Amazon Products
All Amazon Release Notes
- Dec 20, 2025
- Parsed from source:Dec 20, 2025
- Detected by Releasebot:Dec 22, 2025
December 2025 Updates
Agent performance dashboard provides insights into evaluation scores, metrics like handle time, online time breakdown, and evaluations by evaluator across agent hierarchies.
Original source Report a problem - Dec 2, 2025
- Parsed from source:Dec 2, 2025
- Detected by Releasebot:Dec 2, 2025
Amazon Quick Suite Mobile is now available on iOS and Android
Amazon Quick Suite Mobile brings chat and dashboards to iOS and Android. The first version lets you ask questions from mobile, pull context from spaces and dashboards, and share photos or files to capture notes and summarize actions on the go.
Amazon Quick Suite Mobile is now available on iOS and Android
We are excited to share that we have the first version of the Quick Suite mobile app now available, bringing Quick Suite’s chat and dashboard capabilities on the go. Users can ask Quick Suite anything and get answers that pull from the context boundaries they already set up across spaces, Quick Actions, and dashboards. Whether you want to check a sales dashboard while heading into a meeting or ask Quick Suite to find insights from a document in a space, you can now do it on the go with the mobile app.
What’s new with Quick Suite Mobile?
Chat — Get answers from Quick Suite on the go
Users can now interact with Quick Suite from their mobile device and ask questions that draw from their existing spaces, Quick Actions, dashboards, and Quick Flows. Quick Suite understands the context, retrieves the right information, and helps users move work forward even when away from their desk. Users can also upload photos, use the camera, or share files directly from their phone — perfect for snapping a whiteboard, capturing meeting notes, or adding any visual content so Quick Suite can summarize action items and preserve context instantly.Dashboards — View and analyze data on the go
Everything users rely on from the existing Quick Sight mobile experience remains available. Users can view dashboards, drill into visuals, and stay connected to key business metrics anytime.
Download the app here
- iOS App
- Android App
- Dec 1, 2025
- Parsed from source:Dec 1, 2025
- Detected by Releasebot:Dec 9, 2025
Amazon Quick Suite integrates Quick Research with Quick Flows for report automation
Amazon Quick Suite adds Quick Research as a step in Quick Flows, letting teams auto-generate research reports within multi-step workflows. The integration triggers research on schedules, delivers source-traced insights, and feeds downstream actions in Salesforce, Jira, or Asana.
Amazon Quick Suite adds Quick Research to Quick Flows
Amazon Quick Suite now includes Quick Research as a step within Quick Flows. This integration enables teams to generate comprehensive research reports as part of automated, multi-step workflows, transforming research projects into reusable workflows that can be shared across their organization.
Quick Suite is Amazon's new AI-powered workspace that helps organizations get answers from their business data and move quickly from insights to action. With this integration, teams can trigger research automatically within their flows rather than conducting separate analysis. This addresses a critical productivity challenge by enabling teams to capture and scale proven research methods across hundreds of automated use cases. The integration also allows users to automate research workflows through scheduled triggers so users can set up flows that automatically generate research at specific times. Common use cases include automated account plan creation, standardizing product compliance analysis, and scheduled industry reports.
Users benefit from pre-configured flows that generate research based on flow creator instructions and optional user inputs. The generated research report can be used further to automatically trigger downstream actions like updating a Salesforce opportunity for an account team to follow up on, posting on a Jira ticket for a compliance team to review, or creating an Asana task for a patent lawyer to approve. This unlocks "set and forget" workflows that deliver consistent analysis without manual heavy lifting. Now operating within these automated workflows, Quick Research maintains its core strength of streamlining analysis across diverse enterprise data sources while delivering verified, source-traced insights. For existing Flow users, this provides access to more comprehensive analysis.
Quick Research with Flows integration is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more about automating your research needs, read the Quick Suite user guide.
Source
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/12/amazon-quick-suite-research-flows-report-automation
Original source Report a problem - Dec 1, 2025
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December 2025 Updates
Amazon Connect now lets business users real-time adjust queues, routing and customer experience without IT. Data tables and persona based workspaces enable fast, governed operations with role based actions.
Workspace and data table resources provide business users with greater control over daily operations
Amazon Connect now gives business users greater control over daily contact center operations without requiring technical resources. With new capabilities to adjust queues, routing behavior, and customer experience settings in real time, business users can respond to changing conditions immediately while maintaining enterprise-grade governance and security. Contact center administrators can start by defining key business configurations such as queue assignments, operating hours, skill mappings, and escalation rules, in data tables that directly drive contact flows. Guides can then be configured to surface role-specific actions for each business user within persona based workspaces. Together, these updates enable a business-led operating model that keeps contact center operations fast, consistent, and secure, all without relying on IT.
For more information, see Set up workspaces for your admin website users.
Original source Report a problem - December 2025
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- Detected by Releasebot:Dec 20, 2025
- Modified by Releasebot:Jan 2, 2026
Database Migration Service by Amazon
AWS Database Migration Service 3.5.1 release notes
AWS DMS 3.5.1 updates numeric handling for streaming targets like Kafka and Kinesis, where large numbers may format as INT64 or scientific notation, affecting downstream consumers. It also adds new target support and numerous reliability fixes.
