Amazon Quick now integrates with Snowflake Cortex AI

Amazon Quick now integrates with Snowflake Cortex AI through the Model Context Protocol (MCP), enabling teams to query their Snowflake data and documents using natural language, and automate multi-step workflows directly within their Quick workspace. After setting up the connection using Snowflake’s managed MCP server with OAuth authentication, you can ask questions across structured data through Cortex Analyst and retrieve insights from unstructured documents through Cortex Search.
With this integration, you can build Flows in Quick that orchestrate Snowflake Cortex Agents to execute repeatable, governed workflows with consistent structured output. This is ideal for any multi-step process that spans structured data and unstructured documents. The same MCP connection is also accessible from Quick Chat and other Quick features. For example, users can ask ad-hoc follow-up questions or explore their Snowflake data conversationally alongside their automated flows. Quick intelligently routes relevant prompts to Snowflake Cortex AI and returns contextualized answers alongside enterprise knowledge stored in Quick Spaces, giving teams both the rigor of a structured process and the flexibility of a conversational interface.
The Snowflake Cortex AI integration with Amazon Quick is available in all AWS Regions where Amazon Quick is available.
Visit the Amazon Quick website to learn more and start your Quick free trial. To learn more about the Snowflake Cortex AI integration, read the blog. To learn more about Quick integrations, visit the integrations page.
Quelle: aws.amazon.com

Amazon EC2 High Memory U7i-8TB instances now available in AWS Europe (Paris) region

Amazon EC2 High Memory U7i-8TB instances (u7i-8tb.112xlarge) are now available in AWS Europe (Paris) region. U7i instances are part of the AWS 7th generation and are powered by custom fourth-generation Intel Xeon Scalable processors (Sapphire Rapids). U7i-8TB instances offer 8 TiB of DDR5 memory, enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i instances offer up to 45% better price performance over existing U-1 instances.
U7i-8TB instances deliver 448 vCPUs and support up to 100 Gbps of Amazon EBS bandwidth for faster data loading and backups, 100 Gbps of network bandwidth, and ENA Express. U7i instances are ideal for customers running mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.
To learn more about U7i instances, visit the High Memory instances page.
Quelle: aws.amazon.com

Amazon EC2 Capacity Blocks for ML is now available in AWS GovCloud (US) Regions

Amazon EC2 Capacity Blocks for ML is now available in AWS GovCloud (US-West) and AWS GovCloud (US-East), enabling government and regulated-industry customers to reserve GPU capacity for machine learning workloads.
EC2 Capacity Blocks for ML allows you to reserve GPU instances in advance for a defined duration, giving you assured access to accelerated compute for short-duration pre-training, fine-tuning, rapid prototyping, and inference demand surges. Capacity Blocks deliver low-latency, high-throughput connectivity through colocation in Amazon EC2 UltraClusters.
You can reserve capacity up to eight weeks in advance for durations up to 6 months, in cluster sizes of one to 64 instances. Capacity Blocks can also be shared across multiple accounts using AWS Resource Access Manager (RAM), helping organizations coordinate ML infrastructure investments and keep reserved capacity in continuous use across workloads.
In AWS GovCloud (US), EC2 Capacity Blocks for ML is available on P6-B200 instances in AWS GovCloud (US-West), and P6-B200 and P6-B300 instances in AWS GovCloud (US-East). To get started, visit the EC2 Capacity Blocks documentation.
Quelle: aws.amazon.com

Amazon EC2 I7i instances now available in AWS Europe (Paris) Region

AWS is announcing the availability of high performance Storage optimized Amazon EC2 I7i instances in AWS Europe (Paris) region. Powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances. I7i instances offer compute and storage performance for x86-based storage optimized instances in Amazon EC2 ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets. Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.
Quelle: aws.amazon.com

