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AWS Updates - 2026-03-10

AWS What's New

Amazon Connect introduces AI-powered manager assistance (Preview)

Today, Amazon Connect announces the preview of an AI-powered assistant that enables contact center managers to get instant answers to operational questions using natural language. You can query across 150+ Amazon Connect metrics, including agent scheduling, self-service experience, and performance evaluations, with historical data for all of these, and receive results in seconds—eliminating hours of manual data gathering. The assistant can also diagnose underlying issues, such as identifying which queues are at risk of missing service level targets and recommending specific recovery actions.

This feature is available as a preview. To request access, contact your AWS account team or an AWS Representative. To learn more about Amazon Connect, the AWS cloud-based contact center, visit the Amazon Connect website.

Amazon Connect now supports conversational analytics for email

Amazon Connect now supports conversational analytics for email contacts, enabling contact center managers to automatically categorize emails, redact personally identifiable information (PII), and generate contact summaries. This allows you to quickly identify emerging trends, better maintain compliance by protecting sensitive information, and reduce the time spent reviewing agent performance. For example, when customers email about account issues, Amazon Connect automatically categorizes the email, redacts sensitive information, and generates a summary for supervisor review.

To enable this feature, add the Set recording, analytics and processing behavior block to your flows before an email contact is assigned to your agent or sent to your end customer. You can customize which PII types to redact, choose whether redacted content shows specific PII type indicators e.g., [SSN] or generic markings ([PII]), opt to store both original and redacted versions in separate storage, as well as enable contact summaries. Using these analytics, you can quickly create rules to automatically trigger actions such as assigning categories, creating tasks, or updating cases.

Amazon Connect conversational analytics is available in the US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London) regions. To learn more and get started, please refer to the help documentation or visit the Amazon Connect website.

Amazon OpenSearch Service now supports in-place volume increases for all volume sizes

Amazon OpenSearch Service now extends in-place cluster volume size increases to volumes exceeding 3 TiB. With this enhancement, you can scale storage capacity across all volume sizes without requiring a blue/green deployment.

Previously, you could perform volume increases up to 3 TiB on your clusters without a blue/green deployment. This release removes that limitation, making it easier for you to scale up quickly even beyond 3 TiB when required. Domains that already have a volume size above 3 TiB will require a blue/green deployment the first time a volume increase is made; subsequent volume increases will not require a blue/green deployment.

Decreasing storage volume size, or making volume increases within short intervals, will still require a blue/green deployment. You can use the dry-run option to check whether your change requires a blue/green deployment.

This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon OpenSearch Service is available. See here for a full list of our Regions. To learn more about Amazon OpenSearch Service configurations, visit the documentation page.

Amazon Connect enhances AI-powered predictive insights

Today, Amazon Connect is announcing enhancements to AI-powered predictive insights that make it easier for businesses to deliver proactive, personalized customer experiences at scale. Building on the five recommendation algorithms launched at re:Invent 2025, AI-powered predictive insights now support up to 40 million product catalog items (8X increase), are available in message templates for trigger-based campaigns, and deliver up to 14% improved model accuracy. These enhancements enable businesses to automatically engage customers with the right message at the right time, while reducing the time required to deploy AI-powered personalization.

Businesses can now deliver trigger-based campaigns to initiate personalized outreach based on customer behavior and predictive signals – such as sending product recommendations when a customer abandons their cart or offering complementary services after a purchase. Businesses can now deliver targeted campaigns for specific customer cohorts based on predicted preferences and behaviors. Improved model accuracy and reduced training time mean businesses can deploy personalized experiences faster with greater confidence in the recommendations provided to customers.

With Amazon Connect Customer Profiles, you only pay-as-you-go for utilized profiles. Public preview for AI-powered predictive insights enhancements is available in Europe (Frankfurt), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Tokyo), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central).

To learn more, visit our webpages for Customer Profiles and explore the AI-powered predictive insights documentation.

AWS Builder ID now supports Sign in with GitHub and Amazon

AWS Builder ID, your profile for accessing AWS applications including AWS Builder Center, AWS Training and Certification and Kiro, now supports two new social logins: GitHub and Amazon. This expansion of sign-in options builds on the existing Google Apple social sign-in capabilities, providing GitHub and Amazon users with a streamlined way to access AWS resources without managing separate credentials on AWS.

With Sign in with Github and Amazon integration, developers and builders can now enjoy access to their AWS Builder ID profile using their GitHub or Amazon Account credentials. This enhancement eliminates password management complexity, reduces forgotten password issues, and provides a frictionless experience for both new user registration and returning user sign-ins. Whether you're accessing development resources in AWS Builder Center, enrolling in certification programs or using Kiro to code your next app, your GitHub and Amazon Accounts can now serve as a secure gateway to your builder AWS journey.

To learn more about AWS Builder ID and get started with Sign in with GitHub and Amazon, visit the AWS Builder ID documentation.

Amazon Bedrock AgentCore Runtime now supports stateful MCP server features

Amazon Bedrock AgentCore Runtime now supports stateful Model Context Protocol (MCP) server features, enabling developers to build MCP servers that leverage elicitation, sampling, and progress notifications alongside existing support for resources, prompts, and tools. These capabilities allow MCP servers deployed to AgentCore Runtime to collect user input interactively during tool execution, request LLM-generated content from clients, and provide real-time progress updates for long-running operations.

With stateful MCP sessions, each user session runs in a dedicated microVM with isolated resources, and the server maintains session context across multiple interactions using an Mcp-Session-Id header. Elicitation enables server-initiated, multi-turn conversations to gather information such as user preferences. Sampling allows servers to request AI-powered text generation from the client for tasks like personalized recommendations. Progress notifications keep clients informed during operations such as searching for flights or processing bookings. These features work together to support complex, interactive agent workflows that go beyond simple request-response patterns.

Stateful MCP server features are supported in AgentCore Runtime across fourteen AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Canada (Central), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Stockholm).

To learn more, see Stateful MCP server features in the Amazon Bedrock AgentCore documentation.

Amazon Bedrock now supports observability of First Token Latency and Quota Consumption

Amazon Bedrock is a fully managed service for building generative AI applications using high-performing foundation models from leading AI providers. It now supports two new CloudWatch metrics, TimeToFirstToken and EstimatedTPMQuotaUsage, giving you deeper visibility into inference performance and quota consumption.

TimeToFirstToken measures the latency from when a request is sent to when the first token is received, for streaming APIs (ConverseStream and InvokeModelWithResponseStream). You can use this metric to set CloudWatch alarms which monitor latency degradation and establish SLA baselines, without any client-side instrumentation. EstimatedTPMQuotaUsage tracks your estimated Tokens Per Minute (TPM) quota consumption, including cache write tokens and output burndown multipliers, across all inference APIs (Converse, InvokeModel, ConverseStream, and InvokeModelWithResponseStream). You can use this metric to set proactive alarms before reaching your quota limit, track your quota consumption across your models, and request further quota increases before usage is rate limited.

Both metrics are supported in all commercial Bedrock regions for models available via cross-region inference profiles and in-region inference, updated every minute for successfully completed requests. These are available in your CloudWatch out of the box; you pay only for the underlying model inference you consume, with no API changes or opt-in required.

To learn more about TimeToFirstToken and EstimatedTPMQuotaUsage, see our documentation page on Monitoring Amazon Bedrock.

AWS Security Blog

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