AWS Fargate Features

For sensitive, multi-tenant, or regulated containerized workloads, AWS Fargate provides a secure virtualization boundary between every Amazon ECS task or Amazon EKS pod. Each task / pod is deployed on to a dedicated single use, single tenant piece of compute, providing secure isolation between workloads.

AWS Fargate connects applications to existing investments in Virtual Private Networks (VPC), providing load balancing, segmentation through VPC security groups, and traffic monitoring with VPC Flow Logs. For client-based routing and out of the box traffic observability, workloads can be configured with Amazon ECS Service Connect for inter-service communication.

For customers that need to run containerized workloads in regulated or controlled environments, AWS Fargate has been approved by numerous industry-standard compliance programs from HIPAA to PCI to FedRAMP, and is available in AWS GovCloud (US) regions.

To help with troubleshooting and debugging Amazon ECS Exec provides secure access to running containers without logging into SSH to underlying servers. Amazon ECS Exec commands are recorded for audit purposes in AWS CloudTrail and Amazon CloudWatch.

Containerized workloads running on AWS Fargate workloads are deeply integrated with AWS services allowing you to get started quickly with existing tools and skill sets. Workloads are secured with AWS Identity and Access Management, monitored with Amazon CloudWatch Container Insights and scaled with AWS Application Auto Scaling.

You can deploy .NET Framework applications with Windows Containers on Amazon ECS and AWS Fargate,
providing a seamless deployment story, improved monitoring and observability, and removing the management and licensing expenses of maintaining Windows Server instances.
 

With AWS Fargate you pay by the task size and only for the time for which resources are consumed by the task. By adding a tag to Amazon ECS tasks, you can use AWS Cost Explorer to visualize costs, identify opportunities for savings, and provide granular per workload billing.

Use Compute Savings Plans to lock in savings over one or three year increments, choose between On-Demand and Fargate Spot to blend cost and availability, and select AWS Graviton for improved cost-performance. AWS Compute Optimizer uses machine learning to analyze historical usage and provide recommendations on sizing tasks to reduce cost.