Remove Load Balancer Remove Metrics Remove Performance
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Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

AWS Machine Learning - AI

AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment. We also demonstrate how to test the solution and monitor performance, and discuss options for scaling and multi-tenancy.

AWS 103
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Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI

AWS Machine Learning - AI

The following figure illustrates the performance of DeepSeek-R1 compared to other state-of-the-art models on standard benchmark tests, such as MATH-500 , MMLU , and more. SM_NUM_GPUS : This parameter specifies the number of GPUs to use for model inference, allowing the model to be sharded across multiple GPUs for improved performance.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

Load balancer – Another option is to use a load balancer that exposes an HTTPS endpoint and routes the request to the orchestrator. You can use AWS services such as Application Load Balancer to implement this approach. Refer to Perform AI prompt-chaining with Amazon Bedrock for more details.

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Composite AI: The trifecta that is transforming AIOps

CIO

For example, if a company’s e-commerce website is taking too long to process customer transactions, a causal AI model determines the root cause (or causes) of the delay, such as a misconfigured load balancer. AI trained on biased data may produce unreliable results. This customer data, however, remains on customer systems.

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Building Resilient Public Networking on AWS: Part 4

Xebia

One of the key differences between the approach in this post and the previous one is that here, the Application Load Balancers (ALBs) are private, so the only element exposed directly to the Internet is the Global Accelerator and its Edge locations. These steps are clearly marked in the following diagram.

AWS 130
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Revolutionizing customer service: MaestroQA’s integration with Amazon Bedrock for actionable insight

AWS Machine Learning - AI

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Mistral, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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HCL Commerce Containers Explained

Perficient

Benefits of HCL Commerce Containers Improved Performance : The system becomes faster and more responsive by caching frequent requests and optimizing search queries. Manageability : Containers are designed to perform specific tasks, making the system easier to monitor, debug, and maintain.