AWS

Amazon Bedrock has expanded its built-in Web Search tool to include an external_web_access parameter, enabling models to retrieve content directly from the public internet. This feature allows applications to ground responses in the most current data, such as live sports scores, while still operating within the AWS environment. To activate this capability, users must grant the bedrock-websearch:ExternalWebAccess IAM permission and ensure the parameter remains at its default true value.

• Enable live public web retrieval by granting the bedrock-websearch:ExternalWebAccess IAM permission.
• Set the external_web_access parameter to true (default) to fetch fresh content from the internet.
• Ideal for use cases requiring real-time data like live scores or breaking news updates.

Amazon Bedrock AgentCore's Web Search feature now supports runtime filtering by domain and published date. Agents can specify inclusive time windows and include or exclude specific domains per request. This allows for precise control over source trustworthiness and content recency without needing administrative reconfiguration.

• Apply per-request domain filtering to restrict or block specific web sources dynamically.
• Constrain search results to specific time windows using inclusive from/to date bounds.
• Improve response relevance and trust by controlling source domains at runtime.
• No admin reconfiguration required to implement these granular search constraints.

AWS Cost Anomaly Detection has expanded to cover spending on third-party foundation models hosted via Amazon Bedrock, including Anthropic Claude. The service automatically evaluates these costs without additional setup, integrating them into existing AWS managed service monitors. Users receive alerts and root-cause breakdowns when spend on these models deviates from expected patterns.

• Covers third-party models like Anthropic Claude on Bedrock automatically
• No new setup required; integrates with existing Cost Anomaly Detection
• Provides root-cause breakdowns ranked by dollar impact
• Extends ML-based anomaly detection to generative AI workload spend

Amazon Bedrock now offers OpenAI's GPT-5.6 Terra and Luna models in the India geography. This update enables cross-Region inference across Mumbai and Hyderabad while strictly keeping data within India for residency compliance. New inference profiles allow automatic routing to meet demand without manual capacity management.

• OpenAI GPT-5.6 (Terra/Luna) models are now available via Bedrock in India.
• Data residency is maintained by routing inference only within the India geography.
• Cross-Region inference spans Mumbai and Hyderabad for higher throughput.
• Use in.openai.gpt-5.6-terra and in.openai.gpt-5.6-luna profiles for compliance.

AWS has extended Lambda MicroVMs availability to Asia Pacific (Mumbai, Singapore, Sydney) and Europe (Frankfurt, Stockholm), bringing the total to 10 regions. This serverless primitive offers VM-level isolation with near-instant launch speeds and state preservation for user or AI-generated code. It allows developers to provision isolated compute environments without managing underlying virtualization infrastructure.

• Lambda MicroVMs now covers 10 global regions including Mumbai, Singapore, Sydney, Frankfurt, and Stockholm.
• Provides VM-level isolation with near-instant launch and resume capabilities for serverless workloads.
• Supports stateful execution, enabling persistent environments for interactive apps and AI assistants.
• Eliminates infrastructure management overhead while maintaining strong security boundaries per user or job.

Amazon Quick now defaults to denying new AI capabilities in custom permission profiles, shifting governance from reactive to proactive. Administrators must explicitly allow each AI feature rather than discovering it after release. This setting restricts both new and existing capabilities within the targeted category and applies only to the configured profile.

• Shift from reactive to proactive governance by blocking new AI features by default.
• Administrators must explicitly allow each AI capability before users can access it.
• Restrictions apply to the specific profile and cover both new and existing features.
• Configure settings via Amazon Quick management console or AWS CLI.