aws·Apr 28, 2026·3 min readCurated summary

Top announcements of the What’s Next with AWS, 2026 | Amazon Web Services

The 2026 “What’s Next with AWS” event focused on how AI agents are reshaping business operations. Major announcements included Amazon Quick, an AI work assistant; four specialized Amazon Connect solutions; and an expanded AWS–OpenAI partnership bringing OpenAI models and Codex to Amazon Bedrock. Together, these offerings emphasize integrated agents that can connect to existing systems, make decisions, and execute tasks within enterprise-controlled infrastructure. ## Amazon Quick Becomes a Broader AI Work Assistant - Amazon Quick connects to workplace information, learns user preferences, and takes action on users’ behalf. - A new desktop app, currently in preview, can access local files, calendars, and communications without requiring a browser. - Free and Plus plans are available without an AWS account. Users can register with a personal email or Google, Apple, GitHub, or Amazon credentials. - Quick can generate documents, presentations, infographics, and images directly within chat. - New native integrations include Google Workspace, Zoom, Airtable, Dropbox, and Microsoft Teams. ## Amazon Connect Expands into Four Agentic AI Products AWS is repositioning Amazon Connect as a portfolio of solutions for specific business workflows: - **Amazon Connect Decisions:** A supply-chain planning and intelligence platform using AI teammates, Amazon’s operational expertise, and more than 25 specialized tools to support proactive planning. - **Amazon Connect Talent:** A hiring solution in preview that provides AI-led interviews, science-backed assessments, and standardized evaluations for large-scale recruiting. - **Amazon Connect Customer:** The renamed customer-experience product, supporting voice, chat, and digital channels. New configuration tools aim to let organizations deploy conversational AI in weeks rather than months. - **Amazon Connect Health:** Automates patient verification, appointments, patient insights, ambient documentation, and medical coding to improve access to care and reduce administrative workloads. ## AWS and OpenAI Expand Their Partnership The companies announced several limited-preview offerings that bring OpenAI capabilities into AWS environments: - **OpenAI models on Amazon Bedrock:** Models including GPT-5.5 and GPT-5.4 will be accessible through existing Bedrock APIs, with AWS security, governance, and cost controls. - **Codex on Amazon Bedrock:** Organizations can run OpenAI’s coding agent using AWS credentials and infrastructure, with usage counting toward AWS cloud commitments. Initial access includes the Codex CLI, desktop app, and Visual Studio Code extension. - **Bedrock Managed Agents powered by OpenAI:** This service combines OpenAI models with AWS-managed infrastructure and the OpenAI harness for building production-ready agents capable of reasoning through long-running tasks. AWS’s announcements point toward a future in which AI agents are embedded directly into workplace tools, operational systems, customer-service platforms, and cloud development environments. Organizations looking to adopt these capabilities should evaluate the available previews, integrations, governance controls, and workflow fit before moving to production.

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AWSCloud InfrastructureOpenaiCodex+4

aws·Apr 27, 2026·3 min readCurated summary

AWS Weekly Roundup: Anthropic & Meta partnership, AWS Lambda S3 Files, Amazon Bedrock AgentCore CLI, and more (April 27, 2026) | Amazon Web Services

This week’s AWS news centers on deeper AI infrastructure partnerships and tools for building production-ready agents. AWS and Anthropic are expanding Claude’s integration with AWS hardware and Amazon Bedrock, while Meta is adopting Graviton for large-scale agentic AI workloads. New services for Lambda, EKS, Aurora, and Bedrock also emphasize simpler data access, hybrid networking, serverless scaling, and faster agent development. ## Anthropic and Meta Expand AWS AI Partnerships - Anthropic is training advanced foundation models on AWS Trainium and Graviton processors. - Anthropic and AWS’s Annapurna Labs are co-engineering at the silicon level to improve efficiency across the stack. - Claude Cowork is now available through Amazon Bedrock, allowing enterprise teams to collaborate with Claude while keeping data within AWS. - A unified Claude Platform on AWS is planned, offering a single experience for building, deploying, and scaling Claude applications. - Meta signed an agreement to deploy tens of millions of AWS Graviton cores for CPU-intensive agentic AI tasks, including reasoning, code generation, search, and orchestration. ## New Lambda and Kubernetes Infrastructure - AWS Lambda can mount Amazon S3 buckets as file systems using S3 Files. - Functions can perform standard file operations without downloading data first. - Built on Amazon EFS, S3 Files combines file-system access with S3’s scalability, durability, and cost model. - Multiple Lambda functions can share the same workspace, supporting AI agents that need persistent memory or shared state. - The Amazon EKS Hybrid Nodes gateway simplifies networking between cloud-based EKS resources and on-premises Kubernetes Pods. - It enables pod-to-pod traffic, control-plane webhook communication, and access to AWS services without making on-premises pod networks routable. - The gateway is available at no additional charge. ## Aurora Serverless and Bedrock Agent Development - Aurora Serverless now offers up to 30% better performance on platform version 4. - Its scaling algorithm better handles competing workloads, including busy APIs and bursty agentic AI applications. - The service continues to scale to zero during idle periods, with no additional charge for the improvements. - Amazon Bedrock AgentCore adds a managed harness in preview, allowing developers to define a model, system prompt, and tools without writing orchestration code. - Harnesses can later be exported as Strands-based code for greater control. - The AgentCore CLI supports governed, auditable deployments through AWS CDK, with Terraform support planned. - The CLI is available in 14 AWS Regions at no additional charge, and AgentCore skills support coding assistants. ## Cost Management, Operations, and Machine Learning - Granular cost attribution for Amazon Bedrock enables teams to track usage by project or organization and support detailed chargeback. - AWS DevOps Agent can work with the Salesforce MCP Server to investigate incidents, diagnose causes, and notify customers through Salesforce Service Cloud. - AWS microcredentials are now free through AWS Skill Builder in supported countries. - These hands-on assessments use simulated business scenarios and live AWS environments rather than traditional multiple-choice testing. - Amazon SageMaker AI can recommend optimized generative AI inference configurations, including instance types, containers, and inference parameters, helping reduce latency and deployment costs. ## Upcoming AWS Events - “What’s Next with AWS” is scheduled as a virtual event on April 28. - AWS Summits continue in May across cities including Singapore, Tel Aviv, Warsaw, Stockholm, Sydney, Hamburg, Seoul, Amsterdam, Bangkok, and Milan. AWS’s latest releases point toward a more integrated AI platform: specialized hardware for model execution, managed agent tooling, shared state through serverless storage, and stronger cost and operational controls. Builders should evaluate S3 Files and AgentCore for AI workflows, while teams running production inference can benefit from SageMaker recommendations and Bedrock’s improved cost attribution.

