delivered nearly 20 use cases in two days. The centerpiece is Anthropic Claude Opus 4.8, now available through Amazon Bedrock and the Claude Platform on AWS, alongside tools that improve resilience, agentic search, migration analysis, database management, and desktop streaming. Together, these launches show AWS moving toward real-time, AI-assisted development and operations. ## AI-Driven Development and Claude Opus 4.8 - AI-DLC workshops are helping teams deliver software use cases at unprecedented speed, especially when combined with Claude Code on Amazon Bedrock. - Development roles are increasingly consolidating into smaller, AI-augmented teams. - AWS account teams are shifting from producing advisory documents to building solutions collaboratively with customers. - Claude Opus 4.8 is Anthropic’s most capable generally available model and is designed for: - Agentic coding and extended autonomous tasks - Long-document analysis and knowledge work - Deeper reasoning and error recovery - Maintaining context across lengthy coding sessions - On Amazon Bedrock, it includes AWS features such as Guardrails, Knowledge Bases, and data-residency controls. - The Claude Platform on AWS provides Anthropic’s native APIs with unified AWS billing. ## AWS Resilience Hub - The next-generation Resilience Hub provides a unified way to define resilience standards, assess applications, and demonstrate compliance. - Modular policies cover: - Service-level objectives - Multi-Availability Zone and multi-Region disaster recovery - Data recovery - Generative AI assessments align with AWS Well-Architected and Resilience Analysis Framework guidance. - DNS query-log analysis automatically discovers application dependencies. - AWS Organizations integration enables centralized, organization-wide resilience management. ## OpenSearch Serverless for Agentic AI - Amazon OpenSearch Serverless is now positioned as a managed search and vector engine for agent-based applications. - It scales from zero to thousands of requests per second and is approximately 20 times faster than the previous generation. - AWS claims up to 60% cost savings compared with peak-provisioned clusters. - New capabilities include GPU acceleration and dedicated `SEARCH` and `VECTORSEARCH` collection types. - OpenSearch Agent Skills integrate with Vercel, Kiro, Claude Code, and Cursor. ## AWS Transform Assessment and Modernization Tools - AWS Transform can build migration business cases and estimate total cost of ownership. - It accepts data from RVTools, CMDBs, AWS discovery tools, and third-party discovery platforms. - Users can model what-if scenarios involving regions, utilization, and service mappings for services such as EC2, FSx, S3, SQL Server on EC2, and virtual desktops. - Agentic Readiness Analysis and Modernization Analysis scan repositories in roughly 5–30 minutes. - Findings include severity levels, file-level evidence, and AWS-specific remediation recommendations. ## Aurora MySQL with Kiro Powers - Aurora MySQL now integrates with Kiro Powers, which provide curated MCP servers, steering files, and hooks. - Developers can use natural language for both: - Data-plane tasks such as queries and schema changes - Control-plane tasks such as cluster administration - The integration offers guidance for Serverless scaling, RDS-to-Aurora migrations, and replication. - Kiro generates the relevant API calls, SQL, and configuration for developer review before execution. - Installation is available through the Kiro IDE or website. ## Windows Desktop Streaming with WorkSpaces Applications - Amazon WorkSpaces Applications now supports bring-your-own-license Windows Desktop OS deployments. - Customers can stream complete Windows desktops and applications from dedicated AWS hardware. - BYOL removes operating-system fees, leaving compute and streaming infrastructure charges. - Eligible Microsoft 365 Apps for enterprise are supported. - Users receive a consistent experience across local and streamed desktops. ## Additional AWS News - AWS introduced its May 2026 cohort of AWS Heroes. - A new Vercel and AWS Databases integration allows provisioning Aurora PostgreSQL, DynamoDB, and Aurora DSQL through Vercel or v0. - The H0 hackathon offers $160,000 in prizes for applications built with this stack. - AWS GovCloud customers now receive 24/7 support from US-based, US-citizen engineers automatically, without opting in. AWS’s direction is clear: combine capable AI agents with managed infrastructure, developer tools, and operational automation. Teams evaluating these services should focus on practical agentic use cases while retaining review and governance for generated code, infrastructure changes, and database operations.

