AWS

Amazon DynamoDB global tables with multi-Region strong consistency now supports 15 regions, adding Canada Central, Stockholm, Spain, Mumbai, and Singapore. Users can configure tables across any three supported regions using either three replicas or a two-replica plus one-witness setup. This expansion enables zero RPO availability for applications spanning North America, Europe, and Asia Pacific.

• New regions: Canada Central, Europe Stockholm/Spain, Asia Mumbai/Singapore
• Total supported regions for MRSC now stands at 15
• Configurations support 3 replicas or 2 replicas + 1 witness
• Enables zero RPO for cross-continent high-availability apps
• Allows routing to geographically closer DynamoDB endpoints

AWS EMR now offers Long Term Support (LTS) releases, beginning with emr-spark-8.1.0, providing 36 months of maintenance for critical security and bug fixes. This allows teams to stabilize production workloads on a single release version for three years without extra cost. The update also integrates full support for Apache Iceberg v3, enabling advanced features like geospatial handling and schema evolution.

• LTS releases get 36 months of critical and high-severity fix support
• Stabilize Spark workloads on one version for three years at no cost
• Full Apache Iceberg v3 support including geospatial and schema evolution
• Spark SQL can now reference catalogs by name across accounts and S3

AWS Security Hub AI Inventory now discovers and catalogs AI assets on self-hosted Microsoft Azure instances. This update extends existing self-hosted discovery capabilities beyond AWS to provide a centralized view of AI assets and their security posture across multi-cloud environments. The service utilizes enhanced Amazon Inspector SBOM analysis to identify inference endpoints, models, and AI agents like Ollama, vLLM, and Hugging Face TGI on Azure virtual machines. Each found asset is mapped to its infrastructure and correlated with security findings for filtering.

• Security Hub AI Inventory now supports Azure self-hosted instances for centralized AI asset discovery.
• Amazon Inspector SBOM analysis identifies inference endpoints, models, and agents on Azure VMs.
• Supports frameworks including Ollama, vLLM, and Hugging Face TGI.
• Assets are mapped to infrastructure and correlated with security findings for filtering.