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KubernetesGenerative AIPostgreSQLAWS+4

aws·Apr 20, 2026·3 min readCurated summary

AWS Weekly Roundup: Claude Opus 4.7 in Amazon Bedrock, AWS Interconnect GA, and more (April 20, 2026) | Amazon Web Services

The roundup highlights major AWS advances in AI, networking, developer tooling, and security. Claude Opus 4.7 is now available through Amazon Bedrock with stronger agentic coding and research capabilities, while AWS Interconnect simplifies private connectivity across clouds and remote locations. Additional launches improve container supply-chain security, application modernization, database access, cost attribution, and quantum-resistant encryption. ## Anthropic Claude Opus 4.7 in Amazon Bedrock - Anthropic’s latest Opus model improves: - Agentic coding and long-running tasks - Complex code reasoning - Document creation, financial analysis, and multi-step research - It scores: - 64.3% on SWE-bench Pro - 87.6% on SWE-bench Verified - Bedrock features include: - Dynamic capacity allocation - Adaptive thinking and request-specific token budgets - A 1-million-token context window - High-resolution image support for charts, documents, and screen interfaces - The model launched in US East, Tokyo, Ireland, and Stockholm, supporting up to 10,000 requests per minute per account and Region. ## AWS Interconnect Reaches General Availability - **AWS Interconnect – Multicloud** provides Layer 3 private connectivity between AWS VPCs and other clouds. - Google Cloud is supported initially; Azure and OCI are planned. - Traffic uses private networks and the AWS global backbone rather than the public internet. - Includes MACsec encryption, multi-facility resilience, and CloudWatch monitoring. - The underlying specification is open source under Apache 2.0. - **AWS Interconnect – Last Mile** connects branches, data centers, and remote sites to AWS through network providers. - Automatically provisions four redundant connections across two physical locations. - Configures BGP, MACsec, and Jumbo Frames. - Supports adjustable bandwidth from 1 to 100 Gbps. - Launches in US East with Lumen. ## Developer, Database, and Modernization Updates - Amazon ECR pull-through cache now discovers and synchronizes OCI referrers such as signatures, SBOMs, and attestations. - AWS Transform is available directly in Kiro and VS Code for migrations such as language-version upgrades and AWS SDK updates. - Aurora DSQL’s PHP connector supports IAM authentication, SSL, connection pooling, and optional optimistic-concurrency retries. - AWS Transform Custom can modernize VB6 applications into C# ASP.NET Core applications, including COM, ADO, and UI migration challenges. ## Security, Access Control, and Cost Management - Amazon Q for Google Drive now enforces document-level permissions using indexed ACLs and real-time access checks. - AWS Secrets Manager supports hybrid post-quantum TLS using ML-KEM through updated agents, Lambda extensions, and CSI drivers. - Amazon Bedrock can attribute inference costs to individual IAM principals, with reporting through CUR 2.0 and aggregation by teams, projects, or cost centers. ## Compute, Kubernetes, and Storage - EC2 C8in and C8ib instances use sixth-generation Intel Xeon processors and AWS Nitro cards. - C8in offers up to 600 Gbps networking. - C8ib provides up to 300 Gbps EBS bandwidth. - Both scale to 384 vCPUs. - EKS Auto Mode automates networking components such as VPC CNI, load balancers, and DNS while retaining enterprise security controls. - EBS Volume Clones provide immediately usable point-in-time copies for development, disaster recovery testing, and CI/CD workflows. ## Additional AWS Guidance - CloudFront Functions and CloudFront KeyValueStore can support zero-downtime API decomposition using user-aware routing and the Strangler Fig pattern. - The roundup also points readers to AWS events, weekly Power Hour training, and Community.aws meetups. The most significant developments are Bedrock’s expanded AI capabilities and Interconnect’s managed private networking. Teams should evaluate Claude Opus 4.7 for complex AI workflows, use Interconnect where multicloud or resilient connectivity is required, and consider the new security and cost-attribution features for stronger governance.

