Cloud Computing Köln

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.
Quelle: aws.amazon.com

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).
Quelle: aws.amazon.com

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.
Quelle: aws.amazon.com

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.
Quelle: aws.amazon.com

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.
Quelle: aws.amazon.com