Change in Handling of Large Numeric Values for Streaming Targets
In AWS DMS version 3.5.1, there is a change in how large integer and high-precision numeric values are handled when streaming data to targets like Kafka and Kinesis. Specifically, AWS DMS changed its internal data type representation, handling these values as INT64 instead of INT8. This shift can result in different data formats on the streaming endpoints, particularly when the values exceed the limits of INT8. Consequently, the representation of these numeric types may differ from their previous formatting when streamed to destinations like Kafka and Kinesis, potentially impacting downstream systems and processes that consume the data from these targets.
Summary of Change:
- In previous versions (e.g., 3.4.7/3.4.6), large integer values were represented as integers.
- Starting with version 3.5.1, these values may appear in scientific notation (e.g., 7.88129934789981E15), potentially leading to precision and formatting differences.
Affected Data Types
The recent change affects the representation of several numeric types when streamed to endpoints like Kafka and Kinesis. The impacted types are:
- Large integer types (e.g., bigint)
- Floating-point types (FLOAT, DOUBLE)
- High-precision decimal types (DECIMAL, NUMERIC)
Affected Scenarios:
- Full load migrations to streaming targets
- Change Data Capture (CDC) to streaming targets
This change specifically impacts streaming endpoints such as Kafka and Kinesis, while non-streaming targets remain unaffected.
To mitigate this change, you can implement a data type transformation that reverts to the previous formatting, representing large numbers as integers. However, it's important to note that this workaround may not be suitable for all scenarios, as it could potentially introduce limitations or compatibility issues.
Recommendations:
- Test your specific use case in a non-production environment before deploying AWS DMS version 3.5.1 or later to identify and address any impacts of this change.
- Affected customers can implement the change-data-type transformation workaround, if applicable, to revert to the previous formatting for large numbers as integers. However, this approach may not suit all scenarios.
We are reviewing this behavior to ensure consistent data type handling across endpoints in future releases.
The following table shows the new features and enhancements introduced in AWS Database Migration Service (AWS DMS) version 3.5.1
New feature or enhancement Description Support for PostgreSQL 15.x AWS DMS version 3.5.1 supports PostgreSQL version 15.x. For more information, see Using PostgreSQL as a source and Using PostgreSQL as a target. Support for Amazon DocumentDB Elastic Clusters with sharded collections AWS DMS version 3.5.1 supports Amazon DocumentDB Elastic Clusters with sharded collections. For more information, see Using Amazon DocumentDB as a target for AWS Database Migration Service. Amazon Redshift Serverless as a Target Support for using Amazon Amazon Redshift Serverless as a target endpoint. For more information, see Using an Amazon Redshift database as a target for AWS Database Migration Service. Babelfish Endpoint Settings Enhanced PostgreSQL target endpoint settings for providing Babelfish support. For more information, see Using a PostgreSQL database as a target for AWS Database Migration Service. Oracle Source Open Transactions AWS DMS 3.5.1 improves the methodology of handling open transactions when starting a CDC-Only task from the Start Position for an Oracle source. For more information, see OpenTransactionWindow in the Endpoint settings when using Oracle as a source for AWS DMS section. Amazon Timestream as a Target Support for using Amazon Timestream as a target endpoint. For more information, see Using Amazon Timestream as a target for AWS Database Migration Service.AWS DMS version 3.5.1 includes the following resolved issues:
- The representation of large numeric values on streaming targets has been updated. Review the 'Handling of Large Numeric Values in Streaming Targets' documentation for details on potential impacts.
- Fixed an issue for Oracle source where CDC-only tasks had continuously growing inactive sessions, resulting in the following exception: ORA-00020: maximum number of processes exceeded on the source database.
- Fixed an issue for DocumentDB as a target where UPDATE statements were not properly replicated in some scenarios.
- Improved error handling for the data validation feature to properly fail the task when data validation is disabled for validation-only tasks.
- Fixed an issue for Amazon Redshift target where the DMS task would not retry applying changes on the target when the target has ParallelApplyThreads set greater than zero after connection termination, which would result in data loss.
- Fixed an issue for MySQL to MySQL replication of mediumtext data types with full-LOB mode.
- Fixed an issue for DMS tasks with BatchApplyEnabled set to true where DMS would stop replicating data after Secrets Manager rotated the password.
- Fixed an issue for MongoDB / DocDB source where range segmentation would not work properly when the primary key column contained a large value.
- Fixed an issue for Amazon Redshift as a target, where DMS task crashes with BatchApplyEnabled set to true.
- Fixed an issue with Amazon Redshift as a target, where with parallel-load set to type=partitions-auto, parallel segments were writing bulk CSV files to the same table directory and interfering with each other.
- Fixed an issue with Amazon Redshift as a target, where during CDC the target column is of type boolean while the source is of type character varying.
- Fixed an issue for validation with PostgreSQL, where the validation fails when boolean data types are present.
- Fixed an issue for PostgreSQL as a source, so that the full load uses the ExecuteTimeout field in Extra connection attributes.
- Fixed an issue for PostgreSQL as a source, so that a task will fail if it's reading LSNs which are greater than the requested task resume LSN for more than 60 min to indicate that the is a problem with the replication slot being used.
- Fixed an issue for PostgreSQL as a source, where timestamptz before 1970-01-01 were not migrated correctly during CDC.
- Fixed an issue for PostgreSQL as a source, where DMS was truncating character varying datatype values during CDC.
- Fixed an issue for PostgreSQL as a source where resuming a previously stopped task replay misses one or more transactions during CDC.