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KubernetesPostgreSQLAmazon BedrockDevOps+4

aws·Apr 16, 2026·3 min readCurated summary

Introducing Anthropic’s Claude Opus 4.7 model in Amazon Bedrock | Amazon Web Services

Claude Opus 4.7 is now available in Amazon Bedrock as Anthropic’s most capable Opus model for coding, professional knowledge work, long-running agents, and visual tasks. It runs on Bedrock’s new inference engine, which dynamically schedules capacity, improves availability, queues requests during demand spikes, and provides zero operator access to prompts and responses. AWS positions the model as a production-ready upgrade to Opus 4.6, though teams may need to adjust prompts and agent harnesses. ## Model Improvements - **Agentic coding:** Stronger long-horizon autonomy, systems engineering, and complex code reasoning. - 64.3% on SWE-bench Pro - 87.6% on SWE-bench Verified - 69.4% on Terminal-Bench 2.0 - **Knowledge work:** Better document creation, financial analysis, and multi-step research. - Handles underspecified requests by making and explaining reasonable assumptions. - Self-verifies responses to improve first-pass quality. - 64.4% on Finance Agent v1.1. - **Long-running tasks:** Maintains coherence across its full 1-million-token context window while handling ambiguity and verifying results. - **Vision:** High-resolution image support improves analysis of charts, dense documents, and detailed screen interfaces. - **Adaptive thinking:** Dynamically allocates reasoning-token budgets based on request complexity. ## Bedrock Infrastructure and Scaling - The new inference engine uses updated scheduling and scaling logic to allocate capacity dynamically. - It prioritizes steady-state workloads while rapidly scaling capacity for changing demand. - During high demand, requests are queued instead of rejected. - Up to 10,000 requests per minute per account and Region are available immediately, with additional capacity available by request. - Zero operator access prevents AWS and Anthropic operators from viewing customer prompts and responses. ## Ways to Invoke the Model - Test Claude Opus 4.7 in the Amazon Bedrock console through **Playground**. - Use the Anthropic Messages API through: - Anthropic SDK integrations with Bedrock - `bedrock-mantle` endpoints - Use Bedrock-native APIs: - **Converse API** for multi-turn conversations and Guardrails integration - **Invoke API** for direct invocation and lower-level control - Invoke it with the AWS CLI using model ID `anthropic.claude-opus-4-7`. - The Anthropic Bedrock SDK can authenticate with AWS Signature Version 4 and submit Messages API requests programmatically. ## Availability - Initially available in: - US East (N. Virginia) - Asia Pacific (Tokyo) - Europe (Ireland) - Europe (Stockholm) - AWS directs users to the Bedrock model and pricing pages for regional availability updates. Teams seeking stronger coding agents, complex research workflows, or high-volume production inference can try Claude Opus 4.7 in Bedrock, while validating prompt and harness changes before migrating existing Opus 4.6 workloads.

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PythonAmazon BedrockAPIAgentic Coding+4

aws·Apr 14, 2026·3 min readCurated summary

AWS Interconnect is now generally available, with a new option to simplify last-mile connectivity | Amazon Web Services

AWS Interconnect is a managed service for private, high-speed connectivity between AWS and other clouds or on-premises networks. Its multicloud capability, now generally available, initially connects AWS with Google Cloud while Microsoft Azure support is planned for later in 2026. The service aims to replace complex VPN, colocation, and third-party networking setups with a turnkey, resilient configuration managed through AWS. ## AWS Interconnect Capabilities - **Interconnect – multicloud** connects an AWS VPC privately to VPCs on other cloud providers. - **Interconnect – last mile** simplifies connectivity from branch offices, data centers, and remote sites through existing network providers. - Both capabilities provide: - Dedicated bandwidth - Private connectivity - Managed provisioning - Reduced infrastructure and configuration overhead - Connections can be configured through the AWS Console by selecting the location or provider, AWS Region, and bandwidth. ## Multicloud Connectivity - The service provides a managed **Layer 3 connection** between AWS and another cloud provider. - Traffic uses the AWS global backbone and the partner’s private network rather than the public internet. - This improves: - Latency predictability - Throughput consistency - Isolation from internet congestion - Google Cloud is supported at launch; Microsoft Azure is expected later in 2026. ## Security, Resilience, and Monitoring - Physical links between AWS and partner routers use **IEEE 802.1AE MACsec encryption** by default. - Each cloud provider handles encryption on its own backbone, so customers must verify that the resulting deployment satisfies compliance requirements. - Connections use multiple logical links across at least two physical facilities to protect against device or facility failures. - Amazon CloudWatch integration includes: - A Network Synthetic Monitor for round-trip latency and packet loss - Bandwidth utilization metrics for capacity planning ## Open Partner Specification - AWS has published the underlying Interconnect specification on GitHub under the **Apache 2.0 license**. - Other cloud providers can become partners by implementing the specification and meeting AWS requirements for: - Resiliency - Support - Service-level agreements - Operational readiness ## Provisioning an AWS–Google Cloud Connection - The demonstration connects a single AWS VPC to a Google Cloud VPC using a Direct Connect Gateway. - In the AWS Direct Connect console, the user: - Selects Google Cloud as the provider - Chooses AWS Region `eu-central-1` - Chooses Google Cloud Region `europe-west3` - Specifies bandwidth - Selects a Direct Connect Gateway - Enters the Google Cloud project ID - AWS then generates an activation key for use on the Google Cloud side. ## Configuring Google Cloud - Because a Google Cloud web console option was unavailable at the time, the example uses the `gcloud` CLI. - The user creates a transport resource with: - The AWS activation key - The Google Cloud region - The target VPC network - Advertised AWS routes - After the transport reaches the appropriate state, the user creates a VPC peering connection between the Google Cloud VPC and the generated transport network. - Custom routes are imported and exported through the peering configuration. ## Completing the AWS Configuration - Once the Google Cloud transport and peering are configured: - The AWS Interconnect status can be checked in the Interconnect console. - The Direct Connect Gateway shows the new attachment. - The final AWS-side step is associating the gateway with the appropriate Virtual Private Gateway. - The Virtual Private Gateway must be in the same AWS Region as the Interconnect. - AWS routing still requires a final route entry so workloads can reach the remote Google Cloud network. AWS Interconnect is best suited to organizations operating hybrid or multicloud environments that want private, resilient connectivity without managing physical links or complex third-party networking. The managed provisioning process can reduce setup time to minutes, but teams should still validate routing, encryption responsibilities, regional constraints, and compliance requirements.

