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AWS Weekly Roundup: AgentCore Runtime V2, Amazon DynamoDB bulk put items, and more (November 9, 2026)

Summary

  • Amazon S3 Tables now enable migration of Hive tables to Apache Iceberg in three steps without stopping production writes, supporting Athena, SageMaker Unified Studio, and Iceberg REST API engines.
  • Amazon DynamoDB supports bulk loading of line-delimited JSON or Amazon Ion files from S3 into existing tables via managed asynchronous jobs with dedicated system capacity.
  • Amazon Bedrock AgentCore Runtime V2 offers elastic memory usage and reduced cold starts by snapshotting environments, available in 10 Regions with a platformVersion setting of V2.
  • Web Answer is a new Bedrock AgentCore tool that synthesizes cited answers via parallel searches, attachable to AgentCore Gateway with domain and date filters.
  • AWS Lambda supports queues for self-managed Apache Kafka event sources to process records from a single partition across multiple parallel invocations using Kafka share groups.
  • AWS Interconnect provides a last-mile preview with Equinix for private managed connections from 282 data centers to AWS, featuring quad-redundant capacity and MACsec encryption.
  • AWS Security Hub now includes an SBOM inventory for EC2 instances, ECR images, and Lambda functions showing package versions and resource counts at no additional cost.
  • AWS contributed a binary log optimization to community MySQL that reduces commit latency for large transactions by spilling files instead of copying them.
  • OrderServ achieved 64% cost savings by migrating from one ECS cluster per brand to a multi-tenant ECS setup on EC2 Auto Scaling groups with warm pools.
  • AWS re:Invent is scheduled for November 30 to December 4 in Las Vegas with an open event catalog and reserved seating.
  • Upcoming AWS Community Days include events in Belém, Brazil on November 14, JAWS FESTA 2026 in Akita, Japan on November 17, and Port Harcourt, Nigeria on December 12.

Most of the cost of adopting something new isn’t the new thing, it’s the move. Moving a Hive table to Apache Iceberg has typically meant weeks of engineering work. Last week, Amazon S3 Tables turned that into three steps: start, sync as often as you need, complete. The source stays writable except for a few […]

Keywords
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