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AI AgentsAWSAmazon BedrockClaude Opus+4

aws·May 28, 2026·3 min readCurated summary

Introducing the next generation of AWS Resilience Hub for generative AI-based SRE resilience journey | Amazon Web Services

AWS introduces the next generation of AWS Resilience Hub to help organizations manage application resilience consistently across large portfolios. The update adds a new business-oriented application model, modular resilience policies, dependency discovery, generative AI failure-mode analysis, and organization-wide reporting. Its goal is to help SREs and development teams define expectations, identify weaknesses, implement fixes, and demonstrate resilience through testing. ## Modular Resilience Policies - Policies are built from composable requirements rather than a single fixed policy type. - Requirements can include: - Availability service-level objectives (SLOs) - Multi-AZ and multi-Region disaster recovery - Recovery time objectives (RTOs) - Recovery point objectives (RPOs) - Backup data recovery requirements - Example policies can define 99.95% availability, a 15-minute RTO, and a 5-minute RPO for financial applications. ## Business-Oriented Application Modeling - A **system** represents a business application. - **User journeys** describe critical end-user paths and business outcomes. - **Services** represent deployable units such as microservices, AWS resources, code, and observability components. - Resilience Hub automatically maps resource relationships into a topology showing data flow, containment, and permissions. ## Dependency Discovery - Resilience Hub analyzes VPC DNS query logs to identify dependencies that may not be documented. - It can discover: - AWS services - Internal endpoints - Third-party endpoints - Unexpected cross-Region calls - Critical external dependencies - Dependency discovery can be enabled or disabled for individual services. ## Generative AI Failure-Mode Assessments - Assessments analyze services against: - Configured resilience policies - AWS Well-Architected best practices - The AWS Resilience Analysis Framework - Findings explain the failure mode, its architectural impact, recommended remediation, and related policy requirement. - Users can add or modify assertions to guide the AI agents and improve assessment accuracy. - Findings can be marked as resolved after remediation or irrelevant when they do not apply. ## Getting Started and Enterprise Management - Users must configure an invoker IAM role granting read-only access to AWS resources. - Cross-account roles or AWS Organizations service-linked roles can support multi-account environments. - AWS Organizations integration allows a delegated administrator to assess resilience across the enterprise without signing into individual accounts. - A typical workflow is: - Create a resilience policy. - Create a system and service. - Associate resources through tags, CloudFormation, Terraform, or Amazon EKS. - Enable dependency discovery. - Run a failure-mode assessment. - Review and implement recommendations. ## Migration, Availability, and Pricing - Migration APIs convert older Resilience Hub policies and applications into the new model, including mapping multiple related applications into one system with multiple services. - The new version is generally available in supported AWS commercial Regions. - Pricing uses a service-based model and includes two failure-mode assessments per service per month, with automated dependency assessment available optionally. - AWS offers a free trial. The updated Resilience Hub is most useful for organizations that need consistent resilience standards and evidence across many AWS accounts and applications. Teams should begin by defining reusable policies, modeling critical services and dependencies, and using the AI assessments to prioritize remediation.

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Generative AITerraformInfrastructure As CodeAmazon Eks+4

aws·May 28, 2026·2 min readCurated summary

Introducing the next generation of Amazon OpenSearch Serverless for building your agentic AI applications | Amazon Web Services

Amazon’s next-generation OpenSearch Serverless is a managed search and vector engine optimized for agentic AI applications. It scales from zero to thousands of requests per second, creates resources in seconds, and can reduce costs by up to 60% compared with clusters provisioned for peak demand. The release is generally available across supported AWS commercial Regions and integrates with tools such as Vercel, Kiro, Claude Code, and Cursor. ## Elastic Scaling and Cost Optimization - Scales capacity up to 20 times faster than the previous generation. - Supports scale-to-zero when idle, minimizing compute costs. - Charges separately for compute through OpenSearch Compute Units (OCUs), storage in GB-month, and GPU acceleration where applicable. - Supports capacity limits for indexing and search, with minimum capacity set to zero and configurable maximums. ## Creating Next-Generation Collections - Collections can be created through the Amazon OpenSearch Service console, AWS CLI, or SDKs. - The console’s **Express create** option automatically applies default settings and matching security policies. - At launch, supported collection types are: - Full-text search (`SEARCH`) - Vector search (`VECTORSEARCH`) - Users who need the existing infrastructure can select the classic OpenSearch Serverless generation. - Collections inherit their generation from a parent collection group. Example CLI workflows create a next-generation collection group with standby replicas and then create a search collection within it. ## Integrations for Agent Development - Vercel users can create or connect OpenSearch Serverless collections directly from the Vercel console. - OpenSearch Agent Skills bring search-specific knowledge, best practices, and multi-step workflows into agents using Claude Code, Cursor, and Kiro. - Kiro’s OpenSearch Launchpad provides guided architecture planning for building search applications. ## Availability - The next generation is generally available in all AWS commercial Regions where OpenSearch Serverless is currently offered. - AWS recommends consulting the OpenSearch Serverless documentation and pricing information for configuration and cost details. The release is intended to let developers deploy production-ready search and vector backends quickly, while avoiding the infrastructure management and peak-capacity costs associated with provisioned OpenSearch clusters.