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Google CloudCloud MonitoringNetwork ConfigurationAws Interconnect+4

aws·Apr 13, 2026·3 min readCurated summary

AWS Weekly Roundup: Claude Mythos Preview in Amazon Bedrock, AWS Agent Registry, and more (April 13, 2026) | Amazon Web Services

AWS’s April 13, 2026 roundup centers on improving governance and visibility as organizations move AI workloads into production. Amazon Bedrock added IAM user and role-based cost allocation, while Claude Mythos Preview and the AWS Agent Registry expanded capabilities for cybersecurity and agent management. The week also brought updates across storage, observability, WorkSpaces, and quantum computing. ## Bedrock Cost Allocation - Organizations can tag IAM users and roles with attributes such as team or cost center. - Activated tags appear in Billing and Cost Management, AWS Cost Explorer, and detailed Cost and Usage Reports. - This enables teams to track foundation model inference costs across departments, agents, and tools such as Claude Code on Bedrock. ## Claude Mythos Preview in Amazon Bedrock - Anthropic’s Claude Mythos is available as a gated research preview through Project Glasswing. - The model is designed for advanced cybersecurity work, including: - Finding sophisticated vulnerabilities - Analyzing large codebases - Handling complex reasoning and coding tasks - Access is limited to allowlisted organizations, with priority given to critical internet companies and open-source maintainers. ## AWS Agent Registry - AgentCore’s new registry provides a private catalog for AI agents, tools, skills, MCP servers, and custom resources. - Features include semantic and keyword search, approval workflows, and CloudTrail auditing. - Teams can access it through the AgentCore Console, AWS CLI, SDKs, or as an MCP server from IDEs. - The goal is to improve reuse and governance instead of having teams independently recreate capabilities. ## Other AWS Launches - **Amazon S3 Files:** Exposes S3 buckets as shared file systems with file-system semantics, caching, and high aggregate read throughput. Applications can use file-system and S3 APIs simultaneously without migration or code changes. - **OpenSearch observability:** Adds Managed Prometheus, PromQL support, RED metrics, agent tracing, and OpenTelemetry GenAI semantic conventions for correlating AI execution with logs and traces. - **WorkSpaces Advisor:** Uses generative AI to diagnose Amazon WorkSpaces Personal configuration issues and recommend fixes. - **Amazon Braket:** Adds Rigetti’s 108-qubit Cepheus-1-108Q processor, supporting Braket SDK, Qiskit, CUDA-Q, Pennylane, and pulse-level control. ## Additional Resources and Upcoming Events - AWS highlighted guidance for regional availability monitoring with S3, Bedrock model lifecycle management, memory-intensive Lambda managed instances, and OpenClaw deployment choices. - Kiro is bringing back startup credits, offering eligible companies one year of Pro+ access across three team-size tiers. - The virtual “What’s Next with AWS” event on April 28 will focus on agentic AI and feature AWS, OpenAI, and industry leaders. Organizations adopting AI at scale should prioritize IAM-based cost attribution, centralized agent governance, and lifecycle planning for foundation models.

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Database DesignPostgreSQLAmazon BedrockAws Lambda+4

aws·Apr 7, 2026·3 min readCurated summary

Launching S3 Files, making S3 buckets accessible as file systems | Amazon Web Services

Amazon S3 Files makes general-purpose S3 buckets accessible through a native NFS-based file system. It combines S3’s durability, cost, and broad service integration with interactive file operations, shared access, and low-latency performance. The post concludes that this reduces the need to choose between object storage and traditional file systems for many AWS workloads. ## Bridging Object Storage and File Systems - S3 Files presents S3 objects as files and directories. - Applications can use standard NFS v4.1+ operations, including creating, reading, updating, and deleting files. - Changes made through the file system are synchronized back to S3 as new objects or object versions. - Changes made directly in S3 generally appear in the file system within seconds, though synchronization can sometimes take longer. - Multiple compute resources can mount the same file system and share data without duplicating it. ## Performance and Data Access - S3 Files uses Amazon EFS underneath and provides approximately 1 ms latency for active data. - Frequently accessed metadata and file contents are placed on high-performance storage. - Large sequential reads can be served directly from S3 to maximize throughput. - Byte-range reads transfer only the requested portion of a file, reducing data movement and cost. - Intelligent prefetching anticipates access patterns. - Administrators can choose whether to cache complete files or metadata only. - NFS close-to-open consistency supports concurrent, interactive workloads such as ML pipelines and collaborative AI agents. ## Supported AWS Compute Services S3 Files can expose buckets to: - Amazon EC2 instances - Amazon ECS and EKS containers - AWS Fargate workloads - AWS Lambda functions This allows production applications, machine-learning systems, and agentic AI tools to access shared S3 data using ordinary file-system interfaces. ## Creating and Mounting an S3 File System The demonstration uses an EC2 instance and a general-purpose S3 bucket: - Create an S3 file system from the S3 console, AWS CLI, or infrastructure-as-code tools. - Configure or discover a mount target inside the relevant VPC. - Mount the file system on EC2 with commands such as: ```bash sudo mkdir /home/ec2-user/s3files sudo mount -t s3files fs-...:/ /home/ec2-user/s3files ``` - Files created in the mounted directory become visible in the S3 bucket after synchronization. - Standard commands such as `ls`, `echo`, and AWS CLI operations can verify that file contents are consistent between the mount and S3. ## Security, Permissions, and Monitoring - IAM identity and resource policies control access at both the file-system and object levels. - Data is encrypted in transit with TLS 1.3. - Data at rest uses SSE-S3 or customer-managed AWS KMS keys. - POSIX permissions rely on user IDs and group IDs stored as object metadata. - CloudWatch provides performance and update metrics. - CloudTrail records management events. - EC2 instances should use the latest `amazon-efs-utils` package, which is included in AWS-provided AMIs. S3 Files is best suited to workloads requiring shared, interactive file access while retaining data in S3. Teams should still evaluate access patterns and latency requirements, but the service offers a practical way to use familiar file operations without giving up S3’s centralized, durable storage model.

