AWS

The AWS MCP Server is now live in Singapore, Sydney, Tokyo, Ireland, London, and Oregon. This managed Model Context Protocol server allows AI coding agents to discover and call AWS APIs through a single interface. The expansion enables teams to route requests to local endpoints, reducing latency and ensuring data stays within specific geographic boundaries.

• New regions: Singapore, Sydney, Tokyo, Ireland, London, and Oregon.
• Lower latency for AI coding agents by using local endpoints.
• Simplifies agent integrations with a single AWS API interface.
• Helps meet data residency requirements by keeping data in-region.
• Part of the Agent Toolkit for AWS.

Amazon Aurora Serverless has been updated to scale in larger increments, adding up to 16 ACUs within a single second. This enhancement allows the database to reach peak capacity of 256 ACUs much faster, addressing the unpredictable and bursty traffic patterns typical of agentic AI applications. The feature is enabled by default on platform versions 3 and 4, while users on older versions can upgrade to platform version 4 to benefit.

• Scales up to 16 ACUs per second, reducing latency for sudden traffic spikes.
• Optimized for agentic AI workloads with bursty activity and long idle windows.
• Enabled by default on Aurora Serverless platform versions 3 and 4.
• Existing clusters on versions 1 and 2 must upgrade to platform version 4.
• Automatically scales down to zero capacity when idle to minimize costs.

Amazon Aurora and RDS have added support for R8a instances driven by fifth-generation AMD EPYC processors. These instances map one vCPU to a physical core for consistent per-core performance and utilize sixth-generation Nitro Cards via the AWS Nitro System. They offer up to 75 Gbps of network bandwidth and 60 Gbps of EBS bandwidth, targeting high I/O workloads across PostgreSQL, MySQL, and MariaDB engines.

• R8a instances use 5th gen AMD EPYC with 1:1 vCPU-to-core mapping for predictable per-core performance.
• High I/O workloads benefit from 75 Gbps network and 60 Gbps EBS bandwidth on Nitro-based hardware.
• Supported engines include Aurora PostgreSQL, Aurora MySQL, RDS PostgreSQL, MySQL, and MariaDB.
• Availability is currently limited to select regions including US East, US West, Canada, and Asia Pacific.

Fleet impact: For Aurora PostgreSQL/MySQL and RDS fleets, R8a instances offer a viable alternative for I/O-bound workloads requiring consistent per-core latency. Evaluate migration to R8a if current instance families show CPU contention or insufficient EBS throughput, and verify regional availability before updating launch configurations.

AWS has introduced a preview of the Well-Architected Agent, an AI-driven evolution of Trusted Advisor and the Well-Architected Tool. It correlates metrics and application topology against best practices while analyzing Terraform, CDK, and CloudFormation templates. The service delivers prioritized recommendations aligned with business goals and offers automation-ready fixes.

• Replaces legacy Trusted Advisor and Well-Architected Tool with an AI agent.
• Analyzes Terraform, CDK, and CloudFormation for automation-ready fixes.
• Prioritizes recommendations based on business impact and effort.
• Correlates metrics with topology to optimize cost, security, and reliability.

AWS Glue Data Catalog now natively supports Apache Iceberg Version 3 tables, enabling automatic maintenance and performance tuning. Users can apply binpack, sort, or z-order compaction strategies to improve query speed and reduce storage costs by removing expired snapshots. The update also introduces NDV statistics for better query planning and crawlers for automatic table discovery in S3.

• Supports Iceberg V3 data types like variant, geospatial, and nanosecond timestamps.
• Enables z-order, sort, and binpack optimization strategies for V3 tables.
• Generates NDV statistics to help analytics engines plan queries more efficiently.
• Glue crawlers can now discover and register V3 tables stored in Amazon S3.

AWS has introduced system-managed materialized views for Apache Iceberg, restricting write access exclusively to AWS Glue. This prevents users with S3 or catalog permissions from altering precomputed query results, ensuring data integrity. The feature automatically computes and refreshes views based on defined schedules while storing them as standard Iceberg tables.

• Only AWS Glue can write to these materialized views, blocking external modifications.
• Precomputed query results remain immutable despite user permissions on S3 or the catalog.
• Define views via SQL with optional refresh schedules for automated maintenance.
• Stored as standard Apache Iceberg tables in Amazon S3 for engine compatibility.