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AI AgentsClaude CodeVector DbAws Cli+4

aws·May 27, 2026·2 min readCurated summary

Meet Our Newest AWS Heroes – May 2026 | Amazon Web Services

AWS has named four new Heroes for May 2026, recognizing leaders who advance cloud, AI, serverless, and community education. Their work ranges from building Amazon Bedrock-powered tools and contributing to AWS certifications to organizing major user groups and events across Europe and Latin America. Together, they demonstrate how technical expertise and community leadership can help more builders adopt AWS. ## Damiano Giorgi — Pavia, Italy - An Artificial Intelligence Hero and Cloud Solutions Architect specializing in AI. - Helps organize AWS User Groups in Pavia and Milan. - Created the “Unofficial post:Invent Session Suggester,” using Amazon Bedrock and Amazon Nova to recommend re:Invent sessions. - Shares knowledge through his “Bass and Bytes” blog and conferences across Europe. ## Darryl Ruggles — Ottawa, Canada - A Serverless Hero and Cloud Solutions Architect with a background in software development. - Focuses on AWS application architecture, AI/ML, serverless, containers, and FinOps. - Publishes blog posts, LinkedIn content, and open projects. - Participates actively in online communities such as “Believe In Serverless” and in-person AWS events. ## Ricardo Daniel Ceci — Buenos Aires, Argentina - An Artificial Intelligence Hero leading the AWS User Group Buenos Aires, with nearly 2,400 members. - Principal organizer of AWS Community Day Argentina. - Named AWS Community Leader of the Year 2025 for Latin America. - Hosts a podcast with cloud experts, AWS Heroes, and developer advocates. - Works to make cloud and AI more accessible to Spanish-speaking builders across LATAM. ## Matias Kreder — Buenos Aires, Argentina - An Artificial Intelligence Hero and AWS Certification Subject Matter Expert. - Contributed to AI/ML certifications, including the AWS Certified AI Practitioner exam. - Began his community involvement through AWS DeepRacer, qualifying as a finalist three times. - Organizes racing events, ML talks, and AWS community activities across Latin America. - Helped organize AWS Community Day Argentina 2025 and speaks at regional events. These new Heroes illustrate the value of combining AWS expertise with mentorship, content creation, certification work, and community organizing. Builders can learn more or connect with regional leaders through the AWS Heroes program.

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AIMachine LearningAWSAmazon Bedrock+4

aws·May 25, 2026·3 min readCurated summary

AWS Weekly Roundup: AWS Local Zones in Istanbul, open-source ExtendDB, Kiro Web, and more (May 25, 2026) | Amazon Web Services

AWS’s latest updates focus on expanding regional infrastructure, improving developer workflows, and making cloud and AI services more portable. The Istanbul Local Zone strengthens data residency and low-latency capabilities in Türkiye, while tools such as ExtendDB, OpenAI-compatible SageMaker APIs, and Kiro Web reduce migration and development friction. Together, these releases emphasize flexibility, operational resilience, and easier local testing. ## AWS Local Zone in Istanbul - AWS opened a new Local Zone in Istanbul, Türkiye. - It provides nearby compute, storage, and networking with single-digit millisecond latency. - Organizations can keep and process data within Turkish borders to support residency and compliance requirements. - The zone supports latency-sensitive workloads in sectors such as finance, government, telecommunications, and healthcare. - Applications can combine Istanbul infrastructure with the broader AWS Region, enabling hybrid architectures without operating a private data center. ## Security and AI Service Updates - **Security Hub Extended** now integrates with 21 curated partner solutions across nine security categories, including endpoint protection, threat intelligence, and cloud security posture management. - **Amazon SageMaker AI** supports OpenAI-compatible inference APIs, allowing existing OpenAI-based applications to use SageMaker with minimal or no SDK changes. - **Secrets Manager Agent** can pre-fetch secrets at startup, reducing cold-start delays, and can assume IAM roles for workloads with different permission boundaries. - **Amazon Bedrock** introduced tools for advanced prompt optimization and migration across foundation models. ## Open-Source and Local Development Tools - AWS open-sourced **ExtendDB**, a DynamoDB-compatible adapter for alternative storage backends. - It supports local development and testing without a live AWS connection. - It can help teams retain DynamoDB API semantics while controlling the underlying storage layer. - **AWS SAM CLI** now supports CloudFormation Language Extensions locally, improving consistency between local testing and production deployments. ## Developer Experience and Reliability - **Kiro Web** brings AWS’s AI-assisted, spec-driven development environment to browsers, providing access to chat and agent capabilities without installing the desktop IDE. - AWS updated default retry behavior across SDKs and CLI tools. - Improvements include smarter backoff and better throttling handling. - Production applications should become more resilient to transient failures without additional configuration. ## Container Image Changes - Bitnami images are being removed from Amazon ECR Public. - Teams currently using those images should review the migration timeline and update image references to Bitnami’s own registry to avoid interruptions. ## Upcoming AWS Events - AWS Summit Amsterdam: May 27 - AWS Summit Bangkok: May 28 - AWS Summit Milan: May 28 Builders should evaluate the Istanbul Local Zone for residency- or latency-sensitive systems, consider ExtendDB and SAM improvements for local workflows, and review the Bitnami registry change before images are removed from ECR Public.