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Amazon S3Aws CliAws Ec2Aws Eks+4

aws·Apr 6, 2026·3 min readCurated summary

AWS Weekly Roundup: AWS DevOps Agent & Security Agent GA, Product Lifecycle updates, and more (April 6, 2026) | Amazon Web Services

The April 6, 2026 AWS Weekly Roundup highlights the general availability of AWS DevOps Agent and AWS Security Agent, autonomous “frontier agents” designed to handle complex operational and security tasks. It also reviews AWS service lifecycle changes and summarizes notable product launches and technical updates from the previous week. The overall message is that AWS is expanding agentic automation while helping customers manage service transitions and adopt new capabilities. ## AWS DevOps Agent and Security Agent Reach GA - **AWS DevOps Agent** - Investigates incidents, accelerates resolution, and helps prevent recurring problems. - Works continuously across multiple steps until an operational goal is complete. - Customers report up to **75% lower mean time to resolution (MTTR)** and **3–5 times faster incident resolution**. - Western Governors University reduced resolution times from hours to minutes. - **AWS Security Agent** - Provides continuous, context-aware penetration testing during the software development lifecycle. - Operates similarly to a human penetration tester. - LG CNS reported testing that was more than **50% faster**, approximately **30% less expensive**, and produced fewer false positives. - **Deployment flexibility** - Both agents support AWS, multicloud, and on-premises environments. - They are intended to automate repetitive investigative and testing work while allowing teams to focus on higher-value activities. ## AWS Service Lifecycle Changes AWS updated its Product Lifecycle Changes guidance on March 31, 2026, including migration recommendations and alternative services. - Services with availability changes or maintenance guidance include: - AWS App Runner - AWS Audit Manager - AWS CloudTrail Lake - AWS Glue Ray jobs - AWS IoT FleetWise - Amazon Application Recovery Controller Readiness Check - Amazon Comprehend features such as Topic Modeling and Prompt Safety Classification - Amazon Rekognition streaming and batch moderation features - Amazon SNS Message Data Protection - Services listed as entering sunset include: - AWS Service Management Connector - Amazon RDS Custom for Oracle - Amazon WorkMail - Amazon WorkSpaces Thin Client - **Amazon Chime SDK Proxy Sessions** is reaching sunset. AWS recommends reviewing the relevant service documentation or contacting Support to reduce operational disruption. ## Notable AWS Launches - Amazon ECS introduced **Managed Daemons for ECS Managed Instances**. - The AWS Sustainability console now consolidates **Scope 1–3 emissions reporting**. - **Amazon Bedrock AgentCore Evaluations** became generally available. - AWS Transform added generally available automated codebase analysis. - CloudWatch introduced OpenTelemetry Container Insights for Amazon EKS in preview. - Amazon Lightsail added compute-optimized bundles with up to **72 vCPUs**. - Amazon CloudFront added **SHA-256 support** for signed URLs and signed cookies. ## Additional AWS Resources The roundup also points readers to material on: - Architecting agentic AI applications on AWS. - Reducing data-transfer costs with Network Load Balancers. - Preventing hallucinations in production AI agents. - The AWS World Sports Innovation Cup. - Exploring AWS communities through an interactive 3D globe. AWS also encourages readers to participate in Builder Center discussions, community events, AWS Summits, and developer-focused programs. AWS teams should review the lifecycle notices for services they depend on, while developers and operations groups may benefit from evaluating the new agents and launches for automation, security testing, and observability improvements.

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ObservabilityAWSDevOpsSecurity+4

aws·Apr 3, 2026·2 min readCurated summary

Amazon Bedrock Guardrails supports cross-account safeguards with centralized control and management | Amazon Web Services