Amazon Aurora now supports PostgreSQL major version 18

Amazon Aurora PostgreSQL-Compatible Edition now supports PostgreSQL major version 18, starting with version 18.3. This release brings community improvements to query performance and database management, and introduces support for pg_roaringbitmap, a new extension that performs fast, memory-efficient set operations on large collections of integers. This enables use cases such as audience segmentation, tag-based filtering, and permission checks directly in the database without application-layer processing. PostgreSQL 18 introduces B-tree skip scans, which improve query performance, and reduce index storage and maintenance overhead. Major version upgrades now retain optimizer statistics, ensuring consistent query performance immediately after upgrading without waiting for statistics to be regenerated. Logical replication can now stream large transactions in parallel, reducing replication lag and keeping downstream systems more current. Please refer to the Amazon Aurora PostgreSQL release notes for details. You can upgrade your database using several options including RDS Blue/Green deployments, upgrade in-place, or restoring a snapshot. Learn more about upgrading your database instances in the Amazon Aurora User Guide. Aurora PostgreSQL 18.3 is available in all commercial AWS Regions and AWS GovCloud (US) Regions. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full PostgreSQL and MySQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
Quelle: aws.amazon.com

Amazon CloudWatch Application Signals now supports infrastructure, logs, and traces context for faster troubleshooting

Amazon CloudWatch Application Signals introduces service health ranking on the application map and new infrastructure, logs, and traces tabs on the service overview page. These capabilities let operators triage unhealthy services and inspect the underlying compute environment, log snippets, and trace details in one place, making it easier to find root causes without switching tools. Customers use Application Signals to monitor the health of distributed applications, but identifying why a service was unhealthy often required leaving CloudWatch to correlate infrastructure data across separate tools. The application map now ranks services by health and shows runtime indicators on service nodes for Amazon EKS, Amazon ECS, AWS Lambda, and Amazon EC2, along with a new infrastructure tab that surfaces the compute and runtime environment, its components, and curated default metrics with deep links to the relevant monitoring tools. In addition, the service overview page provides the infrastructure, logs, and traces tab, helping operators spot issues in context of their application. With health-ranked services on the application map and new infrastructure, logs, and traces tabs, operators can instantly identify their most degraded services and drill into the compute environment, error-producing log snippets, and slow or failing transactions — all without leaving Application Signals. These capabilities span workloads running on Amazon EKS, Amazon ECS, AWS Lambda, and Amazon EC2, giving teams a single pane to move from symptom to root cause in minutes instead of hours. These capabilities are available in all AWS Regions where Amazon CloudWatch Application Signals is supported. To learn more about this feature, see the Amazon CloudWatch Application Signals documentation . For pricing details, see the Amazon CloudWatch pricing page
Quelle: aws.amazon.com

AWS announces AWS Workload Credentials Provider

AWS announces AWS Workload Credentials Provider, a lightweight client-side provider that automates deployment of exported certificates from AWS Certificate Manager (ACM) and local caching of secrets from AWS Secrets Manager across AWS and non-AWS workloads. Previously, customers exporting public or private certificates from ACM had to build custom automation using Amazon EventBridge to detect renewals and deploy the updated certificates. With public certificate lifetimes decreasing per the the Certification Authority Browser Forum (CA/B) mandate, this custom automation can become difficult to maintain at scale. AWS Workload Credentials Provider eliminates this complexity by providing a single provider that helps distribute and automate both secrets and certificates to your workloads. You configure it with your certificate ARN and specify options such as file paths and server reload behavior — the provider then handles certificate export and deployment automatically to prevent expiry related failures. It runs on Windows and Linux and supports Apache and NGINX web servers. For secrets caching, the provider maintains full backwards compatibility with the AWS Secrets Manager Agent, enabling you to securely cache application secrets locally across AWS and non-AWS workloads through the same unified provider. AWS Workload Credentials Provider is open source and available on GitHub. You can use it with exportable ACM certificates and Secrets Manager in all AWS Regions. To learn more, visit the AWS Certificate Manager documentation or the AWS Secrets Manager documentation.
Quelle: aws.amazon.com