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AIAWSAmazon BedrockServerless+4

aws·May 18, 2026·3 min readCurated summary

AWS Weekly Roundup: AWS Transform at 1 year, Claude Platform on AWS, EC2 M3 Ultra Mac instances, and more (May 18, 2026) | Amazon Web Services

AWS’s May 18, 2026 roundup highlights the rapid expansion of AI-assisted modernization, cloud infrastructure, and developer tooling. AWS Transform reached its first anniversary after processing billions of lines of code and migrating hundreds of thousands of servers, while new services provide direct Claude access, stronger Mac development hardware, improved analytics, and automated security remediation. The roundup also covers multicloud connectivity, AI research funding, community events, and startup credits. ## AWS Transform Reaches Its First Anniversary - AWS Transform launched a year earlier for modernizing .NET, mainframe, and VMware workloads. - New capabilities include: - Custom AWS-managed or user-defined code transformations - Language and framework upgrades - Performance optimization and code analysis - Full-stack Windows modernization - Mainframe reimagining and automated testing - In its first 12 months, customers: - Migrated hundreds of thousands of servers - Saved more than 1.6 million hours - Processed over 4.5 billion lines of code - AWS Transform agents are now available in Kiro, Claude, Cursor, and Codex. ## Major Product Launches - **Claude Platform on AWS:** Provides Anthropic’s native Claude APIs, console, and beta features through existing AWS accounts and billing. Anthropic operates the service, and customer data is processed outside the AWS security boundary. - **EC2 M3 Ultra Mac instances:** Use Apple M3 Ultra Mac Studio hardware with a 28-core CPU, 60-core GPU, 32-core Neural Engine, and 256 GB of unified memory. Compared with M4 Max instances, they offer more CPU, GPU, Neural Engine cores, and memory for parallel Xcode simulators and on-device machine learning. - **Redshift RG instances:** AWS Graviton-based instances run workloads up to 2.4 times faster than previous RA3 instances while costing 30% less per vCPU. They include a vectorized engine for Apache Iceberg and Parquet data. - **Bedrock Advanced Prompt Optimization:** Compares original and optimized prompts across as many as five models, helping users improve performance or migrate between models. - **AWS Security Agent repository scanning:** The preview feature analyzes entire codebases and generates fixes linked to specific files and lines. It is free for existing Security Agent customers during the preview. - **AWS Interconnect for OCI:** Enables private, resilient multicloud connections to Oracle Cloud Infrastructure. The same open specification already supports Google Cloud and is planned for Azure later in 2026. ## Research, Community, and Startup Updates - AWS is investing $110 million in the Build on Trainium program to give university researchers access to purpose-built AI chips. - Research at institutions including UC Berkeley, MIT, and Carnegie Mellon is open source, allowing improvements to benefit the broader developer community. - AWS Community Days 2026 will take place globally, with agendas organized by local developer communities. - The Kiro Startups Credit program has reopened, offering eligible organizations up to one year of Kiro Pro+ credits applied through AWS accounts. AWS’s latest updates emphasize managed AI tools, faster specialized hardware, automated modernization, and broader support for developers and researchers. Organizations can particularly benefit by evaluating AWS Transform, Bedrock prompt optimization, new Mac instances, and the expanding multicloud connectivity options.