Amazon Bedrock Guardrails now supports cross-account safeguards, allowing organizations to centrally enforce safety controls across AWS accounts and organizational units. Administrators can apply immutable, versioned guardrails to all Bedrock model invocations while still allowing account- or application-specific policies. The capability is generally available across commercial and GovCloud Regions where Bedrock Guardrails is supported. ## Centralized Organization- and Account-Level Enforcement - **Organization-level enforcement** uses an Amazon Bedrock policy created in the AWS Organizations management account. - Policies can attach a specified guardrail and version to: - The organization root - Organizational units - Individual AWS accounts - The selected guardrail is automatically applied to Bedrock inference requests across targeted member entities. - Different policies and guardrails can be assigned to different accounts or organizational units. - **Account-level enforcement** applies a configured guardrail to all Bedrock inference API calls within one account and Region. ## Configuring Guardrail Coverage - Guardrails must use a specific version so their configuration remains immutable and cannot be changed by member accounts. - Administrators can choose whether enforcement: - Includes or excludes specific Bedrock models - Covers all or only selected system and user prompt content - **Comprehensive** mode guards all content, regardless of caller-provided tags. - **Selective** mode relies on callers to identify content requiring protection, reducing processing for pre-validated inputs. ## Testing and Verification - Account-level enforcement can be configured in the Amazon Bedrock Guardrails console. - Enforcement can be tested with: - `InvokeModel` - `InvokeModelWithResponseStream` - `Converse` - `ConverseStream` - Responses include guardrail assessment details and identify the enforced guardrail. - Member accounts can verify organization-level enforcement in the Bedrock console. ## Important Considerations - Organizations must meet prerequisites such as configuring resource-based policies for guardrails. - Incorrect or invalid guardrail ARNs can cause policy violations, prevent safeguards from being enforced, and block model inference. - Automated Reasoning checks are not supported. - Charges apply for each enforced guardrail based on its configured safeguards. ## Availability Cross-account safeguards are generally available in all commercial and GovCloud AWS Regions where Amazon Bedrock Guardrails is available. Organizations can enable the feature through the Amazon Bedrock and AWS Organizations consoles. Overall, the capability gives security teams a centralized way to enforce responsible AI requirements while reducing the need to audit guardrail settings independently in every account and application.

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Amazon BedrockAws OrganizationsGuardrailAi Safety+4

aws·Apr 1, 2026·2 min readCurated summary

Announcing managed daemon support for Amazon ECS Managed Instances | Amazon Web Services

Amazon ECS Managed Daemons let platform teams independently deploy and maintain monitoring, logging, and tracing agents across ECS Managed Instances. This decouples operational tooling from application task definitions, reducing coordination and redeployment work. ECS ensures daemons are available before applications start and maintains coverage during rolling updates. ## Decoupled Daemon Management - Platform teams can centrally deploy and update agents without changing application services or rebuilding AMIs. - Daemons can target multiple or specific capacity providers. - Each instance runs exactly one daemon copy shared by its application tasks. - CPU and memory settings are managed separately from application configurations. - Daemons start before application tasks and are drained after them. ## Deployment and Updates - Daemon task definitions are created separately in the ECS console. - A daemon can be associated with a cluster and an ECS Managed Instances capacity provider. - ECS automatically launches the daemon on every applicable instance. - Rolling updates use a “start before stop” process: - New instances launch with the updated daemon. - The daemon starts before application tasks migrate. - Old instances are terminated afterward. - Configurable drain percentages control replacement speed, while automatic rollback improves update safety. ## Technical Capabilities - Managed daemons use a dedicated `daemon_bridge` network mode to communicate with application tasks while remaining isolated from application networking. - They support privileged containers, additional Linux capabilities, and host filesystem mounts. - These features enable host-level monitoring of metrics, processes, and system calls. - ECS validates and manages daemon-specific task definitions independently from standard application tasks. ## Availability and Cost - Managed daemon support is available in all AWS Regions. - There is no additional managed-daemon fee; users pay only for the compute resources consumed by daemon tasks. - The feature can be configured through the ECS console, APIs, and documentation. For organizations running many ECS services, managed daemons provide a simpler and more reliable way to operate shared infrastructure agents without involving application teams in every update.

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Amazon EcsContainerizationResource ManagementManaged Daemons+3

aws·Mar 31, 2026·2 min readCurated summary

Announcing the AWS Sustainability console: Programmatic access, configurable CSV reports, and Scope 1–3 reporting in one place | Amazon Web Services

The AWS Sustainability console is a standalone service that centralizes AWS emissions reporting and sustainability resources. It builds on the Customer Carbon Footprint Tool while adding independent permissions, customizable reports, fiscal-year support, and programmatic access. The underlying emissions data and methodology remain unchanged, but organizations now have more flexible ways to analyze and automate sustainability reporting. ## Independent Sustainability Access - Sustainability professionals can access emissions data without receiving AWS Billing permissions. - The console uses a permissions model separate from the Billing console. - Historical emissions data is available back to January 2022 at no additional cost. ## Scope 1–3 Emissions Reporting - Reports AWS-related emissions in metric tons of carbon dioxide equivalent (MTCO2e). - Covers: - **Scope 1:** Direct emissions from controlled sources, such as data center fuel use. - **Scope 2:** Indirect emissions from purchased energy. - **Scope 3:** Value-chain emissions, including server manufacturing and data center construction. - Data can be viewed by AWS Region and service, including Amazon EC2, Amazon S3, and CloudFront. - Both market-based method (MBM) and location-based method (LBM) calculations are supported. - The methodology is unchanged from the Customer Carbon Footprint Tool and has been independently verified by Apex. ## Configurable Reports and Fiscal Years - The Reports page provides preset monthly and annual emissions reports. - Users can create custom CSV reports by selecting: - Fields - Time granularity - Date ranges - Services, Regions, and other filters - Organizations can configure fiscal years that differ from the calendar year. - Once configured, data views and exports use the organization’s fiscal quarters and reporting periods. ## API and AWS CLI Access - A new API and AWS SDK support integration with: - Internal reporting pipelines - Sustainability dashboards - Compliance workflows - Teams can retrieve emissions for specific periods across many accounts without creating a data export. - Custom account groupings can be used even when they do not match the AWS Organizations hierarchy. - The AWS CLI command `get-estimated-carbon-emissions` returns emissions values, time periods, units, and model versions for MBM and LBM data. ## Availability and Future Development - The console is accessible through the AWS Management Console. - It complements existing Data Exports, allowing users to investigate emissions visually and automate stakeholder reporting. - AWS plans to expand the console with additional capabilities and publishes feature and methodology updates through its Release notes page. Organizations can begin using the free AWS Sustainability console immediately to explore emissions trends, create tailored reports, and connect AWS carbon data to existing sustainability processes.