- Fixed an issue for S3 as a target, where the resultant CSV file header is off by one column when AddColumnName is true and TimestampColumnName is "".
- Fixed an issue for S3 as a source, where a DMS task in full load was only releasing the used memory after the entire table was loaded to the target database.
- Fixed an issue for S3 as a target, where a table reload operation missed generating CDC files.
- Fixed an issue for MySQL as a source where an LOB lookup would fail when the ParallelApplyThreads task setting was set to a value greater than zero.
- Fixed an issue with SQL Server as a source where a task would fail with an illogical LSN sequencing state error error after upgrading from AWS DMS version 3.4.7 to version 3.5.1.
- Fixed an issue with PostgreSQL as a source where a task using the pglogical plugin would fail when the task was stopped, a table was removed from selection rules, the task was resumed, and changes were made to the removed table.
- Fixed an issue for Aurora MySQL as a source where an incorrect recovery checkpoint would be saved as a result of an Aurora failover or Aurora source stop and start.
- Fixed an issue for SQL Server as a source where a task would crash when SafeguardPolicy was set to RELY_ON_SQL_SERVER_REPLICATION_AGENT.
- Fixed an issue for MySQL as a target there where CDC replication would fail as a result of incorrect data type casting in the batch-apply phase.
- Fixed an issue for PostgreSQL as a source where a task would fail due to a DDL being treated as a DML when the CaptureDDLs endpoint setting was set to false.
- Fixed an issue for MongoDB as a source where the task would crash due to an empty collection.
- Fixed an issue for Amazon Redshift as a target where a task would crash during the full load phase when the recovery checkpoint control table was enabled.
- Fixed an issue for S3 to S3 replication where AWS DMS would not replicate the data if the bucketFolder was not specified.
- Fixed an issue for S3 as a target where excessive latency would occur when GlueCatalogGeneration was set to true.
- Fixed an issue with Oracle as a target where AWS DMS truncates data in VARCHAR2 columns.
- Fixed an issue for PostgreSQL as a source where the behavior of the '_' wildcard in the selection rules was not working as documented.
- Fixed an issue for PostgreSQL as a source where the task would fail due to an empty WAL header received from the replication slot.
- Fixed an issue for MySQL and MariaDB as sources where a proper error message was not emitted when AWS DMS detected BINLOG compression.
- Improved S3 data validation to handle special characters in primary and non-primary key columns.
- Fixed an issue for Amazon Redshift as a target where misleading entires were present in the task log reporting batch-apply statement failures on UPDATES and DELETES.
- Fixed an issue for SQL Server to S3 migrations where the task would crash while applying cached changes.
- Fixed an issue for the batch-apply feature where an error in applying a batch would result in missing data.
- Improved logging for SQL Server source to unclude the storage unit value. Enhanced logging for SQL Server source in AlwaysOn configuration to properly indicate missing permissions.
- Several loggin enhancements introduced to provide better visiblitiy and troubleshooting capalities for the Kafka target.
- Enhanced logging for Oracle source with binary reader to properly indicate tables being skipped due to missing primary keys.
- Enhanced logging for migrations with disabled DDL replication to indicate unexpected target table structure after its modified outside of AWS DMS.
- Enhanced logging to better explain paused source capture situation.
- Enhanced logging to indicate when AWS DMS is reading from internal swap files.
- Enhanced logging for Amazon Redshift target to include more detailed information in default logging level.
- Enhanced logging to report issues with table matadata under info logging level to simplify troublshooting.
- Enhanced the data validation feature for Amazon Redshift target to support HandleCollationDiff setting.
- Fixed an issue for data validation feature where the re-validation option was unavailable in certain situations.
- Fixed an issue where a reload of multiple tables was canceled when at least one of the table was invalid.
- Fixed an issue for MySQL source where the JSON data type was not being hadled propely with Batch Apply enabled.
- Fixed an issue for the column filtering feature where filters were not applied correctly to newly added columns during FL.
- Fixed an issue for Db2 LUW source where "table-type" option in selection rules was being ignored.
- Fixed an issue for data validation feature where filters were not respected while validating data.
- Fixed an issue for LOB migration where the AWS DMS task would crash while processing certain event types.
- Fixed an issue for Data Validation feature where the Validation-only task would hang on certain DDL events.
- Fixed an issue for data validation feature where the the HandleCollationDiff setting was not applied when filters were present.
- Fixed an issue for MySQL source where UTF-16 encoded enum values were not migrated correctly.
- Fixed an issue for SQL Server to PostgreSQL migration where data validaiton would report false positives in certain situations.
- Fixed an issue for Amazon Redshift target where the EmptyAsNull ECA would not work correctly.
- Fixed an issue where for targets using CSV files to load data AWS DMS task was showing a memory leak.
- Fixed an issue for Amazon S3 target where CdcMaxBatchInterval and CdcMinFileSize were not respected when cdcInsertAndUpdateOnly setting was enabled.
- Fixed an issue for MySQL target where corrupted column metadata could potentially cause AWS DMS task crash and/or data loss.
- Fixed an issue for data validation feature where the validation process would be terminated prematurely on any table supsension.
- Fixed an issue for Oracle target where AWS DMS task would crash with Batch Apply enabled.
- FIxed an issue for Amazon S3 target data validation where the taks would fail due to the Athena not storing the table names correctly.
