Governed reports with Amazon Quick Desktop and Amazon FSx for NetApp ONTAP
1mo
- Published
- Collected
Build a governed weekly reporting workflow with Amazon Quick Desktop and Amazon FSx for NetApp ONTAP. An Amazon S3 access point exposes an approved folder to a Quick knowledge base, and a custom skill drafts cited weekly reports and Slack summaries with human review before anything is shared.
Amazon Quick Desktop brings governed, AI-assisted reporting to the files your team already manages on Amazon FSx for NetApp ONTAP (FSx for ONTAP), cutting weekly report preparation from hours to minutes. Today, producing those reports takes hours of manual effort each week. Teams re-read the same documents, reformat metrics, and copy summaries into Slack. Leaders need those updates quickly, but they also need to trust the source behind each metric, risk, and recommendation. In this post, you…
overfeed.news indexes and links. We publish a short excerpt — the full article stays at AWS Machine Learning Blog.
More from AWS Machine Learning Blog
Log in to follow this source
ICYMI: What landed for AI builders in September 2026
A monthly recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026: broader model choice, faster serverless agents with built-in evaluation, and automated knowledge base syncing with native enterprise connectors.
How Postman runs Agent Mode for 40 million developers on Amazon Bedrock
Building an AI agent that works in a demo is a different problem from running one for 40 million developers. Postman and AWS share the architectural patterns behind Agent Mode: controlling tool sprawl, exposing schema-based reads, and treating context as the real bottleneck, plus how it runs on Amazon Bedrock at scale.
Pay-per-inference for AI agents: How BlockRun and Incarna use Amazon Bedrock AgentCore payments
Amazon Bedrock AgentCore payments gives AI agents a managed way to pay for services on demand, with spending limits enforced by the infrastructure. See how Incarna's agents pay BlockRun for model inference one request at a time over x402, cutting the work of adding x402 payment support from months to days.
Share GPU clusters across teams with isolation and fairness using Amazon SageMaker HyperPod
A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernetes namespaces for isolation, HyperPod Task Governance for fairness, and namespace-level cost allocation for chargeback.