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APIAws CliCarbon FootprintAws Sustainability+3

aws·Mar 30, 2026·3 min readCurated summary

AWS Weekly Roundup: AWS AI/ML Scholars program, Agent Plugin for AWS Serverless, and more (March 30, 2026) | Amazon Web Services

The March 30, 2026 AWS Weekly Roundup highlights the new AWS AI & ML Scholars program, which will offer free generative AI education to up to 100,000 people and fully funded Udacity Nanodegrees to 4,500 top participants. It also emphasizes new tools for serverless development, SageMaker IDE integration, expanded Lambda Managed Instance capacity, and streaming speech synthesis. AWS Summit and Community Day events are also scheduled worldwide. ## AWS AI & ML Scholars Program - Open to anyone aged 18 or older, with no prior AI or machine learning experience required. - Includes: - A foundational generative AI Challenge phase. - A fully funded three-month Udacity Nanodegree for the top 4,500 performers. - Applications close June 24, 2026. ## Serverless and Database Improvements - **Aurora PostgreSQL express configuration** enables serverless databases to be created and connected in seconds using preconfigured defaults. - **Aurora PostgreSQL is now part of the AWS Free Tier**, with eligible new customers receiving AWS credits. - The **Agent Plugin for AWS Serverless** adds skills, sub-agents, and Model Context Protocol servers to AI coding assistants such as Kiro, Claude Code, and Cursor. - It supports building, deploying, troubleshooting, and managing production-ready serverless applications. - The **Aurora DSQL Connector for Ruby** automatically generates authentication tokens for each connection while remaining compatible with the `pg` gem. ## SageMaker and AWS Console Updates - **SageMaker Studio** now supports remote connections from Kiro and Cursor, combining those IDEs’ coding workflows with SageMaker’s scalable compute. - The AWS Management Console now supports visual customization, including account colors and hiding unused regions or services to reduce interface clutter. ## Expanded Lambda Managed Instance Capacity - The file descriptor limit has increased from 1,024 to 4,096, supporting higher-concurrency and file-intensive workloads. - Functions can now use up to: - 32 GB of memory - 16 vCPUs - Users can select memory-to-vCPU ratios of 2:1, 4:1, or 8:1 for workloads such as data processing, media transcoding, and scientific simulations. ## Conversational Speech with Amazon Polly - Polly’s new Bidirectional Streaming API supports incremental text-to-speech generation. - Audio synthesis can begin before an LLM or other application has produced the complete response, making it better suited to conversational AI. ## Upcoming AWS Events - AWS Summits are free, in-person events covering cloud, AI, best practices, and networking. - Upcoming locations include Paris, London, Bengaluru, Singapore, Tel Aviv, and Stockholm. - AWS Community Days in San Francisco and Romania will feature community-led talks, workshops, and hands-on labs. AWS developers can follow the AWS News Blog and “What’s New with AWS” for additional announcements, while the AWS Builder Center and Events and Webinars pages provide opportunities for learning and community participation.

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AIDatabase DesignPostgreSQLAWS+4

aws·Mar 26, 2026·2 min readCurated summary

Customize your AWS Management Console experience with visual settings including account color, region and service visibility | Amazon Web Services

AWS has expanded User Experience Customization (UXC) to let administrators tailor the Management Console by account color, visible Regions, and visible services. These settings help teams distinguish accounts and reduce clutter by showing only relevant resources. They affect console appearance only and do not restrict access through the CLI, SDKs, APIs, or Amazon Q Developer. ## Account Color Customization - Administrators can assign a color to an AWS account through **Account display settings**. - The color appears in the console navigation bar to make account purpose easier to recognize. - Teams can use colors such as: - Orange for development - Light blue for testing - Red for production ## Region Visibility - Administrators can configure which AWS Regions appear in the console’s Region selector. - They can either show all available Regions or select a specific list. - After saving, only the chosen Regions appear in the navigation bar. - This reduces unnecessary scrolling and helps users focus on approved or relevant Regions. ## Service Visibility - Administrators can select which AWS services appear in the **All services** menu and console search results. - Services can be searched for or selected by category, such as Popular services. - Hidden services are removed from the console interface but remain accessible through programmatic tools. ## Programmatic Configuration - Account customization can be managed through the `AWS::UXC::AccountCustomization` CloudFormation resource. - The resource supports: - `AccountColor` - `VisibleServices` - `VisibleRegions` - Example configurations can expose services such as `s3`, `ec2`, and `lambda`, while limiting Regions to `us-east-1` and `us-west-2`. - Templates can be deployed with the AWS CLI using `aws cloudformation deploy`. AWS administrators can use these settings to create a clearer, more focused console experience without changing permissions or underlying account access.

