Amazon Release Notes
Last updated: Jan 10, 2026
Amazon Products
All Amazon Release Notes (77)
- Feb 11, 2026
- Date parsed from source:Feb 11, 2026
- First seen by Releasebot:Jan 10, 2026
- Modified by Releasebot:Feb 11, 2026
February 2026 Updates
Amazon Connect rolls out major updates: larger multi‑line field support, per‑channel auto‑accept and ACW timeouts, Audio Enhancement for crisper agent audio, and CSV uploads for cascading Case field options. Migration from UpdateUserPhoneConfig to UpdateUserConfig completes the changes.
Audio Enhancement for agents
Amazon Connect now offers Audio Enhancement to improve audio quality on the agent's side by reducing background noise and isolating the agent's voice during calls. Administrators can enable noise suppression or voice isolation modes for agents through user management settings. Agents with the appropriate security profile permissions can also adjust their own Audio Enhancement settings during work sessions.
For more information, see Enable Audio Enhancement.
Amazon Connect Cases now supports CSV upload for dependent field options
Amazon Connect Cases now enables you to bulk configure cascading dropdown menus for case fields by uploading CSV files containing field option mappings. This capability significantly reduces manual configuration time for complex hierarchical data structures such as geographic hierarchies (Country → State → City) or product categorizations (Category → Subcategory). You can include multiple field pairs in a single CSV file.
For more information, see CSV upload for dependent field options.
Amazon Connect Cases now supports larger, multi-line text fields with up to 4,100 characters. Administrators can use the Admin UI to select the appropriate configuration (single-line or multi-line) on a per-field basis, improving case documentation capabilities.
Amazon Connect now enables per-channel auto-accept and after contact work timeout settings for chat, tasks, emails, and callbacks to optimize how agents spend their time. Previously, these settings were available only for inbound voice contacts. To learn more, see Configure agent settings.
Please note that if you currently integrate with the UpdateUserPhoneConfig API, we recommend you migrate to the newly released UpdateUserConfig API instead. Per-channel auto-accept and ACW timeouts can only be updated via UpdateUserConfig API.
Original source Report a problem - Jan 26, 2026
- Date parsed from source:Jan 26, 2026
- First seen by Releasebot:Jan 27, 2026
AWS Weekly Roundup: Amazon EC2 G7e instances, Amazon Corretto updates, and more (January 26, 2026)
AWS headlines a wave of product updates with NVIDIA Blackwell powered GPU instances, including G7e GA for faster AI inference, and enhancements across ECR, CloudWatch Insights regions, and Connect Step-by-Step Guides. Corretto quarterly security updates also released.
Hey! It’s my first post for 2026, and I’m writing to you while watching our driveway getting dug out. I hope wherever you are you are safe and warm and your data is still flowing!
This week brings exciting news for customers running GPU-intensive workloads, with the launch of our newest graphics and AI inference instances powered by NVIDIA’s latest Blackwell architecture. Along with several service enhancements and regional expansions, this week’s updates continue to expand the capabilities available to AWS customers.
Last week’s launches
I thought these projects, blog posts, and news items were also interesting:- Amazon EC2 G7e instances are now generally available — The new G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs deliver up to 2.3 times better inference performance compared to G6e instances. With two times the GPU memory and support for up to 8 GPUs providing 768 GB of total GPU memory, these instances enable running medium-sized models of up to 70B parameters with FP8 precision on a single GPU. G7e instances are ideal for generative AI inference, spatial computing, and scientific computing workloads. Available now in US East (N. Virginia) and US East (Ohio).
- Amazon Corretto January 2026 Quarterly Updates — AWS released quarterly security and critical updates for Amazon Corretto Long-Term Supported (LTS) versions of OpenJDK. Corretto 25.0.2, 21.0.10, 17.0.18, 11.0.30, and 8u482 are now available, ensuring Java developers have access to the latest security patches and performance improvements.
- Amazon ECR now supports cross-repository layer sharing — Amazon Elastic Container Registry now enables you to share common image layers across repositories through blob mounting. This feature helps you achieve faster image pushes by reusing existing layers and reduce storage costs by storing common layers once and referencing them across repositories.
- Amazon CloudWatch Database Insights expands to four additional regions — CloudWatch Database Insights on-demand analysis is now available in Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific (Thailand), and Mexico (Central). This feature uses machine learning to help identify performance bottlenecks and provides specific remediation advice.
