AWS

Amazon RDS for SQL Server Developer Edition now supports Multi-AZ deployments using Always On Availability Groups. This feature provides a synchronous standby replica in a different Availability Zone with automatic failover capabilities. It allows teams to build and test high-availability configurations in non-production environments without Enterprise Edition licensing costs.

• Validate HA architecture and failover behavior in dev/test using production-equivalent setups.
• Eliminate Enterprise Edition licensing fees while testing Always On Availability Groups.
• Ensure non-production environments mirror production infrastructure for accurate testing.
• Leverage automatic failover in Multi-AZ deployments for realistic disaster recovery drills.

Fleet impact: Enables rigorous HA/failover testing for SQL Server workloads in non-production RDS instances without Enterprise licensing costs. DBAs should validate Always On AG configurations in dev/test to ensure production readiness for potential migration or upgrade scenarios.

Amazon EventBridge has updated its Custom event bus to support larger, decoupled architectures. The new version allows shared buses across accounts via AWS RAM and introduces strict ordering, open formats, and built-in retention. A revised publishing API enables direct event routing from publishers to central buses.

• Use AWS Resource Access Manager to share custom event buses across multiple accounts.
• Leverage strict ordering guarantees for critical event sequences.
• Benefit from built-in event retention and open format support.
• Adopt the new publishing API for direct routing to central buses.

Amazon ElastiCache Global Datastore now supports resource tagging and tag-based access control, closing a gap that previously prevented consistent permission and cost-allocation models across the service. Users can apply standard tagging operations and reference tags in IAM policies and Service Control Policies to grant access based on attributes rather than listing individual resources. Tag changes propagate automatically across all regions in a Global Datastore, ensuring that access and cost policies remain synchronized without manual per-region updates.

• Apply consistent IAM permissions and cost allocation across all regions in a Global Datastore.
• Use tag conditions in IAM policies and SCPs instead of enumerating specific resource ARNs.
• Tag modifications propagate automatically to every region, reducing operational overhead.
• Supports standard tagging APIs: AddTagsToResource, RemoveTagsFromResource, ListTagsForResource.

Amazon DynamoDB now supports multi-Region strong consistency (MRSC) in five new AWS Regions, bringing the total to 15. Practitioners can configure global tables with three replicas or two replicas plus a witness region across any supported locations, including cross-continent setups. This update enables zero recovery point objective (RPO) for highly available applications while allowing routing to geographically closer endpoints for reduced latency.

• MRSC now supports 15 AWS Regions including Canada Central, Stockholm, Spain, Mumbai, and Singapore.
• Configurations allow three replicas or two replicas with one witness region for flexibility.
• Cross-continent setups are now possible, spanning North America, Europe, and Asia Pacific.
• Applications can achieve zero RPO while routing to nearby endpoints for better performance.

Amazon EMR on EKS now supports interactive Apache Spark sessions via Spark Connect, allowing developers to use local IDEs like Jupyter or VS Code. This feature decouples the application client from the Spark driver, enabling persistent contexts that span cells and scripts while running on managed EKS clusters. Users can blend local Python execution with remote Spark operations without changing their existing development tooling.

• Use Spark Connect to run interactive sessions on EKS from local IDEs
• Maintain persistent Spark contexts across cells and scripts
• Decouple client from driver to keep preferred local tooling
• Develop and debug directly in SageMaker Unified Studio or Jupyter