Amazon Managed Grafana now supports in-place upgrade to Grafana version 12.4

Amazon Managed Grafana now supports in-place upgrade from Grafana version 10.4 to 12.4. You can upgrade with just a few clicks from the AWS Console or via AWS SDK or AWS CLI.
Upgrading to version 12.4 brings native Grafana Scenes-powered dashboards for faster rendering and queryless Drilldown apps for point-and-click exploration of Prometheus metrics, Loki logs, Tempo traces, and Pyroscope profiles. Amazon CloudWatch plugin enhancements simplify log analysis with PPL/SQL query support, broaden visibility through cross-account Metrics Insights, and surface issues proactively with log anomaly detection. The rebuilt table visualization delivers smoother performance with CSS cell styling and interactive Actions buttons, while trendline transformations and navigation bookmarks streamline data exploration. 
In-place upgrade to Grafana 12.4 is supported in all AWS regions where Amazon Managed Grafana is generally available.  For a complete list of new features, refer to Differences between Grafana versions in the Amazon Managed Grafana User Guide. For upgrade instructions, see Update your workspace version.  To learn more about Amazon Managed Grafana features and its pricing, visit the product page and pricing page.
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Amazon RDS for PostgreSQL announces Extended Support minor versions 11.22-rds.20260224, 12.22-rds.20260224, and 13.23-rds.20260224

Amazon Relational Database Service (RDS) for PostgreSQL announces Amazon RDS Extended Support minor versions 11.22-rds.20260224, 12.22-rds.20260224, and 13.23-rds.20260224. We recommend that you upgrade to these versions to fix known security vulnerabilities and bugs in prior versions of PostgreSQL. Amazon RDS Extended Support provides up to three additional years of critical security and bug fixes beyond a major version’s end of standard support date, giving you more time to upgrade to a new major version. Learn more about Extended Support in the Amazon RDS User Guide. You can upgrade your databases during scheduled maintenance windows using automatic minor version upgrades. To simplify operations at scale, enable automatic minor version upgrades and use the AWS Organizations Upgrade Rollout Policy to orchestrate thousands of upgrades in phases, first to development environments before upgrading production systems. You can also use Amazon RDS Blue/Green deployments with physical replication to minimize downtime for minor version upgrades. Amazon RDS for PostgreSQL makes it simple to set up, operate, and scale PostgreSQL deployments in the cloud. See Amazon RDS for PostgreSQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console or by using the AWS Command Line Interface (CLI).
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Amazon Connect Cases now lets you edit related items and delete cases from the agent workspace

Amazon Connect Cases now supports editing and deleting related items, and deleting cases directly from the agent workspace without administrator help. Agents can update comments, unlink contacts associated with the wrong case, or delete cases opened in error. Agents can also create, edit, and delete custom related items such as orders, returns, and invoices to capture additional case context. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town). To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
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Announcing general availability of Amazon EC2 M3 Ultra Mac instances

Amazon Web Services announces general availability of Amazon EC2 M3 Ultra Mac instances, powered by the latest Mac Studio hardware. Amazon EC2 M3 Ultra Mac instances are the next-generation EC2 Mac instances, that enable Apple developers to migrate their most demanding build and test workloads onto AWS. These instances are ideal for building and testing applications for Apple platforms such as iOS, macOS, iPadOS, tvOS, watchOS, visionOS, and Safari.    M3 Ultra Mac instances are powered by the AWS Nitro System, providing up to 10 Gbps network bandwidth and 8 Gbps of Amazon Elastic Block Store (Amazon EBS) storage bandwidth. These instances are built on Apple M3 Ultra Mac Studio computers featuring a 28-core CPU, 60-core GPU, 32-core Neural Engine, and 256GB of unified memory. Compared to EC2 M4 Max Mac instances, M3 Ultra Mac instances provide 2x the unified memory, 1.75x the CPU cores, 1.5x the GPU cores, and 2x the Neural Engine cores, giving Apple developers the headroom to run significantly more Xcode simulators in parallel and accelerate on-device ML workflows to improve product time to market. 
Amazon EC2 M3 Ultra Mac instances are available in US East (N. Virginia) and US West (Oregon). To learn more about Amazon EC2 M3 Ultra Mac instances, visit the Amazon EC2 Mac page.
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Amazon Bedrock Introduces Advanced Prompt Optimization and Migration Tool

Customers spend days to weeks optimizing prompts and evaluating responses when they want to migrate to a new model or just get better performance out of their current model. They struggle with changing their prompts quickly and then testing them to prevent regressions and improve on underperforming tasks. These situations call for the same tool – a prompt optimizer with built-in evaluations. 
Today, Amazon Bedrock introduces Advanced Prompt Optimization, a new tool that allows customers to optimize their prompts for any model on Bedrock, while comparing their original prompts to their optimized prompts across up to 5 models simultaneously. Customers can use this if they are migrating to a new model or just want to get better performance on their current model. If they’re changing models, they can select their current model as a baseline and up to 4 other models. If they aren’t changing models, they just select their current model to see before and after optimization. The optimizer takes in prompt templates, example user inputs for the variable values, optional ground truth answers, and an evaluation metric or short natural language criteria to use as a guide. It’s even compatible with multimodal inputs such as jpg, png, or PDF. The prompt optimizer works in a feedback loop to steer the prompt and resulting model responses toward optimizing the evaluation metric, and outputs the original and final prompt templates with evaluation scores, cost estimates, and latency.
For region availability, see our documentation. For pricing, see the Bedrock pricing page. To get started, use the Bedrock APIs for Advanced Prompt Optimizer or visit the Bedrock Console.
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Amazon CloudFront announces Passthrough Mode for mutual TLS (Viewer)