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AWSAPICliCloudformation+3

aws·Mar 25, 2026·3 min readCurated summary

Announcing Amazon Aurora PostgreSQL serverless database creation in seconds | Amazon Web Services

Amazon’s new Aurora PostgreSQL express configuration lets developers create a serverless database in seconds with two console clicks or a single CLI/API call. It uses preconfigured defaults, IAM authentication, and an internet access gateway to simplify secure connections without requiring a VPC, VPN, or Direct Connect. The feature is designed to accelerate prototyping and application development while preserving Aurora capabilities such as read replicas and automated failover. ## Express Configuration for Aurora PostgreSQL - Creates an Aurora PostgreSQL serverless cluster and instance within seconds. - Uses preconfigured defaults to reduce setup complexity. - Allows customization of: - Cluster identifier - Serverless capacity range during creation - Read replicas and parameter groups after creation - Express-configured clusters do not require an Amazon VPC. - An internet access gateway is enabled by default for secure connections from development tools worldwide. - The gateway is distributed across multiple Availability Zones for high availability. - IAM authentication is configured for the administrator, enabling passwordless database authentication. ## Creating a Database - In the Aurora and RDS console: - Open the Dashboard. - Choose **Create** with the rocket icon. - Review or adjust the express configuration. - Choose **Create database**. - The AWS CLI and SDKs support the `--with-express-configuration` parameter. - A single `create-db-cluster` call creates both the cluster and its instance: ```bash aws rds create-db-cluster \ --db-cluster-identifier channy-express-db \ --engine aurora-postgresql \ --with-express-configuration ``` - The database becomes ready when its status changes to **Available**. ## Connecting to the Database The **Connectivity & security** tab provides several connection methods: - **Code snippets** - Generates connection examples for .NET, Go, JDBC, Node.js, PHP, PostgreSQL, Python, and TypeScript. - Python examples use `boto3` to generate an IAM authentication token and `psycopg2` to connect over SSL. - **AWS CloudShell** - Launches a shell with a preconfigured `psql` connection command. - Developers can immediately run SQL commands at the PostgreSQL prompt. - **Endpoints** - Supports tools such as pgAdmin that use username-and-password fields. - The password is an IAM authentication token valid for 15 minutes. - A new token must be generated if the connection ends or the token expires. ## Application Development Integrations - Aurora is now included among eligible AWS Free Tier database services. - AWS’s enhanced Free Tier offers up to $200 in credits: - $100 upon signup - Up to another $100 through usage of services such as RDS, Lambda, and Bedrock - Integrations with Vercel and v0 allow developers to create or connect to AWS databases quickly. - v0 can use natural-language prompts to generate full-stack applications backed by Aurora PostgreSQL, Aurora DSQL, or DynamoDB. - Existing Aurora databases created with express configuration can also be connected to Vercel. The express configuration is best suited for quickly starting development, experimentation, and prototypes. Developers can begin with minimal networking and authentication setup, then add capacity, replicas, and other Aurora features as their application grows.

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Database DesignPostgreSQLServerlessAws Cli+4

aws·Mar 23, 2026·3 min readCurated summary

AWS Weekly Roundup: NVIDIA Nemotron 3 Super on Amazon Bedrock, Nova Forge SDK, Amazon Corretto 26, and more (March 23, 2026) | Amazon Web Services

This week’s AWS roundup highlights major updates across generative AI, data analytics, Java, serverless, logging, and Kubernetes. Notable announcements include NVIDIA Nemotron 3 Super on Amazon Bedrock, the Nova Forge SDK for customizing models, faster Redshift queries, and expanded EKS scaling and availability guarantees. The roundup also points readers to community initiatives, developer resources, and upcoming AWS events. ## Generative AI and Developer Tools - **NVIDIA Nemotron 3 Super** is now available through Amazon Bedrock. - Supports text generation, reasoning, summarization, and code generation. - Can be invoked through Bedrock’s unified API without managing infrastructure. - **Nova Forge SDK** simplifies fine-tuning and customizing Amazon Nova models. - Enables domain-specific adaptations for enterprise use cases. - Handles much of the underlying customization and deployment complexity. - **Kiro for students** provides free access to AI-powered development tools. - **Strands Steering Hooks** reportedly achieved 100% agent accuracy, outperforming prompt engineering and rigid workflows for controlling agent behavior. ## Data, Java, and Serverless Updates - **Amazon Redshift** now delivers up to 7x faster execution for new, uncached queries in dashboards and ETL workloads. - The improvement is especially useful for workloads with high query variability. - **Amazon Corretto 26** is generally available. - Includes current Java features, performance improvements, and security updates. - Supports Amazon Linux, Windows, macOS, and Docker environments. - **AWS Lambda** now exposes Availability Zone metadata for function invocations. - Helps with observability, troubleshooting, latency analysis, and multi-AZ architecture decisions. - **CloudWatch Logs** supports log ingestion through an HTTP-based protocol, reducing the need for custom agents or SDK integrations. ## Amazon EKS Enhancements - Provisioned Control Plane clusters now receive a **99.99% SLA**, compared with 99.95% for the standard control plane. - A new **8XL scaling tier** doubles Kubernetes API server request-processing capacity compared with the 4XL tier. - The larger tier targets demanding workloads such as AI/ML training, HPC, and large-scale data processing. ## AWS Community and Events - **AWS Builder Center badges** recognize contributions, challenges, and community participation. - AWS promotes community-driven learning through the “Keep Building Together” initiative. - Upcoming events include AWS Summits in cities such as Paris, London, Bengaluru, Singapore, Tel Aviv, and Stockholm; AWS Community Days in San Francisco and Romania; and the AWSome Women Summit LATAM in Mexico City. Overall, the announcements emphasize AWS’s continued investment in enterprise AI customization, higher-performance infrastructure, improved observability, and developer communities. Teams should evaluate the new Bedrock, Redshift, Lambda, and EKS capabilities according to their workload scale, reliability, and customization needs.

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Database DesignKubernetesGenerative AIAmazon Bedrock+4