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Amazon BedrockAmazon Ec2ClaudeApache Iceberg+3

aws·May 14, 2026·2 min readCurated summary

Amazon Bedrock introduces new advanced prompt optimization and migration tool | Amazon Web Services

Amazon Bedrock Advanced Prompt Optimization automatically rewrites prompts to improve performance or support migration between models. It compares original and optimized prompts across up to five Bedrock models using example inputs, reference answers, and configurable evaluation methods. The tool supports text and multimodal inputs, then reports quality scores, estimated costs, and latency. ## Prompt Optimization and Model Migration - Users can optimize prompts for their current model or compare a baseline model with up to four alternatives. - Bedrock runs prompts against supplied examples, evaluates the responses, and iteratively rewrites the prompt. - Results include: - Original and optimized prompt templates - Evaluation scores - Cost estimates - Latency information - The process can identify regressions in established use cases and improve weaker tasks. ## Multimodal and Dataset Support - Prompt templates and evaluation examples are supplied in JSONL format. - Each JSON object must appear on a single line. - Supported multimodal inputs include: - PNG and JPG images - PDF documents - Files can be uploaded directly or imported from Amazon S3. - Optimization results and evaluation data can also be written to an S3 location. ## Evaluation Methods Users can select one evaluation approach per prompt template: - **Lambda-based evaluation** - Uses custom Python scoring logic for metrics such as accuracy, F1, execution accuracy, or structured JSON matching. - The function compares model outputs with reference responses. - **LLM-as-a-judge** - Uses a custom rubric with named metrics, structured instructions, and rating scales. - Bedrock’s judge model evaluates responses and provides scores with reasoning. - Claude Sonnet 4.6 is the default judge, though other supported judge models can be selected. - **Natural-language steering criteria** - Describes desired qualities such as brand voice, formatting, or safety constraints. - A default LLM judge evaluates responses holistically against those criteria. ## Getting Started and Availability - Start from **Create prompt optimization** in the Amazon Bedrock console or use the `CreateAdvancedPromptOptimizationJob` API. - Optimization is available in selected AWS Regions across North America, Europe, Asia-Pacific, Canada, and South America. - Pricing is based on Bedrock inference tokens consumed during optimization, using standard per-token inference rates. The tool is most useful when teams need measurable prompt improvements or want to migrate applications to another model. Preparing representative evaluation examples and choosing an appropriate scoring method will be essential for producing reliable optimization results.

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Large Language ModelsAmazon BedrockMultimodal AIAmazon S3+3

aws·May 12, 2026·2 min readCurated summary

Amazon Redshift introduces AWS Graviton-based RG instances with an integrated data lake query engine | Amazon Web Services

Amazon Redshift introduces RG instances powered by AWS Graviton, targeting lower-cost, higher-volume analytics for both human users and AI agents. RG instances can run warehouse workloads up to 2.2× faster than RA3 at 30% lower price per vCPU, while an integrated data lake engine enables faster SQL queries across warehouse tables and S3 data. The architecture also removes the need for Redshift Spectrum and its per-terabyte scanning fees. ## Performance and Cost Improvements - RG instances deliver: - Up to 2.2× faster data warehouse workloads than RA3. - 30% lower pricing per vCPU. - Up to 2.4× faster queries on Apache Iceberg data. - Up to 1.5× faster queries on Apache Parquet data. - The improvements are designed for: - Low-latency BI dashboards. - ETL pipelines and near-real-time analytics. - High-volume queries generated by autonomous AI agents. - AWS recommends using the AWS Pricing Calculator to estimate savings for specific workloads. ## Integrated Data Lake Query Engine - RG instances query warehouse tables and S3 data lakes through one engine. - Data lake queries run directly on Redshift cluster nodes rather than through Redshift Spectrum. - Existing external tables, schemas, Spectrum queries, and SQL syntax remain unchanged. - Customers do not need to recreate external tables or modify application code. - Queries remain inside the customer’s VPC, use existing IAM roles, and avoid Spectrum’s former $5-per-terabyte scanning charge. ## Migration and Setup - RG clusters can be created or migrated through: - The AWS Management Console. - AWS CLI. - AWS API. - The integrated data lake engine is enabled by default. - Migration options include: - **Elastic Resize:** In-place migration with approximately 10–15 minutes of downtime for compatible configurations. - **Snapshot and Restore:** Creates an RG cluster from an RA3 snapshot and is useful when configuration changes are needed. ## Availability and Pricing Options - RG instances are available across numerous AWS Regions in North America, Europe, Asia-Pacific, Canada, and South America. - Redshift Provisioned customers can choose: - On-Demand Instances with hourly billing and no commitment. - Reserved Instances for additional savings. RG instances are intended for organizations combining data warehouse and data lake workloads, especially those needing lower costs and fast response times at high query volumes. Customers should test compatibility and use workload-specific pricing estimates before migrating.

