Tag: Internet

Amazon OpenSearch Service introduces support for Derived Source, a new feature that can help reduce the amount of storage required for your OpenSearch Service domains. With derived source support, you can skip storing source fields and dynamically derive them when required.  OpenSearch stores each ingested document in the _source field and also indexes individual fields for search. The _source field can consume significant storage space. To reduce storage use, you can configure OpenSearch to skip storing the _source field and instead reconstruct it dynamically when needed, for example, during search, get, mget, reindex, or update operations. Derived Source is available in all regions where OpenSearch 3.1 is supported. The feature is opt-in and can be enabled at index creation using composite index settings. Please refer to the AWS Regional Services List for more information about Amazon OpenS

OpenSearch has introduced Star-Tree Index, a new feature that significantly improves aggregation performance for high-cardinality and multi-dimensional queries. This index pre-aggregates data across configured dimensions and metrics at ingestion time, enabling sub-second response times for frequent aggregations like terms, histogram, and range. Star-Tree Index is designed for real-time analytics and requires no changes to query syntax; OpenSearch automatically uses the optimized path when supported queries are detected. Early benchmarks show faster aggregation performance on large datasets. This makes it ideal for use cases such as observability, personalization, and time-series dashboards. It works best with append-only data and builds during segment refresh/merge, with minimal impact on ingestion throughput. Star-Tree Index is available in all regions where OpenSearch 3.1 is supported. The feature is opt-in and can be enabled at index creation

Amazon S3 Batch Operations now supports managing objects within an S3 bucket, prefix, suffix, or more, in a single step in AWS Management Console. When creating an S3 Batch Operation, customers can specify the objects on which to perform the operation. With this feature you have the option to instead specify an entire bucket, prefix, suffix, creation date, or storage class. Amazon S3 Batch Operations will then quickly apply the operation to all the matching objects and notify you when the job completes. S3 Batch Operations lets you easily perform one-time or recurring batch workloads such as copying objects between staging and production buckets, restoring archived backups from S3 Glacier storage classes, or computing objects checksum to verify the content of stored datasets, at any scale. After starting your job, S3 Batch Operations automatically processes all of the objects that match your filtering criteria. You will receive a detai

Today, Amazon SageMaker HyperPod announces the general availability of the health monitoring agent for Slurm clusters. SageMaker HyperPod helps you provision resilient clusters for running machine learning (ML) workloads and developing state-of-the-art models such as large language models (LLMs), diffusion models, and foundation models (FMs). The health monitoring agent performs passive, background health checks of instances to identify problems in key areas without impact on application behavior or performance, flags failures instantly, and replaces any unhealthy instances to keep your training jobs running smoothly.  The agent runs continuously on all GPU- or Trainium-based nodes in your HyperPod cluster, watching for hardware issues such as unresponsive GPUs or NVLink error counters. When a fault is detected, it marks the node as unhealthy and automatically reboots or replaces it with a healthy node, keeping your jobs running without requiring manual intervention. Th

You can now generate AI-powered forecasts and visualizations on time-series data that has been indexed into Amazon OpenSearch domains. Forecasts can be used to enhance various analytics use cases to power insights into trending infrastructure utilization and events, application or business metrics, and more. They can help you anticipate upcoming changes in areas such as business metrics, website traffic, system performance, and more. You can easily get started with this feature by setting up forecasts within OpenSearch dashboards or the OpenSearch UI. No data science or AI expertise is required. AI-powered forecasts are available in all Amazon OpenSearch Service regions that support OpenSearch 3.1+ domains. Learn more from the

Amazon Connect Cases now supports filtering by date ranges in the case list view, enabling contact center managers and agents to efficiently manage their case workloads. For example, users can filter cases created in the last 30 days for monthly reporting, view cases modified in the last 24 hours to monitor recent activity, or surface cases with potential SLA breaches in the next 2 days to help prevent violations. 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) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.

You can now run OpenSearch version 3.1 in Amazon OpenSearch Service. OpenSearch 3.1 introduces several improvements in areas like search relevance and performance, and introduces features that simplify development of vector-driven applications for generative AI workloads. This launch incorporates Lucene 10 that enables optimized vector field indexing resulting in faster indexing times and reduced index sizes, sparse indexing for CPU and storage efficiency improvements, and vector quantization to reduce memory usage. Other key areas of improvement include improved range query performance, which benefits log analytics and time-series workloads, and reduced latency for high-cardinality aggregations. This launch also introduces a new Search Relevance Workbench, which provides integrated tools for teams to evaluate and optimize search quality

Starting today, customers can use the on-demand deployment option in Amazon Bedrock for their Meta Llama 3.3 models that have been fine-tuned or distilled in Bedrock. Models customized on or after September 15, 2025 will be eligible. This enables Bedrock customers to reduce costs by processing requests in real time without requiring pre-provisioned compute resources. Customers only pay for what they use, eliminating the need for an always-on infrastructure. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities customers need to build generative AI applications with security, privacy, and responsible AI built in. To get started, visit documentation here.

Today, AWS announces the general availability of the new Amazon Elastic Compute Cloud (Amazon EC2) R8gn instances. These instances are powered by AWS Graviton4 processors to deliver up to 30% better compute performance than AWS Graviton3 processors. R8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances. Take advantage of the enhanced networking capabilities of R8gn to scale the performance and throughput of network-intensive workloads such as SQL and NoSQL databases, and in-memory databases. For increased scalability, these instances offer instance sizes up to 48xlarge, including two metal sizes, up to 1,536 GiB of memory, and up to 60 Gbps of bandwidth to Amazon Elastic Block Store (EBS). These instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency an

AWS Organizations provides a new State field in the AWS Organizations Console and APIs (DescribeAccount, ListAccounts, and ListAccountsForParent) to enhance AWS account lifecycle visibility. With this launch, the account state, a new State field replaced the existing account status, Status field in the AWS Organizations Console, however both Status and State fields will remain available in the APIs until September 9, 2026. This launch allows you to have a more granular account state information such as, 'SUSPENDED' for AWS-enforced suspension, 'PENDING_CLOSURE' for in-process closure requests, and 'CLOSED' for accounts in their 90-day reinstatement window, and more. After September, 2026 the Status field will be fully deprecated. Customers using account vending pipelines should update their implementations to reference the State field before the Status field deprecation date. This feature is available in al