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.
What happened
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.
Where the sources line up
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….
Practical impact for readers
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.
Who should pay attention now
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.
What is still unclear
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 Cata 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.
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