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AI AgentsAmazon S3SqlApache Iceberg+4

aws·May 11, 2026·3 min readCurated summary

AWS Weekly Roundup: Amazon Bedrock AgentCore payments, Agent Toolkit for AWS, and more (May 11, 2026) | Amazon Web Services

The May 11, 2026 AWS roundup highlights growing support for autonomous AI agents, especially through Amazon Bedrock AgentCore’s managed payment capabilities. It also covers new tools for building secure agents on AWS, enhanced WorkSpaces automation, faster EC2 instances, and updates across Valkey, vector search, and agentic SRE operations. ## AgentCore Payments for Autonomous Agents - Amazon Bedrock AgentCore previewed managed payments for AI agents. - Agents can autonomously pay for: - APIs - MCP servers - Web content - Other agents - The service was developed with Coinbase and Stripe to handle billing, credentials, and compliance. - Developers can connect: - Coinbase CDP wallets - Stripe Privy wallets - Session-level spending limits help control agent transactions. - Potential applications include research agents purchasing live market data and coding agents calling paid APIs during execution. ## New Tools for Building AI Agents on AWS - **Agent Toolkit for AWS** provides production-ready tools and guidance at no additional charge. - It aims to reduce coding errors and token usage while adding enterprise security controls. - The toolkit replaces AWS Labs’ earlier MCP servers, plugins, and skills. - **AWS MCP Server** is now generally available as a managed, remote MCP server. - It provides secure, authenticated access to AWS services. - Agents interact through a small, standardized set of tools. - It is included in the Agent Toolkit for AWS. ## AI-Controlled Workspaces and New EC2 Instances - **Amazon WorkSpaces for AI agents** entered preview. - Agents can securely access and operate desktop applications. - Managed WorkSpaces environments provide governance and compliance controls. - The capability targets large-scale automation of everyday workflows. - New **EC2 M8idn/M8idb and R8idn/R8idb instances** use sixth-generation Intel Xeon processors and AWS Nitro cards. - They provide up to 43% better compute performance per vCPU than prior generations. - M8idn and R8idn offer up to 600 Gbps of network bandwidth. - M8idb and R8idb offer up to 300 Gbps of EBS bandwidth. ## Valkey and Vector Search Updates - Valkey, the community-driven Redis alternative, marked its second anniversary. - It has surpassed: - 100 million Docker pulls - 225 contributors - 1,500 pull requests - Valkey’s development pace is described as roughly twice that of Redis over the same period. - Valkey 9.0 is available through Amazon ElastiCache. - Amazon Aurora PostgreSQL-Compatible Edition can query billion-scale Amazon S3 Vectors using standard SQL. - Vector similarity searches can be combined with relational filters, such as price, inventory, or tenant, in a single query. ## Agentic Site Reliability Engineering - AWS DevOps Agent can be configured with “Spaces” that define investigation scopes. - It integrates with Amazon CloudWatch, Splunk, GitHub, and Slack. - Webhooks can trigger automated investigations. - The system can create mitigation plans and produce agent-ready specifications for coding tools such as Kiro. AWS’s latest updates emphasize autonomous agents that can transact, operate software, investigate incidents, and interact with cloud services while remaining governed by enterprise security and spending controls. Teams interested in these capabilities should start with the Agent Toolkit for AWS and explore the related previews and documentation.

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aws·May 6, 2026·3 min readCurated summary

