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Broadcom and OpenAI have announced an agreement to collaborate on producing 6GW of custom AI accelerators. OpenAI will design the chips and systems, which will be developed and deployed in …
The post Broadcom and OpenAI to collaborate on custom AI accelerators appeared first on Electronics Weekly .
By Steve Bush
Power Integrations is one of the power semiconductors collaborating with Nvidia on its 800V data centre concept, where ~1MW will be delivered to each rack over an 800Vdc bus, and …
The post 800V data centres: Power Integrations appeared first on Electronics Weekly .
At the OCP Global Summit, Nvidia will unveil specs of the Vera Rubin NVL144 MGX-generation open architecture rack servers, which more than 50 MGX partners are gearing up for along …
The post Nvidia and partners gear up for 800Vdc datacentres and Vera Rubin appeared first on Electronics Weekly .
By admin
After careful consideration, we’re announcing availability changes for a select group of AWS services and features. These changes fall into three lifecycle categories:
Services and Capabilities moving to Maintenance
Services moving to maintenance will no longer be accessible to new customers starting Nov 7, 2025. Current customers can continue using the service or feature while exploring alternative solutions.
Services Entering Sunset
The following services are entering sunset, and we are announcing the date upon which we will end operations and support of the service. Customers using these services should click on the links below to understand the sunset timeline (typically 12 months), and begin planning migration to alternatives as recommended in the updated service web pages and documentation.
Services Reaching End of Support
The following services have reached end of support and are no longer available as of October 7, 2025.
For customers affected by these changes, we’ve prepared comprehensive migration guides and our support teams are ready to assist with your transition. Visit AWS Product Lifecycle Page to learn more. or contact AWS Support .
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Amazon CloudWatch announces the general availability of generative AI observability, helping you monitor all components of AI applications and workloads, including agents deployed and operated with Amazon Bedrock AgentCore. This release expands beyond runtime monitoring to include complete observability across AgentCore’s Built-in Tools, Gateways, Memory, and Identity capabilities. DevOps teams and developers can now get an out-of-the-box view into latency, token usage, errors, and performance across all components of their AI workloads, from model invocations to agent operations. This feature is compatible with popular generative AI orchestration frameworks such as Strands Agents , LangChain, and LangGraph, offering flexibility with your choice of framework.
With this new feature, CloudWatch enables developers to analyzes telemetry data across components of a generative AI application. Customers can monitor code execution patterns in Built-in Tools, track API transformation success rates through Gateways, analyze memory storage and retrieval patterns, and ensure secure agent behavior through Identity observability. The connected view helps developers quickly identify issues – from gaps in VectorDB to authentication failures – using end-to-end prompt tracing, curated metrics, and logs. Developers can monitor their entire agent fleet through the “AgentCore” section in the CloudWatch console, which integrates seamlessly with other CloudWatch capabilities including Application Signals, Alarms, Sensitive Data Protection, and Logs Insights.
This feature is now available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney).
To learn more, visit documentation . There is no additional pricing for Gen AI Observability, existing CloudWatch pricing for underlying telemetry data applies.
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Vector search for Amazon ElastiCache is now generally available. Customers can now use ElastiCache to index, search, and update billions of high-dimensional vector embeddings from popular providers like Amazon Bedrock , Amazon SageMaker , Anthropic , and OpenAI with latency as low as microseconds and up to 99% recall.
Key use cases include semantic caching for large language models (LLMs) and multi-turn conversational agents, which significantly reduce latency and cost by caching semantically similar queries. Vector search for ElastiCache also powers agentic AI systems with Retrieval Augmented Generation (RAG) to ensure highly relevant results and consistently low latency across multiple retrieval steps. Additional use cases include recommendation engines, anomaly detection, and other applications that require efficient search across multiple data modalities.
Vector search for ElastiCache is available with Valkey version 8.2 on node-based clusters in all AWS Regions at no additional cost. To get started, create a Valkey 8.2 cluster using the AWS Management Console , AWS Software Development Kit (SDK), or AWS Command Line Interface (CLI). You can also use vector search on your existing clusters by upgrading from any version of Valkey or Redis OSS to Valkey 8.2 in a few clicks with no downtime . To learn more about vector search for ElastiCache for Valkey read this blog and for a list of supported commands see the ElastiCache documentation .
