5/19/2026, 12:00:00 AM ~ 5/20/2026, 12:00:00 AM (UTC)
Recent Announcements
Amazon MWAA now supports Apache Airflow 3.2
Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow version 3.2, the latest major release of the popular open-source workflow orchestration framework. Amazon MWAA is a managed service that lets you run Apache Airflow at scale without managing the underlying infrastructure. This release brings new data-aware scheduling capabilities and developer productivity improvements to teams building and operating data pipelines on AWS.\n With Apache Airflow 3.2, you can now use asset partitioning to trigger downstream DAGs based on specific slices of data, such as a date-partitioned S3 path, rather than an entire asset, giving data engineering teams more precise control over pipeline execution. This release also expands Human-in-the-Loop (HITL) capabilities with a full audit history view for approvals, HITL support for the AgenticOperator, and synchronous callback support for Deadline Alerts. Additional improvements include Grid View virtualization for faster rendering of large DAGs, full XCom management from the Airflow UI, and async callable support in PythonOperator..
You can launch a new Apache Airflow 3.2 environment on Amazon MWAA, or upgrade from 2.11 or later, with just a few clicks in the AWS Management Console in all currently supported Amazon MWAA regions. To learn more about Apache Airflow 3.2 visit the Amazon MWAA documentation, and the Apache Airflow 3.2 change log in the Apache Airflow documentation. Apache, Apache Airflow, and Airflow are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.
Amazon Inspector is now available in the AWS Asia Pacific (Taipei) Region
Today, AWS announces the availability of Amazon Inspector in the AWS Asia Pacific (Taipei) Region. Amazon Inspector is an automated vulnerability management service that continually scans AWS workloads including Amazon EC2 instances, container images, and AWS Lambda functions for software vulnerabilities and unintended network exposure across your AWS Organization. \n With this expansion, Amazon Inspector extends its security coverage to AWS Asia Pacific (Taipei) Region, designed to help customers automatically discover workloads, conduct continuous vulnerability assessments, and receive actionable security findings. The service is designed to detect newly launched Amazon EC2 instances, Lambda functions, and eligible container images pushed to Amazon Elastic Container Registry (ECR) and scan them for software vulnerabilities and unintended network exposure. All accounts new to Amazon Inspector are eligible for a 15-day free trial to evaluate the service and estimate its cost. During the trial, all eligible Amazon EC2 instances, AWS Lambda functions, and container images pushed to Amazon ECR are continually scanned at no cost. After the trial period, you will be charged based on public pricing for Amazon Inspector. Visit the Amazon Inspector pricing page for more details. To get started with Amazon Inspector visit our documentation or begin your free trial today.
Amazon ECS introduces pause and continue controls for service deployments
Amazon Elastic Container Service (Amazon ECS) now enables you to pause service deployments at critical stages during deployment progression and continue deployments when ready. You can use these pause points to introduce manual decision points and interactive controls into your deployments for scenarios such as manual approval workflows, operational checks, integration tests, or custom automation, while continuing to use native Amazon ECS deployment strategies with managed traffic shifting, bake times, fast rollbacks, CloudWatch alarms, and deployment circuit breaker.\n With this launch, you can configure a new PAUSE deployment lifecycle hook as part of your Amazon ECS service deployment configuration. When a deployment reaches a configured pause point, Amazon ECS pauses deployment progression and emits Amazon EventBridge events that you can use to trigger automation workflows, approval systems, or external validation processes. You can then continue or roll back the deployment using the new ContinueServiceDeployment API. With pause hooks, you can configure timeout durations up to 14 days and timeout actions to automatically continue or roll back the deployment if no action is received.
You can configure pause hooks for rolling, blue/green, linear, and canary deployment strategies using the Amazon ECS Console, AWS CLI, AWS SDKs, AWS CloudFormation, AWS CDK, and Terraform. You can use the ContinueServiceDeployment API through the Amazon ECS Console, AWS CLI, and AWS SDKs. This feature is available in all AWS commercial and AWS GovCloud (US) Regions. To learn more, see our documentation on pause hooks for service deployments and continuing service deployments.
Amazon Managed Grafana now supports dual-stack connectivity (IPv6 and IPv4)
Amazon Managed Grafana now supports dual-stack connectivity, enabling workspaces to communicate over both Internet Protocol version 4 (IPv4) and Internet Protocol version 6 (IPv6). Dual-stack mode is available for workspaces running Grafana version 10.4 or later.\n With dual-stack support, customers can simplify their network stack by eliminating the need to manage overlapping address spaces in their VPCs. Customers migrating to IPv6 can connect to their Grafana workspaces over IPv6 while maintaining IPv4 compatibility, and those not yet on IPv6 can continue using IPv4-only connections. This is especially beneficial as the continued growth of the internet exhausts available IPv4 addresses.
Support for dual-stack connectivity on Amazon Managed Grafana is available in all regions where the service is generally available. To get started, update your workspace configuration via the Amazon Managed Grafana console, API, or CLI. For more information, see the Amazon Managed Grafana User Guide. To learn more about best practices for configuring IPv6 in your environment, visit the whitepaper on IPv6 in AWS.
AWS Blogs
AWS Japan Blog (Japanese)
- AWS Weekly Roundup: 1st anniversary of AWS Transform, Claude Platform on AWS, EC2 M3 Ultra Mac Instances, etc. (May 18, 2026)
- AWS Security Agent’s full repository code scanning feature is now available as a preview
- Introduction to Change Data Capture with Amazon Aurora DSQL
AWS Architecture Blog
- How ALS GeoAnalytics LITHOLENS ™ revolutionizes core logging through machine learning with Amazon EKS
- How Synthesia optimizes generative AI video inference on Amazon EC2 G7e instances
AWS Cloud Operations Blog
AWS Big Data Blog
- A systematic approach to benchmarking SQL processing engines on AWS
- Build petabyte-scale synthetic test data with Amazon EMR on EC2
- Meet Amazon Redshift RG – AWS Graviton-based instances with an integrated data lake query engine delivering up to 2.4x better performance at 30% lower price than RA3
AWS Database Blog
- Deploying Amazon RDS for Db2 using Terraform
- Nine Entertainment’s journey: Achieving 98% cost savings with Amazon ElastiCache Serverless for Valkey
- Automated JDBC query caching with the AWS Advanced JDBC Wrapper
AWS DevOps & Developer Productivity Blog
AWS for Industries
- How Toyota securely deployed HiveMQ with mTLS on AWS to power Smart Manufacturing
- From record to intelligence: How EMR systems on AWS become the foundation for generative AI in healthcare
Artificial Intelligence
- Scalable voice agent design with Amazon Nova Sonic: multi-agent, tools, and session segmentation
- Extending conversational memory in Kiro CLI using Amazon Bedrock AgentCore Memory
- Accelerate ML feature pipelines with new capabilities in Amazon SageMaker Feature Store
- Implementing programmatic tool calling on Amazon Bedrock
AWS Security Blog
- CIRT insights: How to help prevent unauthorized account removals from AWS Organizations
- Governing infrastructure as code using pattern-based policy as code