- Amazon Connect adds conditional logic and real-time updates to Step-by-Step Guides — Amazon Connect Step-by-Step Guides now enables managers to build dynamic guided experiences that adapt based on user interactions. Managers can configure conditional user interfaces with dropdown menus that show or hide fields, change default values, or adjust required fields based on prior inputs. The feature also supports automatic data refresh from Connect resources, ensuring agents always work with current information.
Upcoming AWS events
Keep a look out and be sure to sign up for these upcoming events:- Best of AWS re:Invent (January 28-29, Virtual) — Join us for this free virtual event bringing you the most impactful announcements and top sessions from AWS re:Invent. AWS VP and Chief Evangelist Jeff Barr will share highlights during the opening session. Sessions run January 28 at 9:00 AM PT for AMER, and January 29 at 9:00 AM SGT for APJ and 9:00 AM CET for EMEA. Register to access curated technical learning, strategic insights from AWS leaders, and live Q&A with AWS experts.
- AWS Community Day Ahmedabad (February 28, 2026, Ahmedabad, India) — The 11th edition of this community-driven AWS conference brings together cloud professionals, developers, architects, and students for expert-led technical sessions, real-world use cases, tech expo booths with live demos, and networking opportunities. This free event includes breakfast, lunch, and exclusive swag.
Join the AWS Builder Center to learn, build, and connect with builders in the AWS community. Browse for upcoming in-person and virtual developer-focused events in your area.
That’s all for this week. Check back next Monday for another Weekly Roundup!
~ micah
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- Jan 20, 2026
- Date parsed from source:Jan 20, 2026
- First seen by Releasebot:Jan 21, 2026
Amazon Quick Suite launches expanded size, faster ingestion, and richer data type support for SPICE datasets
Amazon Quick Suite expands SPICE with bigger scale, faster ingestion, and broader data types for AI workloads. Datasets now support up to 2TB, 64K Unicode strings, and timestamps from year 0001 to 1400 in Enterprise Editions. Faster loads and richer analytics—details in docs.
Amazon Quick Suite SPICE engine enhancements
Amazon Quick Suite SPICE engine is now supporting higher scale, faster ingestion, and broader data types to power advanced analytics and AI-driven workloads. With this launch, customers can load up to 2TB of data per dataset, doubling the previous 1TB limit, when using the new data preparation experience. Despite the increased dataset size, SPICE continues to deliver strong performance, with ingestion further optimized to enable even faster data loading and refresh to reduce time to insight. We’ve also expanded SPICE’s data type support by increasing string length limits from 2K to 64K Unicode characters and extending the supported timestamp range from year 1400 back to year 0001. As Quick Suite customers bring richer, more complex, and increasingly AI-driven workloads into SPICE, these enhancements enable broader data coverage, faster data onboarding, and more powerful analytics, without compromising performance. To learn more, visit our documentation.
The new SPICE dataset size limitation is now available in Amazon Quick Sight Enterprise Editions across all supported Amazon Quick Sight regions.
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2026/01/amazon-quick-suite-launches-expanded-spice
Original source Report a problem - Jan 14, 2026
- Date parsed from source:Jan 14, 2026
- First seen by Releasebot:Jan 14, 2026
Amazon Quick Suite browser extension now supports Quick Flows
Amazon Quick Suite browser extension now supports Quick Flows, letting you run workflows directly in your browser by passing page content to prebuilt or shared flows. Available in multiple regions with no extra charges; install from Chrome, Firefox, or Edge stores.
Amazon Quick Suite browser extension now supports Quick Flows
Amazon Quick Suite browser extension now supports Amazon Quick Flows, enabling you to run workflows directly within your web browser, eliminating the need to manually extract information from each web page. You can invoke workflows that you’ve created or that have been shared with you, and pass web page content as input—all without leaving your browser.
This capability is great for completing routine tasks such as analyzing contract documents to extract key terms, or generating weekly reports from project dashboards that automatically notify stakeholders.
Quick Flows in browser extension is available now in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). There are no additional charges for using the browser extension beyond standard Quick Flows usage.
To get started, visit your Chrome, Firefox, or Edge store page to install browser extension and sign in with your Quick Suite account. Once you sign in, look for the Flows icon below the chat box to invoke your flows. To learn more about invoking Quick Flows in browser extension, please visit our documentation.
