Author: Deepali Rajale

In this post, we share how Karini AI’s migration of vector embedding models from Kubernetes to Amazon SageMaker endpoints improved concurrency by 30% and saved over 23% in infrastructure costs.

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we have helped hundreds of customers optimize their workloads, set guardrails, and improve visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share lessons learned about optimizing costs in […]

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we’ve helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share lessons learned about optimizing costs in […]

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we’ve helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share lessons learned about optimizing costs in […]

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support offering. Since its introduction, we have helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share lessons learned about optimizing costs […]

Cost optimization is one of the pillars of the AWS Well-Architected Framework, and it’s a continual process of refinement and improvement over the span of a workload’s lifecycle. It enables building and operating cost-aware systems that minimize costs, maximize return on investment, and achieve business outcomes. Amazon SageMaker is a fully managed machine learning (ML) […]

Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to quickly build, train, and deploy machine learning (ML) models. With SageMaker, you can deploy your ML models on hosted endpoints and get inference results in real time. You can easily view the performance metrics for your endpoints in Amazon […]