The AWS MCP Server is now generally available | Amazon Web Services

The AWS MCP Server is now generally available as a managed way for AI agents to access AWS securely through IAM-authenticated tools. It combines live AWS documentation, access to more than 15,000 API operations, and sandboxed scripting so agents can produce more current, efficient, and production-ready results. The post concludes that this solves major limitations of model-only AWS assistance without granting agents unrestricted credentials. ## Why AI Agents Struggle with AWS - Models may lack knowledge of recently launched services such as Amazon S3 Vectors, Aurora DSQL, and Bedrock AgentCore. - Agents often default to the AWS CLI instead of AWS CDK or CloudFormation. - Generated IAM policies are frequently broader than necessary. - The resulting infrastructure may work in demos but fail production standards. ## Core AWS MCP Server Tools - `call_aws` can execute more than 15,000 AWS API operations using the user’s existing IAM credentials. - `search_documentation` and `read_documentation` retrieve current AWS documentation and best practices at query time. - The compact tool set reduces model context usage and is intended to support newly launched APIs within days. ## General Availability Improvements - IAM context keys allow fine-grained access control through standard IAM policies without requiring a separate server permission. - Documentation retrieval no longer requires authentication. - Reduced token consumption improves complex, multi-step workflows. - The `run_script` tool executes short Python scripts in a server-side sandbox. - The sandbox inherits IAM permissions. - It has no network access or access to the user’s local filesystem and shell. - It can combine multiple API calls, filter results, and calculate outputs in one round trip. ## Skills and AWS Best Practices - Skills replace Agent SOPs with curated guidance for common AWS tasks. - AWS service teams contribute and maintain the Skills. - They help agents avoid mistakes, use validated patterns, reduce hallucinations, and consume fewer tokens. - Keeping the tool list small makes agent behavior more predictable. ## Enterprise Security and Observability - IAM policies and Service Control Policies can separate human permissions from agent permissions. - For example, a user may perform write operations while the MCP server is restricted to read-only access. - CloudWatch metrics under the `AWS-MCP` namespace distinguish agent activity from direct human calls. - AWS CloudTrail records all API calls for auditing and compliance. ## Demonstration with Claude Code - Without the MCP Server, Claude Opus 4.6 suggested several valid ways to store embeddings on S3 but missed Amazon S3 Vectors because the service launched after its training cutoff. - With the MCP Server, Claude Code searched current AWS documentation and correctly identified S3 Vectors. - Claude Code can connect through the open-source `mcp-proxy-for-aws`, which bridges local IAM credentials and MCP’s OAuth 2.1 requirement. - The server works with Claude Code, Kiro, Cursor, Codex, and other MCP-compatible clients. ## Availability and Cost - The service is available in US East (N. Virginia) and Europe (Frankfurt). - It can make API calls across AWS Regions. - There is no additional charge for the MCP Server; users pay for AWS resources and applicable data transfer. The AWS MCP Server is a practical foundation for giving agents current AWS knowledge and controlled operational access. Teams should pair it with narrowly scoped IAM policies, read-only defaults where possible, and CloudWatch or CloudTrail monitoring.

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aws·May 5, 2026·2 min readCurated summary

Modernize your workflows: Amazon WorkSpaces now gives AI agents their own desktop (preview) | Amazon Web Services

Amazon WorkSpaces now lets AI agents operate desktop and legacy applications directly, eliminating the need to build APIs or modernize existing software. Agents use managed virtual desktops with IAM authentication, security controls, and auditability through CloudTrail and CloudWatch. The feature is in public preview and supports agent frameworks through the Model Context Protocol (MCP). ## The Challenge of Legacy Applications - Many enterprises depend on applications without modern APIs: - 75% of organizations reportedly run legacy applications. - 71% of Fortune 500 companies rely on mainframe-based processes with limited programmatic access. - Organizations can either delay AI adoption or undertake costly, risky modernization projects. ## AI Agents in Secure WorkSpaces - AI agents operate desktop applications inside managed WorkSpaces environments. - Agents authenticate with AWS Identity and Access Management (IAM). - Existing security and compliance controls remain in place because agents do not run on local machines. - AWS CloudTrail and Amazon CloudWatch provide audit trails. - WorkSpaces supports MCP, making it compatible with frameworks such as LangChain, CrewAI, and Strands Agents. ## Configuring Agent Access - Administrators create a WorkSpaces Applications stack and enable the **Add AI Agents** option. - Agent capabilities can include: - **Computer input:** Clicking, typing, and scrolling. - **Computer vision:** Capturing screenshots so the agent can interpret the interface. - **Screenshot storage:** Saving session images for auditing and debugging. - Administrators define screen resolution and image format. The example uses 1280×720 resolution and PNG images. - Agents connect through a managed MCP endpoint using IAM credentials. ## Automating Unmodified Desktop Workflows - A Strands Agent SDK and Amazon Bedrock example completes a prescription refill by: - Looking up a patient record. - Searching for medication. - Placing the order. - Confirming the refill. - The pharmacy application requires no API, code changes, migration, or awareness that an agent is controlling it. ## Availability - The feature is in public preview at no additional cost. - It is available in selected AWS Regions across the United States, Canada, Europe, and Asia. - Developers can begin with AWS’s GitHub repository or the Amazon WorkSpaces product page. Organizations can use WorkSpaces as a governed execution environment for AI agents, allowing them to automate legacy desktop workflows while postponing or avoiding extensive application modernization.

