AWS

Amazon Aurora DSQL Change Data Capture is now generally available, allowing developers to stream real-time insert, update, and delete events directly to Amazon Kinesis Data Streams. This managed feature supports event-driven architectures by integrating with AWS Lambda, Amazon S3, Redshift, and OpenSearch via Data Firehose, all without requiring infrastructure management. The service is designed to operate with zero impact on the underlying database workload performance.

• Aurora DSQL CDC is GA and integrates natively with Kinesis Data Streams for real-time event streaming.
• Automatically captures inserts, updates, and deletes without managing infrastructure or impacting DB performance.
• Enables event-driven workflows by triggering Lambda functions or delivering data to S3, Redshift, and OpenSearch.
• Available in all AWS Regions where Aurora DSQL is currently supported.

Amazon EMR on EKS now integrates an Apache Spark troubleshooting agent that allows data engineers to diagnose job failures using natural language queries. The agent automatically analyzes Spark History Server data, distributed executor logs, and cluster configurations to identify root causes like memory errors or data skew. It provides automated root cause analysis and PySpark code recommendations, eliminating the need to manually navigate complex logs. This feature extends the troubleshooting agent's coverage to all EMR deployment options, including EC2 and Serverless.

• Diagnose EMR on EKS failures via natural language in the console.
• Agent analyzes history server data, logs, and configs for root causes.
• Identifies memory errors, data skew, contention, and connectivity issues.
• Provides automated root cause analysis and PySpark code fixes.
• Spark troubleshooting agent now covers EC2, Serverless, and EKS.

AWS Neuron 2.31.0 introduces NKI 0.5.0 with MX FP8 scale dtype support, tensor indirection for optimized indexed access, and zero-cost layout transformation APIs. The release adds a public beta UltraServer Operator for Amazon EKS to automate Trainium UltraServer workload management. Additionally, the Neuron Compiler uses a redesigned backend by default on Trn2 and Trn3 for better performance, while the Runtime simplifies configuration with contiguous shared scratchpad support.

• NKI 0.5.0 adds MX FP8 scale dtype and tensor indirection for efficient indexed access patterns.
• UltraServer Operator for EKS automates discovery, allocation, and resource claims for Trainium workloads.
• Neuron Compiler backend redesign is now default on Trn2 and Trn3, boosting inference/training performance.
• Neuron Runtime supports contiguous shared scratchpad, removing manual page size configuration needs.

Amazon DocumentDB now supports R8g.24xlarge and R8g.48xlarge instances powered by AWS Graviton4 processors and DDR5 memory. These new nodes offer up to 1,536 GiB of memory and 192 vCPUs, enabling larger in-memory working sets and higher throughput. They are designed to handle high-concurrency transactional applications and memory-intensive operational workloads.

• R8g instances leverage Graviton4 and DDR5 for improved throughput and memory capacity.
• R8g.48xlarge provides 192 vCPUs and 1,536 GiB RAM for massive working sets.
• Suitable for high-concurrency transactions and large-scale document processing.
• Deploy via Console, CLI, or SDK by modifying existing clusters or creating new ones.

Amazon SageMaker Unified Studio Workflows now includes 19 new operators to orchestrate Amazon Bedrock, S3 Tables, S3 Vectors, AWS Glue Data Catalog, and MWAA Serverless. These additions enable users to manage Bedrock guardrails, provision S3 resources, and handle Glue catalog tasks directly within the visual workflow builder. This update eliminates the need to write custom integration code or switch between multiple AWS consoles for these specific service interactions.

• 19 new operators added for Bedrock, S3 Tables/Vectors, Glue Catalog, and MWAA Serverless
• Visual workflow creator now supports managing Bedrock guardrails and Glue catalog objects
• No custom DAG code required for provisioning/deleting S3 Tables and Vectors
• Reduces context switching by orchestrating diverse AWS services from one interface
• Available in all AWS Regions as of the publication date

AWS has extended availability of sixth-generation Intel Xeon Scalable-powered R8in, R8ib, R8idn, and R8idb instances to Asia Pacific (Tokyo) and Europe (Frankfurt, Ireland) regions. These instances feature custom sixth-gen processors and latest Nitro cards, delivering up to 43% better compute performance per vCPU than previous R6 generations. The R8in and R8idn variants offer 600 Gbps network bandwidth, the highest among enhanced networking EC2 instances, targeting big data, in-memory caches, AI/ML caching fleets, and 5G Telco applications.

• New regions for R8in/ib/idn/idb: Tokyo, Frankfurt, Ireland
• Up to 43% better compute per vCPU vs R6in/6idn
• R8in/idn provide 600 Gbps network bandwidth
• Ideal for big data, AI/ML caches, and 5G Telco workloads
• Powered by custom 6th-gen Intel Xeon and latest Nitro cards

AWS Organizations now automatically attaches service control policies (SCPs) that prevent member accounts from leaving or closing when a new organization is created via the console. This default behavior safeguards multi-account environments by blocking unintended departures from day one. Central security teams gain immediate protection without manual configuration during initial setup.

• New orgs created via console get departure-blocking SCPs automatically
• Members cannot leave or close accounts without explicit policy override
• Reduces initial security configuration effort for new AWS entrants
• Existing orgs are not retroactively affected by this change
• CloudOps teams should verify SCP inheritance in new deployments