Amazon CloudFront now supports passthrough mode for viewer mutual TLS (mTLS) authentication, enabling customers to forward client certificates to their origin for validation without requiring CloudFront to perform certificate verification. Passthrough mode allows customers with existing mTLS implementations at their origins to use CloudFront without requiring to implement their validation logic at the edge.
CloudFront viewer mTLS already supports required mode and optional mode, which offload client certificate authentication to CloudFront using trust stores. Passthrough mode is designed for customers to maintain their existing mTLS validation infrastructure at their origin without requiring any trust store configuration on CloudFront. In passthrough mode, CloudFront forwards every request to the origin along with the client’s full certificate chain. Caching is not performed, ensuring each request is authenticated end-to-end by your origin. Connection functions which allow you to inspect or transform connection-level data are still invoked, enabling you to process certificate data before it reaches the origin.
CloudFront Mutual TLS (viewer) in passthrough mode is available at no additional cost. To learn more, refer to the documentation for CloudFront Mutual TLS (Viewer). 
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Amazon CloudFront announces support for OCSP Revocation for Mutual TLS (Viewer)

Amazon CloudFront now supports Online Certificate Status Protocol (OCSP) revocation checking for viewer mTLS, enabling you to validate client certificate revocation status in real time during connection establishment. This enables customers using mutual TLS (mTLS) on CloudFront  to verify that client certificates haven’t been revoked before accepting connections—a common requirement for regulated industries and zero-trust architectures.
Previously, customers implemented certificate revocation using CloudFront Functions and KeyValueStore, maintaining static revocation lists that were only as current as the last manual update. With OCSP, CloudFront queries the responder URL embedded in the client certificate at connection time, validating revocation status directly with the issuing Certificate Authority. CloudFront caches OCSP responses for up to 30 minutes to minimize latency impact on subsequent connections. The OCSP result is exposed in the connection function, enabling customers to implement custom logic—such as grace periods for certificate rotation, IP-based exceptions, or combining OCSP with their own revocation lists.
OCSP revocation checking for viewer mTLS is available at no additional cost. To learn more, refer to the documentation for CloudFront Mutual TLS (Viewer).
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ARC Region switch adds Lambda event source mapping execution block for event handling during failover

Amazon Application Recovery Controller (ARC) Region Switch helps customers orchestrate the failover of their multi-Region applications to achieve a bounded recovery time in the event of a Regional impairment. Today, we are announcing the Lambda event source mapping execution block, which automates the coordinated failover of event streams for multi-Region workloads. Customers running event-driven architectures use Lambda functions with event source mappings to process event streams from Kinesis, DynamoDB Streams, MSK, or SQS. For active-passive workloads, customers may maintain Lambda functions in each Region but process events in only one Region at a time. These event source mappings must be toggled during failover to avoid duplicate processing—a manual, error-prone step. The Lambda event source mapping execution block automates this by enabling or disabling event source mappings in either the activating or deactivating Region. To control duplicate processing, customers can configure two Lambda event source mapping execution blocks in sequence: a disable block to stop event processing in the deactivating Region, and an enable block to start it in the activating Region. The disable block can be overridden by running the plan in “ungraceful” mode for unplanned failovers where the deactivating Region may be impaired. Native cross-account support enables a single plan to handle event stream failover across multiple accounts. To get started, see the Lambda event source mapping execution block documentation. ARC Region switch is available in all commercial Regions. See ARC Region switch availability
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Amazon Aurora DSQL now supports change data capture (Preview)

Amazon Aurora DSQL introduces support for change data capture (CDC) in preview, enabling you to stream real-time database changes directly to Amazon Kinesis Data Streams. This fully managed capability removes the need to build or maintain custom streaming pipelines, making it easier to build event-driven applications, power real-time analytics pipelines, and synchronize data across systems. Aurora DSQL automatically captures the result of insert, update, and delete operations as change events. You can use these events to synchronize data across microservices, trigger downstream processing with AWS Lambda, or deliver to Amazon S3, Amazon Redshift, and Amazon OpenSearch Service through Amazon Data Firehose for analytics. CDC streaming requires no infrastructure setup and is designed to have zero impact on your database workload, so you can stream changes without affecting database throughput or latency. CDC streaming in preview is available in all AWS Regions where Aurora DSQL is available. Streams are billed using Distributed Processing Units (DPUs) based on the volume of data captured, with standard Amazon Kinesis Data Streams pricing applying separately. To learn more, read the blog and see getting started.
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AWS Transform agents now available in Kiro, Claude, Cursor, and Codex

Today, AWS announces that the AWS Transform agents — built on decades of AWS migration and modernization experience — are now accessible through a Kiro power, agent plugins, and via the AWS Transform MCP server. Developers can now consume all of AWS Transform’s capabilities directly from their preferred development environment, whether working interactively in an agentic IDE, managing jobs through the web console, or integrating programmatically via MCP.
This launch gives builders flexibility to choose the surface that fits their workflow while gaining the depth of transformation expertise behind the AWS Transform agents for Windows, VMware, mainframe and more. A developer can start a transformation in their agentic IDE, monitor progress and collaborate in the web console, then see results back in their IDE — all against the same underlying job with consistent state. Additionally, AWS Transform now supports IAM role authentication. Customers who start using AWS Transform in their IDE or the web app can use their existing AWS credentials to create a Transform environment, workspace, and transformation job.
The agent plugin and MCP are available on GitHub, and the Kiro Power within the Kiro marketplace. To learn more, see https://aws.amazon.com/transform.
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