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Amazon Web Services, Inc.
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Discover more about what's new at AWS with Amazon Quick Suite browser extension now supports Quick Flows - Jan 14, 2026
- Date parsed from source:Jan 14, 2026
- First seen by Releasebot:Jan 14, 2026
Amazon Quick Suite now supports memory for chat agents
Amazon Quick Suite adds memory for chat agents to remember user preferences across chats, enabling personalized, context-aware responses. Users can view, edit, or delete memories and even run in Private Mode to keep conversations private. Availability currently US East and US West.
Memory for chat agents in Amazon Quick Suite
We are announcing memory for chat agents in Amazon Quick Suite – a feature that allows users to get personalized responses based on their previous conversations. With this feature, Quick Suite remembers the preferences users specify in chat and generate responses that are tailored to them. Users can also view their inferred preferences and remove any memory they don’t want Quick chat agents to use.
Previously, chat users needed to repeat their preferences around response format, acronyms, dashboards, and integrations in every conversation. They also had to clarify ambiguous topics and entities in chat, increasing the tedious back and forth needed to get accurate and insightful responses. Memory addresses this pain point by remembering facts and details about users in a way that ensures responses provided to users continuously learn and improve. Users also control what Quick Suite remembers about them – all the memories are viewable and removable by users, and users have the choice to start chat in Private Mode in which conversations are not used to infer memories.
Memory in Quick Suite chat agents is available in US East (N. Virginia) and US West (Oregon). To learn more, visit the Amazon Quick Suite User Guide.
Original source: Amazon Quick Suite now supports memory for chat agents - AWS
Original source Report a problem - January 2026
- No date parsed from source.
- First seen by Releasebot:Jan 7, 2026
Database Migration Service by Amazon
AWS Database Migration Service 3.4.4 release notes
AWS DMS 3.4.4 introduces TLS and Kafka target auth with MSK, plus broad reliability tweaks across Oracle, PostgreSQL, S3, MongoDB, DocumentDB, and more. Expect improved logging, CDC resilience, and richer datatype handling for multiple sources and targets.
Features and enhancements
The following table shows the new features and enhancements introduced in AWS DMS version 3.4.4.
- AWS DMS now supports TLS encryption and TLS or SASL authentication using Amazon MSK and on-premises Kafka cluster as a target. For more information on using encryption and authentication for Kafka endpoints, see Connecting to Kafka using Transport Layer Security (TLS).
Issues resolved in AWS DMS 3.4.4
The issues resolved in AWS DMS 3.4.4 include the following:
- Improved AWS DMS logging on task failures when using Oracle endpoints.
- Improved AWS DMS task execution continues processing when Oracle source endpoints switch roles after Oracle Data Guard fail over.
- Improved error handling treats ORA—12561 as a recoverable error when using Oracle endpoints.
- Fixed an issue where EMPTY_BLOB() and EMPTY_CLOB() columns are migrated as null when using Oracle as a source.
- Fixed an issue where AWS DMS tasks fail to update records after add column DDL changes when using SQL Server as a source.
- Improved PostgreSQL as a source migration by supporting the TIMESTAMP WITH TIME ZONE data type.
- Fixed an issue where the afterConnectScript setting does not work during a full load when using PostgreSQL as a target.
- Introduced a new mapUnboundedNumericAsString setting to better handle the NUMERIC date type without precision and scale when using PostgreSQL endpoints.
- Fixed an issue where AWS DMS tasks fail with “0 rows affected” after stopping and resuming the task when using PostgreSQL as a source.
- Fixed an issue where AWS DMS fails to migrate the TIMESTAMP data type with the BC suffix when using PostgreSQL as a source.
- Fixed an issue where AWS DMS fails to migrate the TIMESTAMP value “±infinity” when using PostgreSQL as a source.
- Fixed an issue where empty strings are treated as NULL when using S3 as a source with the csvNullValue setting set to other values.
- Improved the timestampColumnName extra connection attribute in a full load with CDC to be sortable during CDC when using S3 as a target.
- Improved the handling of binary data types in hex format such as BYTE, BINARY, and BLOB when using S3 as a source.
- Fixed an issue where deleted records are migrated with special characters when using S3 as a target.
- Fixed an issue to handle empty key values when using Amazon DocumentDB (with MongoDB compatibility) as a target.
