Remove Load Balancer Remove Metrics Remove Scalability
article thumbnail

Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

AWS Machine Learning - AI

there is an increasing need for scalable, reliable, and cost-effective solutions to deploy and serve these models. As a result, traffic won’t be balanced across all replicas of your deployment. For production use, make sure that load balancing and scalability considerations are addressed appropriately.

AWS 95
article thumbnail

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. API Gateway also provides a WebSocket API.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

HCL Commerce Containers Explained

Perficient

HCL Commerce Containers provide a modular and scalable approach to managing ecommerce applications. Scalability : Each Container can be scaled independently based on demand, ensuring the system can handle high traffic. It facilitates service discovery and load balancing within the microservices architecture.

article thumbnail

SaaS Platfrom Development – How to Start

Existek

They must track key metrics, analyze user feedback, and evolve the platform to meet customer expectations. Measuring your success with key metrics A great variety of metrics helps your team measure product outcomes and pursue continuous growth strategies. or Django serve for the core server logic and API integrations.

article thumbnail

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

AWS Machine Learning - AI

Amazon SageMaker AI provides a managed way to deploy TGI-optimized models, offering deep integration with Hugging Faces inference stack for scalable and cost-efficient LLM deployment. Optimizing these metrics directly enhances user experience, system reliability, and deployment feasibility at scale. xlarge across all metrics.

article thumbnail

AI-Driven API and Microservice Architecture Design for Cloud

Dzone - DevOps

Here are some key aspects where AI can drive improvements in architecture design: Intelligent planning : AI can assist in designing the architecture by analyzing requirements, performance metrics, and best practices to recommend optimal structures for APIs and microservices.

article thumbnail

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

AWS Machine Learning - AI

MaestroQA also offers a logic/keyword-based rules engine for classifying customer interactions based on other factors such as timing or process steps including metrics like Average Handle Time (AHT), compliance or process checks, and SLA adherence. Success metrics The early results have been remarkable.