- Fixed an issue for MongoDB and Amazon DocumentDB endpoints where the credentials could not be retrieved from Secret Manager which resulted in an error.
- Fixed an issue for Oracle data validation where validation of certain tables would never complete.
- Fixed an issue for data validation feature where validation of certain tables would hang due to insufficient memory allocation.
- Fixed an issue for Amazon S3 target where AWS DMS task would crash after receiving alter table DDL when GlueCatalogGeneration is enabled.
- Fixed an issue for data validation feature where validation would fail on NUL (0x00) characters.
- Fixed an issue for babelfish endpoint where tables names with mixed case would be suspended.
- Fixed an issue for Amazon Redshift target where data loss would occur when ParallelLoadThreads was >0 under certain conditions.
- Fixed an issue for Amazon S3 target data validation where validation would fail when there were no other columns than the PK in the table.
- Fixed an issue for data validation feature where the CloudWatch metrics would be missing for validation which took a short amount of time to complete.
- Fixed a memory leak issue for batch apply feature which would occur under certain conditions.
- Fixed an issue where AWS DMS task start woudl take a very long time and never complete.
- Fixed an issue for PostgreSQL source where data loss would occur due to unknown events in the replication slot.
- Fixed an issue for Amazon S3 target where failed LOB lookup would result in data loss.
- Nov 30, 2025
- Parsed from source:Nov 30, 2025
- Detected by Releasebot:Nov 30, 2025
Amazon Quick Research now includes trusted third-party industry intelligence
Amazon Quick Research expands with a partner ecosystem, adding third party data from S&P Global, FactSet and IDC, plus vast US Patent and PubMed data. The unified workspace now blends internal data, web search and external datasets to speed insight to action across finance, energy and more.
Quick Research partner ecosystem and data integrations
Amazon Quick Suite, the AI-powered workspace helping organizations get answers from their enterprise data and move swiftly from insights to action, enhances Quick Research with access to specialized third-party datasets.
Quick Research transforms how business professionals tackle complex business problems by completing weeks of data discovery, analysis, and insight generation in minutes. Today, Quick Research launches its partner ecosystem with industry intelligence providers S&P Global, FactSet, and IDC, with more to come. Users with existing subscriptions can combine these authoritative datasets with all of their business data and real-time web search, accelerating their path to deeper insights and strategic decision-making. Additionally, all users have access to decades of US Patent and Trademark Office data along with millions of PubMed citations and abstracts in biomedical and life sciences literature.
Business professionals from any industry can now access and analyze multiple data sources in one unified workspace, eliminating the need to switch between platforms. For example, a financial analyst can evaluate investment opportunities using FactSet’s financial data alongside real-time web search and internal market reports, while energy teams can optimize trading strategies using S&P Global’s commodity data combined with insights from their strategy teams. Similarly, sales and product teams can spot emerging trends faster by leveraging IDC’s industry intelligence with their customer data. By bringing critical data sources together in one place, organizations can move from insight to action with greater speed and confidence.
Quick Research’s third-party data integration regions
Quick Research’s third-party data integration is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more, read our User Guide.
This is a companion discussion topic for the original entry at Amazon Quick Research now includes trusted third-party industry intelligence - AWS
Original source Report a problem - Nov 30, 2025
- Parsed from source:Nov 30, 2025
- Detected by Releasebot:Nov 30, 2025
Amazon Quick Suite introduces scheduling for Quick Flows
Amazon Quick Flows gains scheduling to automate tasks with daily, weekly, monthly intervals across regions. Schedule any flow you have access to to run at set times, boosting efficiency and consistency with no extra charges. Learn more in docs.
Amazon Quick Flows now supports scheduling, enabling you to automate repetitive workflows without requiring manual intervention. You can now configure Quick Flows to run automatically at specified times or intervals, improving operational efficiency and ensuring critical tasks execute consistently.
You can schedule Quick Flows to run daily, weekly, monthly, or on custom intervals. This capability is great for automating routine and administrative tasks such as generating recurring reports from dashboards, summarizing open items assigned to you in external services, or generating daily meeting briefings before you head out to work.
You can schedule any flow you have access to whether you created it or it was shared with you. To schedule a flow, click the scheduling icon and configure your desired date, time, and frequency.
Scheduling in Quick Flows is available now in US East (N. Virginia), US West (Oregon), and Europe (Ireland) There are no additional charges for using scheduled execution beyond standard Quick Flows usage.
To learn more about configuring scheduled Quick Flows, please visit our documentation.
This is a companion discussion topic for the original entry at Amazon Quick Suite introduces scheduling for Quick Flows - AWS
Original source Report a problem - Nov 24, 2025
- Parsed from source:Nov 24, 2025
- Detected by Releasebot:Nov 25, 2025
AWS Weekly Roundup: How to join AWS re:Invent 2025, plus Kiro GA, and lots of launches (Nov 24, 2025)
AWS re:Invent week brings a wave of new AWS capabilities from EC2 and Bedrock to Lambda and S3, plus enhanced observability and security features. The headline is Kiro, the AI coding tool, now GA with four new capabilities to boost spec-driven development.
Next week, don’t miss AWS re:Invent, Dec. 1-5, 2025, for the latest AWS news, expert insights, and global cloud community connections! Our News Blog team is finalizing posts to introduce the most exciting launches from our service teams. If you’re joining us in person in Las Vegas, review the agenda, session catalog, and attendee guides before arriving. Can’t attend in person? Watch our Keynotes and Innovation Talks via livestream.