- Fixed an issue where AWS DMS fails to replicate NumberDecimal or Decimal128 columns when using MongoDB or Amazon DocumentDB (with MongoDB compatibility) as a source.
- Fixed an issue to allow CDC tasks to retry when there is a fail over on MongoDB or Amazon DocumentDB (with MongoDB compatibility) as a source.
- Added an option to remove the hexadecimal “0x” prefix to RAW data type values when using Kinesis, Kafka, or OpenSearch as a target.
- Fixed an issue where validation fails on fixed length character columns when using Db2 LUW as a source.
- Fixed an issue where validation fails when only the source data type or the target data type is FLOAT or DOUBLE.
- Fixed an issue where validation fails on NULL characters when using Oracle as a source.
- Fixed an issue where validation fails on XML columns when using Oracle as a source.
- Fixed an issue where AWS DMS tasks crash when there are nullable columns in composite keys using MySQL as a source.
- Fixed an issue where AWS DMS fails to validate both UNIQUEIDENTIFIER columns from SQL Server source endpoints and UUID columns from PostgreSQL target endpoints.
- Fixed an issue where a CDC task does not use an updated source table definition after it is modified.
- Improved AWS DMS fail over to treat task failures caused by an invalid user name or password as recoverable errors.
- Fixed an issue where AWS DMS tasks fail because of missing LSNs when using RDS for SQL Server as a source.
- Jan 1, 2026
- Date parsed from source:Jan 1, 2026
- First seen by Releasebot:Jan 21, 2026
Amazon Quick Sight expands dashboard customization in tables and pivot tables
Amazon QuickSight now lets readers customize dashboards directly by adding/removing fields, changing aggregations, and tweaking formatting without author updates. This boosts flexibility for sales and finance analyses and is available now in Enterprise Edition across supported regions.
Building on our recent launch of customizable tables and pivot tables, Amazon Quick Sight now enables readers to add or remove fields, change aggregations, and modify formatting directly in dashboards—all without requiring updates from dashboard authors.
These enhanced capabilities empower readers with even greater flexibility to tailor their data views for specific analytical needs. For example, sales managers can add revenue breakdowns by product category to identify growth opportunities, while finance teams can change aggregations from sum to average to better understand spending patterns across departments.
These new customization features are now available in Amazon Quick Sight Enterprise Edition across all supported Amazon Quick Sight regions. To get started with these new customization features, see our blog post.
Original source Report a problem - Jan 1, 2026
- Date parsed from source:Jan 1, 2026
- First seen by Releasebot:Nov 7, 2025
- Modified by Releasebot:Feb 9, 2026
January 2026 Updates
Amazon Connect rolls out wait time estimates, task file attachments, tag-based access controls, easy case linking with flows, a recurring hours calendar, CloudFormation support, and live agent screen recording status. Rich data, automation, and security upgrades boost coaching and efficiency.
Amazon Connect Launches Wait Time Estimates to Improve Customer Experience
Amazon Connect now delivers improved estimated wait time metrics for queues and enqueued contacts, empowering organizations to enhance customer satisfaction. This allows contact centers to set accurate customer expectations, provide convenient options such as callbacks when hold times are extended, and balance workloads effectively across multiple queues. By leveraging the estimated wait time metric, contact centers can make strategic routing choices across queues while gaining enhanced visibility for better resource planning. For example, a customer calling about billing during peak hours with a 15-minute wait is seamlessly transferred to a cross-trained team with 2-minute availability, getting help faster without repeating their issue. The metric works seamlessly with routing criteria and agent proficiency configurations.
This feature is available in all AWS regions where Amazon Connect is offered. To learn more about estimated wait time see the Amazon Connect Administrator Guide. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.
Amazon Connect now supports file attachments for tasks via StartTaskContact API
Amazon Connect now enables you to include file attachments when creating tasks using the StartTaskContact API. You can attach up to 5 files per task in various formats such as .pdf, .docx, .csv, .txt, .png, .jpg, .mp4, and more. This capability allows you to provide agents with relevant documents, images, or other files directly within the task context, streamlining workflows and improving agent efficiency.
Amazon Connect now supports tag-based access controls for cases
Amazon Connect now enables you to use tag-based access controls to define who can access specific cases. You can associate tags with case templates and configure security profiles to determine which users can access cases with those tags. For example, you can restrict access to fraud-related cases so that only agents in the fraud department can view or edit them.
