Why Fargate?
AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. 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.
Benefits of Fargate
Manage your applications, not infrastructure
Deploy and manage your applications, not infrastructure. Remove the operational overhead to scale, patch, help secure, and manage servers.
Monitor your applications to gain metrics and insights
Monitor your applications through built-in integrations with AWS services like Amazon CloudWatch Container Insights or gather metrics and logs with third-party tools.
Improve security through isolation
Improve security through workload isolation by design. Amazon ECS tasks and Amazon EKS pods run in their own dedicated runtime environment.
Optimize for cost
Pay only for compute resources used, with no upfront expenses. Further optimize costs with Savings Plans, Fargate Spot, or AWS Graviton processors.
Use cases
Web apps, APIs, and microservices
Build and deploy your applications, APIs, and microservices architectures with the speed and immutability of containers. Remove the need to own, run, and manage the lifecycle of a compute infrastructure, so you can focus on your applications.
Modernize applications
Use AWS Fargate with Amazon ECS or Amazon EKS to more easily run and scale your containerized workloads. Migrate and run your Amazon ECS Windows containers without refactoring or rearchitecting your legacy applications.
Support AI and ML applications
Create a flexible and portable artificial intelligence (AI) and machine learning (ML) development environment. Train, test, and deploy your ML models with scalable resources that boost server capacity while avoiding overprovisioning.
Data processing
Run data processing workloads, scale up to 16 vCPU and 120 GB memory per task, and integrate with AWS Batch for serverless parallel processing.
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