Kiro is now generally available
Last week, Kiro, the first AI coding tool built around spec-driven development, became generally available. This tool, which we pioneered to bring more clarity and structure to agentic workflows, has already been embraced by over 250,000 developers since its preview release. The GA launch introduces four new capabilities: property-based testing for spec correctness (which measures whether your code matches what you specified); a new way to checkpoint your progress on Kiro; a new Kiro CLI bringing agents to your terminal; and enterprise team plans with centralized management.
Last week’s launches
We’ve announced numerous new feature and service launches as we approach re:Invent week. Key launches include:
- Accelerate large-scale AI applications with the new Amazon EC2 P6-B300 instances
- Introducing flat-rate pricing plans with no overages for website delivery and security
- New Amazon Bedrock service tiers help you match AI workload performance with cost
- Monitor network performance and traffic across your EKS clusters with Container Network Observability
- New: AWS Billing Transfer for centrally managing AWS billing and costs across multiple organizations
- AWS Control Tower introduces a Controls Dedicated experience
- New business metadata features in Amazon SageMaker Catalog to improve discoverability across organizations
- Streamlined multi-tenant application development with tenant isolation mode in AWS Lambda
- Accelerate workflow development with enhanced local testing in AWS Step Functions
- Simplify access to external services using AWS IAM Outbound Identity Federation
- Introducing attribute-based access control for Amazon S3 general purpose buckets
- Introducing VPC encryption controls: Enforce encryption in transit within and across VPCs in a Region
- Build production-ready applications without infrastructure complexity using Amazon ECS Express Mode
- New one-click onboarding and notebooks with a built-in AI agent in Amazon SageMaker Unified Studio
- Simplified developer access to AWS with ‘aws login’
Here are some AWS bundled feature launches:
- Amazon EKS announces new Provisioned Control Plane, and fully managed MCP servers (preview) and enhanced AI-powered troubleshooting in the console with Amazon ECS.
- Amazon ECR introduces managed container image signing, archive storage class for rarely accessed container images, and AWS PrivateLink for FIPS Endpoints.
- Amazon Aurora DSQL provides an integrated query editor in the console, statement-level cost estimates in query plans, new Python, Node.js, and JDBC Connectors, up to 256 TiB of storage volume.
- Amazon API Gateway supports response streaming for REST APIs, developer portal capabilities, and additional TLS security policies for REST APIs.
- Amazon Connect provides conversational analytics for voice, persistent agent connections for faster call handling, and multi skill agent scheduling.
- Amazon CloudWatch introduces scheduled queries in Logs Insights and in-console agent management on EC2.
- AWS CloudFormation StackSets offers deployment ordering for auto-deployment mode. You can define the sequence in which your stack instances automatically deploy across accounts and Regions.
- AWS NAT Gateway supports Regional availability to create a single NAT Gateway that automatically expands and contracts across availability zones (AZs).
- Amazon Bedrock supports OpenAI GPT OSS models for Custom Model Import, coding use cases for Guardrails, and 10 additional languages for speech analytics for Data Automation.
- Amazon OpenSearch supports Cluster Insights for improved operational visibility, backup and restore, and audit logs for data plane APIs in Serverless through the console.
See AWS What’s New for more launch news that I haven’t covered here, and we’ll see you next week at re:Invent!
- Channy
- Nov 16, 2025
- Parsed from source:Nov 16, 2025
- Detected by Releasebot:Nov 4, 2025
- Modified by Releasebot:Nov 17, 2025
November 2025 Updates
Amazon Connect updates introduce conditional case field visibility and dependent options to streamline case handling, plus outbound campaigns with preview dialing and new analytics dashboards. You can tailor schedule adherence thresholds by team to fine tune agent performance.
Conditional case field visibility and dependent options
Amazon Connect Cases now supports conditional field visibility and dependent field options, so you can simplify case layouts and ensure agents capture the right information faster. For example, you can show a Return Reason field only when the case involves a return, and limit Issue Type choices to hardware-related options when Issue Category is set to Hardware.
For more information, see Add case field conditions to a case template in Amazon Connect.October 2025 Updates
Preview dialing mode for outbound campaigns
Outbound campaigns support preview dialing, allowing agents to review customer information before placing calls. Campaign managers can configure review time limits and enable contact removal. New analytics dashboards provide visibility into agent behavior and campaign performance.
For more information, see Set up Amazon Connect outbound campaigns.Configure thresholds for schedule adherence
You can configure thresholds for schedule adherence, giving you more flexibility in how you track agent performance. You can define thresholds for how early or late agents start or end their shifts, as well as for individual activities. For example, agents can start their shift 5 minutes early and end 10 minutes late, or end their breaks 3 minutes late, without negatively impacting their adherence scores.
Original source Report a problem
You can further customize these thresholds for individual teams. For example, teams that handle contacts with long ha... - Nov 15, 2025
- Parsed from source:Nov 15, 2025
- Detected by Releasebot:Nov 7, 2025
- Modified by Releasebot:Nov 16, 2025
November 2025 Updates
Amazon Connect delivers a broad update with conditional field visibility, granular permissions, AI powered email overviews, and richer outbound campaigns. It adds schedule adherence controls, enhanced analytics, new APIs, multi‑user calls, and parallel Lambda in flows.
