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 minutes at cutover. The same week, Amazon DynamoDB started loading data from S3 into tables that already exist. The pattern I like is that neither one asks you to stop what’s running.
That’s also the way to read the agent news this week. The new Amazon Bedrock AgentCore Runtime is a single field on the runtime you already have, and Web Answer is a tool you attach to a gateway you already run. Now, let’s get into this week’s AWS news… Headlines The new AgentCore Runtime: elastic, optimized, and consistently fast starts – If you run agents on AgentCore and haven’t tried the new runtime since it became generally available, it’s worth a look.
It changes two things. First, memory: sessions start small, page in more on demand, and give memory back when it goes cold instead of holding the peak, so you pay for what your agent uses. Second, cold starts: AgentCore prepares your environment once, snapshots it, and restores the snapshot for every new instance.
In the team’s tests, that kept P75 cold starts at about 2 seconds for images from 200 MB up to 2 GB, while the original runtime rose from roughly 5. 4 seconds to nearly 30 seconds as images grew. The per-unit rate is higher, but you use far fewer GB-hours, so the team expects most agents to see a lower bill, though that isn’t guaranteed.
To opt in, you set platformVersion to V2 when you create or update a runtime. Create and update take several minutes while the snapshot is prepared, and your container must report healthy on /ping within 120 seconds, so report health only after initialization finishes. The docs cover how to optimize your agent for V2 .
V2 is available in 10 Regions , and committed baseline pricing is coming soon. Amazon S3 Tables now offer managed migration of Apache Hive tables to Apache Iceberg – You can now migrate Parquet tables registered in the AWS Glue Data Catalog into S3 Tables without building a pipeline or provisioning compute. S3 Tables validates the source and produces a compatibility report covering every object in scope.
Each sync copies only what changed, so production keeps writing until cutover. Afterward you can query the table with Amazon Athena , Amazon SageMaker Unified Studio , or any engine that speaks the Iceberg REST API. You pay only for the data copied, with no charge for the conversion, and objects in S3 Intelligent-Tiering keep their tier.
At launch it works within the same account and Region, in 10 Regions. Last week’s launches Here are some launches and updates from this past week that caught my attention: Amazon DynamoDB now supports bulk put items – You can now load line-delimited DynamoDB JSON or Amazon Ion files from Amazon S3 into existing tables as a managed, asynchronous job. Each record can carry its own condition expression, so one file can mix plain, insert-only, and version-guarded writes.
Writes use dedicated system capacity and cost less than the equivalent per-request writes. An Accelerated tier handles deadline-bound jobs. The Database blog post gives illustrative Accelerated times of less than 1 hour for 100 million 1 KB items.
One thing to know before you start: canceling doesn’t roll back items already written. Announcing Web Answer on Amazon Bedrock AgentCore – You can now give an agent a single tool call that returns a synthesized, cited answer to a natural-language question, instead of building your own search, retrieval, and citation pipeline. Web Answer plans its own searches, runs several in parallel, and decides when it has enough evidence.
You attach it as a target on AgentCore Gateway and call it over MCP, and you can limit it with domain include and deny lists and publish-date filters. It’s available in US East (N. Virginia).
The getting started post explains when to use it instead of Web Search, which returns ranked results for your own model to synthesize. AWS Lambda now supports queues for Apache Kafka in self-managed Kafka event sources – You can now process records from a single Kafka partition across many parallel AWS Lambda invocations. Classic consumer groups cap parallelism at the partition count.
Queue mode uses Kafka share groups and needs Kafka 4. 2 or later with share groups enabled. It works with self-managed clusters and managed offerings such as Confluent Cloud.
You give up ordering and get at-least-once delivery, so your functions need to be idempotent. The Compute blog walkthrough covers poller scaling and when to keep stream mode. AWS announces AWS Interconnect – last mile preview with Equinix – You can now set up a private, managed connection from Equinix’s network of 282 data centers to AWS without ordering cross-connects or configuring routers.
Capacity is quad-redundant across two locations and four links, with BGP and VLANs configured for you, a 99. 99% availability SLA, and MACsec by default. You pick a Region, bandwidth, and AWS Direct Connect gateway, then paste the activation key into Equinix Fabric.
The preview covers the San Jose metro and, as of last Thursday , Northern Virginia, with 1 Gbps connections at no charge. AWS Security Hub now provides an SBOM inventory for your compute resources – You can now see every software package installed across your organization’s Amazon EC2 instances, Amazon ECR images, and Lambda functions in AWS Security Hub , with each package’s version and how many resources run it.
That’s the list you want the next time a widely used library has a vulnerability. The inventory builds on the SBOMs that Amazon Inspector already generates, so it fills in automatically wherever Inspector is enabled. It’s included in Security Hub Essentials at no additional cost.
Originally published at aws.amazon.com