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aws·May 4, 2026·4 min readCurated summary

AWS Weekly Roundup: What’s Next with AWS 2026, Amazon Quick, OpenAI partnership, and more (May 4, 2026) | Amazon Web Services

The AWS weekly roundup highlights a major shift toward agentic AI across Amazon’s products and its partnership with OpenAI. The biggest announcements include expanded Amazon Quick capabilities, four specialized Amazon Connect solutions, and OpenAI models and Codex becoming available through Amazon Bedrock. AWS also introduced new EC2 instances, agent optimization tools, Ruby 4.0 support for Lambda, and a transition plan from Amazon Q Developer to Kiro. ## What’s Next with AWS 2026 - AWS and OpenAI executives presented new ways businesses are using AI agents to automate operations. - The announcements centered on Amazon Quick, Amazon Connect, and deeper integration with OpenAI through Amazon Bedrock. ## Amazon Quick Expands Beyond Chat - A new desktop app, currently in preview, connects Quick to local files, calendars, and communications without requiring a browser. - Users can sign up with a personal email or Google, Apple, GitHub, or Amazon credentials; an AWS account is not required. - Quick can generate: - Documents - Presentations - Infographics - Images - New integrations include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams. - The preview “Build custom apps with Quick” feature lets users create intelligent applications, dashboards, and web pages using natural-language instructions. ## Amazon Connect Becomes Four Agentic AI Products - **Amazon Connect Decisions** applies Amazon’s operational expertise and supply-chain tools to help organizations move from reactive crisis management to proactive planning. - **Amazon Connect Talent** provides AI-led interviews, science-backed assessments, and consistent candidate evaluations for large-scale hiring. - **Amazon Connect Customer**, the renamed customer-service product, supports personalized voice, chat, and digital experiences, with conversational AI that can be configured in weeks. - **Amazon Connect Health** supports patient verification, appointment management, patient insights, ambient documentation, and medical coding. ## OpenAI Partnership Expands Through Amazon Bedrock - OpenAI models, including GPT-5.5 and GPT-5.4, are coming to Bedrock in limited preview. - Customers can use existing Bedrock APIs with AWS security, governance, and cost controls, without managing new infrastructure. - **Codex on Amazon Bedrock** brings OpenAI’s coding agent into AWS environments: - Authentication uses AWS credentials. - Inference runs through Bedrock. - Usage can count toward AWS cloud commitments. - Initial access includes the Codex CLI, desktop app, and Visual Studio Code extension. - **Bedrock Managed Agents powered by OpenAI** combines OpenAI models with AWS infrastructure and the OpenAI harness for long-running, production-oriented agent workflows. ## New EC2 Instance Families - **M8in and M8ib** instances are generally available, offering up to 43% higher performance than M6in and M6ib. - M8in provides up to 600 Gbps of network bandwidth. - M8ib provides up to 300 Gbps of EBS bandwidth. - **R8in and R8ib** target memory-intensive workloads such as commercial databases, data lakes, and SAP HANA. - **C8ine and M8ine** provide up to 2.5 times higher packet performance per vCPU and up to twice the internet-gateway throughput of their predecessors. - These network-optimized instances are designed for virtual firewalls, load balancers, security appliances, and 5G user-plane workloads. ## AgentCore and Lambda Updates - Bedrock AgentCore Optimization, in preview, adds: - Production-trace analysis - Recommendations for system prompts and tool descriptions - Batch evaluations - A/B testing against live traffic - Recommendations require human approval before deployment. - AWS Lambda now supports Ruby 4.0 as a managed runtime and container base image. - Ruby 4.0 support includes advanced logging features such as structured JSON logs, configurable log levels, and custom CloudWatch log groups. ## Amazon Q Developer Moves Toward Kiro - Amazon Q Developer IDE plugins and paid subscriptions will reach end of support on April 30, 2027. - New signups will be blocked beginning May 15, 2026. - Existing subscriptions can continue adding users until then. - Opus 4.6 will leave Q Developer Pro on May 29, 2026, while newer coding models such as Opus 4.7 will be exclusive to Kiro. - Q Developer experiences in the AWS Console, documentation, mobile app, Slack, and Microsoft Teams are unaffected. AWS’s direction is increasingly centered on managed AI agents integrated into everyday business workflows. Organizations adopting these services should evaluate the new Bedrock, Quick, and Connect capabilities while also planning migration from Q Developer to Kiro before the announced support deadlines.

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