Schlagwort: cloud computing

langcache-embed-v3-small, Mellum2-12B-A2.5B-Thinking, and LightOnOCR-2-1B models now available on Amazon SageMaker JumpStart

Redis’s langcache-embed-v3-small, JetBrains’ Mellum2-12B-A2.5B-Thinking, and LightOn’s LightOnOCR-2-1B models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These three models bring specialized capabilities spanning semantic caching optimization, code-focused reasoning, and end-to-end document OCR, enabling customers to deploy high-performance, scalable AI solutions on AWS infrastructure.
langcache-embed-v3-small is optimized for semantic caching in LLM applications. It maps sentences and paragraphs into a dense vector space purpose-built for identifying semantically equivalent queries regardless of phrasing, enabling intelligent cache hits that reduce redundant LLM calls and accelerate response times in high-volume inference workloads.
Mellum2-12B-A2.5B-Thinking excels in code generation, debugging, multi-step reasoning, and agentic coding workflows. It uses a Mixture-of-Experts architecture (64 experts, 8 activated per token), activating only 2.5B of its 12B total parameters per forward pass with a 131,072-token context length. It emits explicit chain-of-thought reasoning traces before final answers, delivering high-throughput, low-latency inference ideal for routing, RAG, sub-agents, and private deployments.
LightOnOCR-2-1B provides end-to-end multilingual document-to-text conversion for PDFs, scans, and images without brittle OCR pipelines. This 1B-parameter vision-language model directly transduces page images into clean, naturally ordered text, achieving state-of-the-art performance on OlmOCR-Bench while being ~9× smaller and significantly faster than competing approaches.
With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases. To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.
Quelle: aws.amazon.com

FLUX.2-small-decoder and gemma-4-12B-it models now available on Amazon SageMaker JumpStart

Black Forest Labs’ FLUX.2-small-decoder and Google’s gemma-4-12B-it models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These two models bring specialized capabilities spanning efficient image generation decoding and unified multimodal understanding, enabling customers to deploy high-performance, scalable AI solutions on AWS infrastructure.
FLUX.2-small-decoder is optimized for faster image decoding with lower VRAM usage in FLUX.2 image generation pipelines. It is a distilled VAE decoder that serves as a drop-in replacement for the standard FLUX.2 decoder, delivering approximately 1.4× faster decoding speed at 1.4× lower VRAM consumption with minimal to zero quality loss. Benefits increase at higher resolutions where the decoder processes more pixels, making it ideal for production-grade image generation workloads at scale.
gemma-4-12B-it excels in unified multimodal understanding across text, image, and audio inputs with native support for function calling and agentic workflows. It features an encoder-free architecture where all modalities flow directly into a single decoder-only transformer, delivering performance nearing Google’s larger 26B MoE model at less than half the memory footprint. Compact enough to run on 16GB of RAM, it enables powerful multimodal and agentic experiences for enterprise deployments.
With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases.
To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.
Quelle: aws.amazon.com

AWS Elastic Disaster Recovery now preserves UEFI boot mode for Linux servers

AWS Elastic Disaster Recovery (AWS DRS) now preserves UEFI boot mode when recovering Linux source servers that boot with UEFI firmware. Previously, DRS launched these Linux servers in legacy BIOS mode, which could require extra configuration after recovery. Now your recovered Linux instances launch with the same UEFI boot mode as your source servers. This means your recovery instances more closely match your source environment, so applications that depend on UEFI boot behavior come back exactly as you expect — with no additional post-recovery steps. Boot mode preservation is automatic, with nothing to configure.
This capability is available in all AWS Regions where AWS DRS is offered, at no additional cost. To learn more, visit the AWS Elastic Disaster Recovery User Guide.
Quelle: aws.amazon.com

Amazon OpenSearch Serverless now supports up to 10,000 collections per collection group

The next generation of Amazon OpenSearch Serverless now supports up to 10,000 collections within a single collection group, increased from the previous limit of 1,500. Collection groups organize multiple collections and enable them to share OpenSearch Compute Units (OCUs), even when the collections are encrypted with different AWS KMS keys. With this higher limit, you can consolidate significantly more collections into a single collection group and manage them under a shared set of capacity limits.
Customers use collection groups to reduce costs by sharing compute across many collections rather than provisioning separate OCUs for each KMS key, while still maintaining collection-level security and access controls. As customer workloads have grown, particularly for multi-tenant applications that provision a collection per tenant, the previous limit of 1,500 collections per group constrained how many tenants could benefit from a shared compute pool. Raising the limit to 10,000 collections on the next generation of Amazon OpenSearch Serverless lets you scale these workloads further, improve compute utilization, and lower per-collection cost, without creating and operating additional collection groups. The higher limit applies automatically to new and existing nextgen collection groups.
The increased limit is available on the next generation of Amazon OpenSearch Serverless in all AWS Regions where it is available. To learn more, see Amazon OpenSearch Serverless technical documentation and quotas.
 
Quelle: aws.amazon.com

Amazon EC2 introduces application status checks

Amazon EC2 introduces application status checks, a new status check that helps customers detect and respond to application-level issues on their EC2 instances. With application status checks, EC2 monitors applications to detect issues such as a web server that has stopped accepting requests, a Docker daemon that is not running, an incorrect networking configuration, or a network interface that is no longer passing traffic.
Customers rely on EC2 status checks today to receive alerts when an instance or the underlying system is unreachable. However, to monitor application issues, customers had to build and maintain their own monitoring solution. Now, with application status checks customers can monitor the status of their applications running on EC2 instances alongside existing EC2 instance and system status checks. Customers create a check by specifying the protocol, port, and path to monitor, along with the response codes that indicate a healthy application. After customers associate the check with their instances by instance ID or tag, Amazon EC2 sends HTTP or HTTPS requests to that port and path and reports on the application’s status every 60 seconds. Auto Scaling groups act on application status, initiating recovery by replacing instances when their applications report unhealthy.
Application status checks are available in all commercial AWS Regions and AWS GovCloud (US) Regions.
To get started with application status checks and review pricing, see the Amazon EC2 User Guide.
Quelle: aws.amazon.com