Amazon Managed Service for Prometheus now supports out of order sample ingestion

Amazon Managed Service for Prometheus now supports out-of-order sample ingestion and a workspace-level rule query offset. All workspaces have a default out-of-order time window of 1 minute, allowing the workspace to accept metric samples arriving outside strict chronological order. You can adjust this window to match your ingestion patterns or set it to 0 to disable the feature and discard out-of-order samples. You can also configure a global rule query offset that introduces a delay before rule evaluation queries run, giving late-arriving samples time to be ingested before rules execute.
Together, these features reduce data loss and improve alerting accuracy for workloads with distributed collectors, batched exports, or variable network latency. Out-of-order sample support ensures late-arriving data points are ingested rather than discarded, preserving metric completeness. The rule query offset compensates for the expected ingestion delay. Without it, rules evaluate instantly and may miss samples that haven’t landed yet, producing results that differ from the same expression evaluated after all metrics arrive. Two new CloudWatch vended metrics, OutOfOrderIngestionRate and OutOfOrderSampleAge give you visibility into ingestion patterns, helping you tune both settings for your workload. 
Out-of-order sample ingestion and rule query offset are available in all AWS regions where Amazon Managed Service for Prometheus is generally available. To get started, configure the out-of-order time window and ruler query offset in your workspace settings via AWS console, API or CLI. For more information, see Amazon Managed Service for Prometheus user documentation.
Quelle: aws.amazon.com

AWS Elastic Beanstalk console now integrates CloudWatch Logs in the Logs tab

AWS Elastic Beanstalk now provides a CloudWatch Logs integration directly in the environment Logs tab of the Elastic Beanstalk console. Previously, customers had to navigate to the CloudWatch console to find the relevant log groups and log streams for their environments. With this launch, customers can view CloudWatch log events without leaving the Elastic Beanstalk console.  
The Logs tab displays log groups that an environment streams logs to, as well as log groups matching the aws/elasticbeanstalk/<env-name>/* prefix. Customers can select a log group to view its log streams, with the most recently active stream selected by default. A log stream dropdown allows switching between streams and filtering results. For deeper analysis, a View in CloudWatch dropdown provides direct links to the log group, log stream, or CloudWatch Logs Insights in the CloudWatch console.
This feature is available across all Elastic Beanstalk platform branches in all AWS Commercial Regions and AWS GovCloud (US) Regions where Elastic Beanstalk is available. For a complete list of supported Regions, see AWS Regions.
For more information about using Elastic Beanstalk with Amazon CloudWatch, see the AWS Elastic Beanstalk developer guide. To learn more, visit the AWS Elastic Beanstalk product page.
Quelle: aws.amazon.com

Amazon MWAA Serverless now supports Amazon EventBridge notifications/

Amazon Managed Workflows for Apache Airflow (MWAA) Serverless now supports workflow and task state change events to Amazon EventBridge, enabling data engineering and platform teams to build event-driven automation for their Apache Airflow workflows.
Previously, monitoring workflow execution required custom polling logic or manual observation. With this launch, MWAA Serverless can emit events when workflows transition between states, including started, running, succeeded, or failed, and when individual tasks change state, such as scheduled, succeeded, failed, or up for retry. With this feature, you can further automate your existing workflows – for example, using EventBridge notifications to trigger alerts when a production workflow fails, automatically restart dependent pipelines when an upstream workflow succeeds, or log state transitions to Amazon S3 for compliance and auditing.
This feature is available in all AWS Regions where Amazon MWAA Serverless is available. For the complete list of supported Regions, see Regions in the Amazon MWAA Serverless User Guide. For pricing details, see Amazon EventBridge pricing.
To learn more, see Monitoring Amazon MWAA Serverless in the Amazon MWAA Serverless User Guide and Amazon MWAA Serverless events in the Amazon EventBridge Events Reference.
Quelle: aws.amazon.com