Conditional case field visibility and dependent options
Amazon Connect Cases now supports conditional field visibility and dependent field options, so you can simplify case layouts and ensure agents capture the right information faster. For example, you can show a Return Reason field only when the case involves a return, and limit Issue Type choices to hardware-related options when Issue Category is set to Hardware.
For more information, see Add case field conditions to a case template in Amazon Connect.
October 2025 Updates
Preview dialing mode for outbound campaigns
Outbound campaigns support preview dialing, allowing agents to review customer information before placing calls. Campaign managers can configure review time limits and enable contact removal. New analytics dashboards provide visibility into agent behavior and campaign performance.
For more information, see Set up Amazon Connect outbound campaigns.Configure thresholds for schedule adherence
You can configure thresholds for schedule adherence, giving you more flexibility in how you track agent performance. You can define thresholds for how early or late agents start or end their shifts, as well as for individual activities. For example, agents can start their shift 5 minutes early and end 10 minutes late, or end their breaks 3 minutes late, without negatively impacting their adherence scores.
You can further customize these thresholds for individual teams. For example, teams that handle contacts with long handle times can be given more flexibility in when they start their breaks. This enables you to focus on true adherence violations and eliminates the impact of minor schedule deviations on agent performance.
For more information, see Schedule Adherence.Use granular permissions for conversation recordings and transcripts
You can use granular permissions to manage access to conversation recordings and transcripts in the Amazon Connect admin website. You can separately configure access to recordings and transcripts, allowing users to listen to calls while preventing unauthorized copying of transcripts. Amazon Connect provides flexible download controls, enabling users to download redacted recordings while restricting downloads of unredacted versions.
For more information, see List of security profile permissions.Set up agent schedule adherence notifications
You can set up agent schedule adherence notifications to make it easier for you to proactively identify when agents aren't adhering to their scheduled activities. You can define rules to automatically send email or text notifications (using EventBridge) to supervisors when agents exceed adherence thresholds. For example, if agent adherence drops below 85% in a trailing 15-minute window, supervisors can receive an email alert.
For more information, see Set up schedule adherence notifications.Search for related items across all cases within a domain
You can use the SearchAllRelatedItems API to search for related items across all cases within a domain. This is a global search operation that returns related items from multiple cases, unlike the case-specific SearchRelatedItems API.Generative AI-powered email conversation overviews and suggested responses
Amazon Connect provides agents with generative AI-powered email conversation overviews, suggested actions, and responses. This enables agents to handle emails more efficiently, so customers receive faster, more consistent support.
For example, a customer emails about a refund request. Amazon Connect Connect automatically provides key details about the customer's purchase history on the agent workspace, recommends a refund resolution step-by-step guide, and generates an email response to help resolve the contact quickly.
For more information, see Use generative AI-powered email conversation overviews and suggested responses. Also see the CreateSession API for updates to support this feature, updates to data types such as DataDetails, and new data types such as EmailGenerativeAnswerAIAgentConfiguration.Amazon Connect makes it easier to get customer input on outbound calls
Amazon Connect supports Get customer input and Store customer input flow blocks for outbound voice whisper flows. The Get customer input block allows a prompt to be played to a customer on an outbound call after they answer the call but before they are connected with an agent, and the customer’s response can be collected through either DTMF input or by using an Amazon Lex bot.
This capability allows you to capture interactive and dynamic customer input on outbound calls before these are connected to an agent. For example, you can use the Get customer input block to obtain customer consent for call recording as part of outbound calls placed by agents, and use it to trigger Amazon Connect Contact Lens recording and analytics.Agent time-off balance data in the Amazon Connect analytics data lake
Agent time-off balance data is available in the Amazon Connect analytics data lake, making it easier for you to generate reports and insights from this data. You access the latest and historical agent time-off balances across different time-off categories (paid time-off, sick leave, leave of absence, etc.) in the analytics data lake. You can also view a chronological list of all transactions that impacted the balance. For example, if an agent starts with 80 hours of paid time-off on January 1, submits a 20-hour request on January 3, and later cancels it, you can see each transaction's impact on the final 80-hour balance. This makes time-off management easier by eliminating the need for managers to manually reconcile balances and time-off transactions.
For more information, see Staff timeoff balance changes.Agent screen recording for ChromeOS devices
You can use screen recording for agents using ChromeOS devices. With screen recording, you can identify areas for agent coaching (for example, long contact handle duration or non-compliance with business processes) by not only listening to customer calls or reviewing chat transcripts, but also watching agent actions while handling a voice, chat, or task contact. Email is not supported.
For more information, see Amazon Connect Client Application.September 2025 Updates
Dashboards support filtering and comparing metrics by any time range
Amazon Connect dashboards support selecting and comparing any time ranges. This enables you to focus on specific, relevant data and perform in-depth analysis up to a maximum of 35 days in the last 3 months. Additionally, you can select Week to Date and Month to Date time ranges.
For example, if a new sales campaign launches at the start of the current week, a contact center manager can compare the current week's handle time or contact volume with the same time range last week using Week to Date, to decide if additional agents are required to handle the increasing contact volume and maintain service levels.
For more information, see Dashboards in Amazon Connect for getting contact center performance data.Added two APIs: AssociateContactWithUser and ListRoutingProfileManualAssignmentQueues
Use these APIs to programmatically assign queued contacts to available users and list the manual assignment queues associated with a routing profile:
AssociateContactWithUser and ListRoutingProfileManualAssignmentQueues.
