AWS Fargate Features

Overview

AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. It is compatible with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). AWS Fargate makes it easy to scale and manage cloud applications by shifting as much management of the underlying infrastructure resources to AWS so development teams can focus on writing code that solve business problems. Moving tasks such as server management, resource allocation, and scaling to AWS does not only improve your operational posture, but also accelerates the process of going from idea to production on the cloud and lowers the total cost of ownership (TCO). 

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Page Topics

Serverless Containers Security and Compliance Extending AWS Fargate Flexible Pricing

Serverless Containers

AWS Fargate manages capacity needs, operating system (OS) updates, compliance requirements, resiliency, and more, freeing you to focus on applications, not servers. Deploy any OCI compliant container image to AWS Fargate and move the undifferentiated heavy lifting of managing the underlying infrastructure to AWS. 

For customers running stateful workload in containers, you can leverage Amazon EFS with AWS Fargate to externalize data outside of your application. 

Respond to changes in demand seamlessly by dynamically scaling capacity to reduce wasted resources while ensuring application availability. Utilize AWS Auto Scaling’s scheduled scaling, target tracking, and step scaling techniques, and Kubernetes’ Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) components with AWS Fargate.

Security and Compliance

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.

Extending AWS Fargate

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.
 

Flexible Pricing

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.