Amazon Connect now simplifies linking related contacts to cases using flows
Amazon Connect now makes it easier to link related contacts such as email replies, call transfers, persistent chats, and queued callbacks to the same case so agents can view the complete customer journey and resolve issues faster. You can use flows to search for a case associated with a prior contact in the chain to follow-up contacts more easily.
In addition, you can now use flows to link a related contact to a case. For example, when you create a case via a Step-by-Step Guide, you can link that case to the main contact (e.g., voice, chat, email, or tasks) directly using flows.
Recurring overrides and visual calendar for hours of operation
Amazon Connect now makes it easier to manage contact center operating hours for recurring events like holidays, maintenance windows, and promotional periods, with a visual calendar that provides at-a-glance visibility by day, month, or year. You can set up recurring overrides that automatically take effect weekly, monthly, or every other Friday, and use them to provide customers with personalized experiences, all without having to manually revisit configurations. For example, every January 1st you can automatically greet customers with "Happy New Year!" and route them to a special holiday message before checking if agents are available, then on January 2nd your contact center automatically returns to normal operations.
For more information, see Set overrides for extended, reduced, and holiday hours.
Cases now supports AWS CloudFormation
Amazon Connect Cases now supports AWS CloudFormation, enabling you to model, provision, and manage case resources as infrastructure as code. With this launch, administrators can create CloudFormation templates to programmatically deploy and update their Cases configuration—such as templates, fields, and layouts—across Amazon Connect instances, reducing manual setup time and minimizing configuration errors.
For more information, see documentation.
Agent screen recording status tracking
Amazon Connect now offers customers the ability to view status of agent screen recordings in near real time in CloudWatch using Amazon EventBridge. With screen recording, supervisors can identify areas for agent coaching (e.g., non-compliance with business processes) by not only listening to customer calls or reviewing chat transcripts, but also watching agents' actions while handling a contact (i.e., a voice call, chat and task). Using Amazon EventBridge, customers can see status of each agent screen recording including success/failure, failure codes with description, installed client version, agent web browser version, agent operating system, screen recording start and end times from CloudWatch.
Customers can start using Amazon Connect screen recording status tracking by subscribing to Screen Recording Status Changed event type in Amazon EventBridge event bus.
For more information, see Set up and review agent screen recordings in Amazon Connect Contact Lens.
Store nested JSON object and looping arrays
Amazon Connect now enables you to store and work with complex data structures in your flows, making it easy to build dynamic automated experiences that use rich information returned from your internal business systems. You can save complete data records, including nested JSON objects and lists, and reference specific elements within them, such as a particular order from a list of orders returned in JSON format.
Additionally, you can automatically loop through lists of items in your customer service flows, moving through each entry in sequence while tracking the current position in the loop. This allows you to easily access item-level details and present relevant information to end-customers. For example, a travel agency can retrieve all of a customer's itineraries in a single request and guide the caller through each booking to review or update their reservations. A bank can similarly walk customers through recent transactions one by one using data retrieved securely from its systems. These capabilities reduce the need for repeated calls to your business systems, simplify workflow design, and make it easier to deliver advanced automated experiences that adapt as your business requirements evolve.
For more information, see Flows in Amazon Connect.
Original source Report a problem - December 2025
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- First seen by Releasebot:Dec 20, 2025
- Modified by Releasebot:Jan 29, 2026
Database Migration Service by Amazon
AWS Database Migration Service 3.5.1 release notes
AWS DMS 3.5.1 updates streaming numeric handling for targets like Kafka and Kinesis, may display large numbers in scientific notation due to INT64 backing. The release also adds PostgreSQL 15, DocumentDB Elastic Clusters, Redshift Serverless, Babelfish support, and extensive bug 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.
Mitigation
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.
New features and enhancements in AWS DMS v3.5.1
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. Support for using Amazon Amazon Redshift Serverless as a target endpoint 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. Enhanced PostgreSQL target endpoint settings for providing Babelfish support 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. 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. 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 data validation feature where the validation would fail with a syntax error on Oracle versions prior to 12.2.
- Fixed an issue for PostgreSQL to PostgreSQL migrations where timestamp with time zone data was not migrated properly with Batch apply enabled during CDC.
- Fixed an issue with Oracle to PostgreSQL migrations where data validation was failing for the NUMERIC(38,30) data type.