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AWS Config now supports 3 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.
With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators.
You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available:
Resource Types:
AWS::ApiGatewayV2::Integration
AWS::CloudTrail::EventDataStore
AWS::Config::StoredQuery
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AWS now provides immediate access to resource search capabilities in all accounts through AWS Resource Explorer. With this launch, you no longer need to activate Resource Explorer to discover your resources in a Region.
To start searching, you need, at minimum, permissions in the AWS Resource Explorer Read Only Access or AWS Read Only Access managed policies. You can discover resources in the AWS Resource Explorer console, Unified Search, and AWS CLI and SDKs. To search the full inventory of supported resources, including historical backfill and automatic updates, complete Resource Explorer setup. This requires additional permissions to create a Service-Linked Role, so that Resource Explorer can automatically complete setup in each Region where you search. You can also enable cross-Region search to discover resources across all Regions in your AWS account with one-click in the Console, or with a single API call using the new CreateResourceExplorerSetup API.
This feature is available at no additional cost in all AWS Regions where Resource Explorer is supported . To start searching for your resources, visit the AWS Resource Explorer console . Read about getting started in the AWS Resource Explorer documentation , or explore the AWS Resource Explorer product page .
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Amazon Bedrock AgentCore is an agentic platform to build, deploy and operate highly capable agents securely at scale using any framework, model, or protocol. AgentCore lets you build agents faster, enable agents to take actions across tools and data, run agents securely with low-latency and extended runtimes, and monitor agents in production – all without any infrastructure management.
With general availability, all AgentCore services now have support for Virtual Private Cloud (VPC), AWS PrivateLink, AWS CloudFormation, and resource tagging, enabling developers to deploy AI agents with enhanced enterprise security and infrastructure automation capabilities. AgentCore Runtime builds on its preview capabilities of industry-leading eight-hour execution windows and complete session isolation by adding support for the Agent-to-Agent (A2A) protocol, with broader A2A support coming soon across all AgentCore services. AgentCore Memory now offers a self-managed strategy that gives you complete control over your memory extraction and consolidation pipelines. AgentCore Gateway now connects to existing Model Context Protocol (MCP) servers in addition to transforming APIs and Lambda functions into agent-compatible tools. It also supports Identity and Access Management (IAM) authorization enabling customers to leverage IAM in additional to OAuth for secure agent to tool interactions over MCP, and acts as a single, secure endpoint for agents to discover and use tools without the need for custom integrations. AgentCore Identity now offers identity-aware authorization, secure vault storage for refresh tokens, and native integration with additional OAuth-enabled services so agents can securely act on behalf of users or by themselves with enhanced access controls. AgentCore Observability now delivers complete visibility into end-to-end agent execution and operational metrics across all AgentCore services through dashboards powered by Amazon CloudWatch, and it is OTEL compatible, offering seamless integration with Amazon CloudWatch and external observability providers like Dynatrace, Datadog, Arize Phoenix, LangSmith, and Langfuse. AgentCore works with any open source framework (CrewAI, LangGraph, LlamaIndex, Google ADK, OpenAI Agents SDK) and any model in or outside Amazon Bedrock, giving you freedom to use your preferred frameworks and models, and innovate with confidence.
Amazon Bedrock AgentCore is available in nine AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland).
Learn more about AgentCore through the blog , deep dive using the AgentCore resources , and get started with the AgentCore Starter Toolkit . AgentCore offers consumption-based pricing with no upfront costs.
By admin
Amazon Quick Sight now supports font customization for data labels and axes. Authors can now customize fonts for data labels and axes in supported charts, in addition to the previously supported font customization for visual titles, subtitles, and legend, as well as tables and pivot tables headers.
Authors can set the font size (in pixels), font family, color, and styling options like bold, italics, and underline across analysis, including dashboards, reports and embedded scenarios. With this update, you can further align your dashboard’s fonts with your organization’s branding guidelines, creating a more cohesive and visually appealing experience. Additionally, the expanded font customization options help improve readability, especially when viewing visualizations on large screens.
This is now available in all supported Amazon Quick Suite regions .
To learn more about this, visit Amazon Quick Suite Visual formatting guide.