These APIs support the functionality described in Access the Worklist app in the Amazon Connect agent workspace.Customize service level calculations
You can customize service level calculations to your specific needs by selecting if callbacks, abandons, or transfers are included in service level calculations. You can define time thresholds for when a contact is considered to meet service level standards and select which contact outcomes to include in the calculation.
For example, managers can choose to count callback contacts, exclude contacts transferred out while waiting in queue, and exclude short abandons using a configurable time threshold. This enables them to create a service level metric calculation that better aligns with their business operations.
For more information, see Create custom calculations of service level metrics.Amazon Connect Contact Lens sensitive data redaction in 7 additional languages
Amazon Connect Contact Lens provides sensitive data redaction from voice and chat conversational analytics in French (France, Canada), Portuguese (Portugal, Brazil), Italian, German, and Spanish (Spain).
For more information, see AI features.Flow designer analytics mode
You can use analytics in the drag-and-drop flows designer. This enables you to make data-driven decisions when optimizing your flows. You can view aggregate traffic through each completed and in-progress step in the flow, allowing you to identify behavioral patterns of your customers or pinpoint where errors are being encountered. For more information, see Monitor flow performance.New callback metrics
Added the following metric definitions:- Average queue abandon time - customer first callback
- Average queue answer time - customer first callback
- Average speed of answer - customer first callback dialed
- Average wait time after customer connection - customer first callback
- Callback attempts - customer first callback
- Contact volume - agent first callback
- Contact volume - customer first callback
- Contacts abandoned - customer first callback
- Contacts handled - customer first callback
Use contact segment attributes
For scenarios where information for a contact varies between transfers or multi-party conferences—such as business unit name, account type, or contact reason—you can use contact segment attributes. Contact segment attributes enable you to centrally manage the information with predetermined values and apply it to a unique contact record. This approach preserves accurate business context throughout customer journeys. It helps minimize data inconsistencies by enforcing standardized attribute values, and ensures reporting and analytics always reflect the true customer journey. For more information, see Contacts, contact chains, and contact attributes and Use contact segment attributes.New detailed disconnect reasons for improved call troubleshooting
Amazon Connect offers expanded disconnect reasons to help you better understand why outbound calls failed to connect in your contact center. These enhanced reasons are based on standard telecom error codes that provide deeper call insights and enable faster troubleshooting. For more information, see DisconnectReason under ContactTraceRecord.Use agent hierarchy filters to search for contacts
You can search for contacts by using agent hierarchy filters on the Contact search page in the Amazon Connect admin website. You can drill-down into your hierarchy to review contacts handled by specific contact center sites, departments or teams, for assessing contact quality or agent performance.
This functionality enables centralized teams within contact centers, such as quality management and regulatory compliance, to efficiently locate and review contacts handled by specific teams or departments. This streamlines their workflow for performance evaluation and compliance auditing. For more information see Search for completed and in-progress contacts in Amazon Connect.Manual work item assignment for agents
Agents can manually prioritize the next important task, email, or chat in a queue. For example, when a customer calls in to enquire about their previously submitted refund request, an agent can search for any pending tickets related to the case, assign it to themselves, and resolve it immediately.
Supervisors and managers can enable manual assignment by updating agent configuration in routing and security profiles. Agents can then use the new worklist application in their agent workspace to manually assign themselves the next important chat, task, or email. For more information, see Access the Worklist app in the Amazon Connect agent workspace.August 2025 Updates
Contact Lens with external voice expanded to additional AWS Regions
Contact Lens with external voice is now supported in Asia Pacific (Tokyo), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt), and Europe (London). For more information, see Integrate Amazon Connect Contact Lens with external voice systems and Contact Lens availability by Region.Multi-user web, in-app, and video calling
Amazon Connect supports multi-user web, in-app, and video calling, allowing multiple users to join the same session with an agent through a web browser or mobile application. Contact center customers and agents can dynamically add participants during a live call or multiple participants can join a scheduled session with the same agent. Participants can engage in audio, video, and screen sharing for a fully collaborative experience. For more information, see Enable multi-user in-app, web, and video calling.Recurring activities in agent schedules
Amazon Connect supports recurring activities in agent schedules, allowing you to add repeating events in a few clicks. You can schedule activities such as daily stand-up at 8 a.m. or team meeting every Monday at 9 a.m. as a series that automatically gets added to agent schedules. These can be scheduled as individual recurring series for each agent or a shared recurring series across multiple agents. For more information, see Forecasting, capacity planning, and scheduling in Amazon Connect.Amazon Connect communications widget supports task and email forms for websites and applications
Amazon Connect provides out-of-the-box embedding of tasks and emails into your websites and applications using the contact form option in the communications widget. You can add the communications widget to your website to enable customers to submit callback requests outside business hours or send emails through webforms.
The feature includes these capabilities:- Configure customer-facing forms using the drag and drop editor
- Generate code snippets for seamless website integration
- Provide customers with flexible engagement options
- Manage all engagements through existing Amazon Connect workflows
For more information, see Add the Amazon Connect widget to your website to accept chat, task, email, and web calling contacts.
Amazon Connect Outbound Campaigns supports multi-profile campaigns and enhanced phone number retry sequencing
Amazon Connect Outbound Campaigns supports account-based campaigns, enabling you to reach multiple people associated with the same account. For example, when calling about a joint bank account, if the first person is unavailable, the system automatically tries to reach other authorized members of the account.