- Fixed an issue with Oracle source where extended varchar data type was being truncated.
- Fixed an issue for the filtering feature where CDC replication was failing.
- Enhanced the functionality of Kafka endpoints by adding the option to disable hostname validation of the certificate authority (SslEndpointIdentificationAlgorithm).
- Fixed an issue where Db2 LUW source date, timestamp, and time data types were not handled properly during data validation.
- Fixed an issue with PostgreSQL source where the AWS DMS task was failing to restart and could not consume relational events when using the pglogical plugin.
- Fixed an issue for SQL Server source where validation of HIERARCHY data type would fail.
- Fixed an issue for SQL Server soruce where strings with control characters were not replicated correctly.
- Fixed an issue with Amazon Redshift target where testing the endpoint would fail when using Secrets Manager.
- Fixed an issue with MySQL target where the ParallelLoadThreads setting was not properly retained after task settings changes.
- Fixed an issue with PostgreSQL to Oracle migrations where the task would fail when replicating from data type TEXT to data type VARCHAR2(2000).
- Fixed an issue with Oracle to PostgreSQL migrations where data validation reported false positives when NULL characters were replicated as SPACE characters.
- Fixed an issue with SQL Server source in AlwaysOn confuguration where the AWS DMS task would fail when the replica name didn't match the actual server name exactly.
- Fixed an issue with Oracle source where the AWS DMS endpoint connection test would fail due to insufficient priveleges while retrieving the Oracle session ID (SID).
- Fixed an issue with CDC-only tasks where tables created on the source after the task was started were not replicated in some cases.
- Improved the methodology of handling open transactions when starting a CDC-Only task from the Start Position for an Oracle source.
- Fixed an issue of missing data when resuming a task if it was stopped after cached changes were applied (StopTaskCachedChangesApplied option set to true). This issue could occur rarely if AWS DMS persists cached changes to the AWS DMS replication instance disk due to a high volume of changes on the source.
- Fixed an issue for PostgreSQL to Oracle data validation where validation was failing for extended data types.
- Fixed an issue for SQL Server to PostgreSQL data validation where validation was failing when character encoding was inconsistent between source and target.
- Fixed an issue where an ORA-01455 error occurs during validation when a PostgreSQL integer maps to an Oracle number(10).
- Fixed an issue for SQL Server to SQL Server data replication where migrating identity columns fails when the target column had the IDENTITY property.
- Fixed an issue for MySQL to MySQL replication where AWS DMS changes the character set to UTF16 when migrating an ALTER statement during CDC.
- Added support for the spatial datatype when migrating from PostgreSQL to Amazon Redshift.
- Fixed an issue where AWS DMS fails to generate .parquet files with GZIP compression with S3 as a target.
- Fixed an issue where AWS DMS doesn't migrate some of the partitions from a MongoDB source.
- Fixed an issue for Amazon Redshift as a target, where DMS task crashes with BatchApplyEnabled set to true.
- Fixed an issue for 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.
- Improved the task log to identify a DDL change that fails to replicate to Amazon Redshift as a target.
- 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 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 where a task crashes using a specific update statement with Parallel Apply in Amazon Kinesis.
- Fixed an issue where a task crashes on the ALTER TABLE statement with Amazon S3 as a target.
- Fixed an issue where values on polygon columns are truncated when using Microsoft SQL Server as a source.
- Fixed an issue on Unicode converter of JA16SJISTILDE and JA16EUCTILDE when using Oracle as a source.
- Fixed an issue where MEDIUMTEXT and LONGTEXT columns failed to migrate from MySQL to S3 comma-separated value (CSV) format.
- Fixed an issue where boolean columns were transformed to incorrect types with Apache Parquet output.
- Fixed an issue with extended varchar columns in Oracle.
- Fixed an issue where data validation tasks failed due to certain timestamp combinations.
- Fixed an issue with Sybase data definition language (DDL) replication.
- Fixed an issue involving an Oracle Real Application Clusters (RAC) source crashing with Oracle Binary Reader.
- Fixed an issue with validation for Oracle targets with schema names' case.
- Fixed an issue with validation of IBM Db2 versions 9.7 and 10.
- Fixed an issue for a task not stopping two times with StopTaskCachedChangesApplied and StopTaskCachedChangesNotApplied enabled.
- Dec 20, 2025
- Date parsed from source:Dec 20, 2025
- First seen 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.
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