The feature includes these enhancements:- Target multiple profiles within the same campaign for outreach to all associated contacts in an account
- Define prioritized contact sequences across multiple phone numbers (mobile, home, work)
- Configure fallback phone numbers within each profile
- Automatically progress to next preferred phone number after unsuccessful attempts
- Create more flexible engagement workflows to improve right-party contact rates
This feature is available in all AWS Regions where Amazon Connect Outbound Campaigns is supported. For more information, see Outbound Campaigns.
Use the GetContactMetrics API to retrieve real-time position in queue
You can use the GetContactMetrics API and the Position in queue metric to retrieve real-time position in queue data. (This functionality is not available in flows, only by using the API.) This enhancement provides contact centers with a way to manage customer wait times more effectively by:- Retrieving accurate queue position for each contact
- Offering proactive callbacks during long wait periods
- Making data-driven decisions between primary and alternative queues
- Monitoring queues with routing criteria and agent proficiencies
- Optimizing agent resource allocation through improved queue visibility
For more information, see the GetContactMetrics API documentation and the Position in queue metric definition.
July 2025 Updates
Enhancements to audio treatment while customers wait in queue
You can configure flows to execute logic such as routing priority changes while continuing to play audio to customers waiting in queue. For example, when a customer is in queue listening to music or instructions, you can periodically check metrics to determine whether to transfer them to a different queue or conditionally offer a callback, without having the check itself cause any interruption to the music. For more information, see the Loop prompts block.Enhanced third-party application support in agent workspace
The agent workspace supports new actions and workflows powered by third-party applications running in the background. This enhancement allows agents to perform various tasks without leaving the agent workspace, such as:- Completing new training prompts upon login
- Accessing company-specific phone directories during contact transfers
- Filling out forms in pop-up windows
- Downloading files
Agents can seamlessly resume their work exactly where they left off after helping a customer. This single-pane-of-glass experience improves agent productivity and enhances customer satisfaction.
Third-party applications are available in the following AWS Regions: US East (N. Virginia), US-West (Oregon), Africa (Cape town), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London).
For more information, see Access third-party applications in the Amazon Connect agent workspace in the Amazon Connect Administrator Guide and the Amazon Connect Agent Workspace Developer Guide.
Apply Automatic fail to a section or the entire evaluation form
You can configure an evaluation form so answering 0 to a specific question assigns a score of 0 to the section, the subsection, or the entire evaluation form. Previously this option assigned a score of 0 to the entire form. For more information, see Step 5: Assign scores and ranges to answers in Create an evaluation form in Amazon Connect.Per-day pricing for external voice connectors
Amazon Connect external voice connectors are now priced at $100 per connector per day. The new daily rate provides customers with more granular billing options. For the per-day rate is effective July 24, 2025, for new and existing connectors. For more information, see Set up Amazon Connect external voice transfer to an on-premise voice system.Direct signing of calls from US numbers to North American Numbering Plan (NANP) destinations
All calls from US numbers (toll-free or direct-inward-dial) are marked and signed with STIR/SHAKEN attestation headers and attestation levels provided by Amazon Connect through AMCS LLC. Previously, these calls were marked and signed with headers and attestation levels determined by our carrier partners. For more information, see Stir/Shaken attestation in Amazon Connect.Forecast editing user interface
You can select a forecast and then make edits—such as increasing contact volume by a percentage or setting exact values—across specific date ranges, queues, and channels. You can preview and apply changes within the forecasting user interface. For example, if a there's an upcoming marketing campaign expected to drive higher traffic, you can increase the short-term forecast by 15% for Tuesdays and Wednesdays between 12 PM and 2 PM for the next two weeks. With this feature, you can simplify the process of managing forecast changes, improve planning accuracy, and respond faster to demand fluctuations. For more information, see Edit a forecast in Amazon Connect.New disconnect reason: CUSTOMER_NEVER_ARRIVED
Added the disconnect reason CUSTOMER_NEVER_ARRIVED to the contact record. For more information, see ContactTraceRecord.Analytics dashboard in agent workspace
The agent workspace includes an out-of-box analytics dashboard that provides agents with insights into their individual performance metrics and queue status. Agents can view their performance metrics, such as contacts handled and average handle time. They can also view metrics about their assigned queue, such as contacts in queue and longest wait time.
These insights help agents improve their performance and make data-driven decisions to enhance customer experience. For example, agents can better time their breaks by monitoring queue volumes.
For more information, see Access the performance dashboard directly in the agent workspace.
In addition, there's a new widget on the Queue and agent performance dashboard: Agent status drill down. And there's a new metric: Agents on contact.Parallel AWS Lambda execution in flows
Original source Report a problem
You can set up the parallel execution of AWS Lambda functions in flows, enabling faster and more seamless customer experiences. You can integrate with third-party or homegrown systems such as CRMs by using Lambda to automate tasks like reading or updating customer records. You can now execute multiple Lambda functions concurrently or continue progressing the flow and run additional actions while a Lambda runs. For example, in an automated customer interaction, you can now look up a customer's past purchases while simultaneously checking for active promotions and playing a message about a new offer.
You can configure these capabilities directly in the drag-and-drop flow designer using the AWS Lambda function and Wait flow blocks, or through public APIs.
Note
The name of the Invoke Lambda function block has been changed to AWS Lambda function to indicate this increased functionality.
