5 Other AWS Compute Options
Compare AWS Batch, AWS App Runner, and AWS Elastic Beanstalk by workload pattern, operational responsibilities, and infrastructure control.
for finite jobs
is designed for work submitted as jobs that can be queued and run when compute capacity is available. You define each job’s container image and resource needs, place jobs in a queue, and associate that queue with compute environments. Batch schedules the jobs and can manage capacity using options such as Amazon EC2 or AWS Fargate.
Batch fits work that is finite, repeatable, and often parallelizable. Examples include processing a large set of images, transcoding video files, running scientific simulations, and analyzing batches of financial data. A job can wait in a queue, run, and finish without keeping a web server available between jobs; separate jobs can process separate inputs when work is parallelized.
Choose Batch when queues, scheduling, and resource-aware execution matter. For a small event-driven task that runs briefly in response to an event, may be simpler. For an application that must continuously serve HTTP requests, choose a web-service option instead.
for managed web services
deploys a web application or API from source code or a container image and operates it as a scalable web service. It can build from a supported source repository or use a container image, while handling much of the service setup and operation.
App Runner suits developers who want to publish an HTTP endpoint without configuring and operating the underlying container infrastructure in detail. For example, a team could deploy a small customer-facing API from its source repository or run an existing web-service container as an App Runner service.
Choose App Runner for a relatively straightforward, continuously available web application or API when ease of deployment and managed operations are priorities. It is not a job queue for finite workloads like Batch, and it offers less infrastructure-level control than managing deployment on EC2 or a container platform yourself.
environments
helps deploy, monitor, and scale web applications and services. You provide application code or a supported container, select an environment, and Beanstalk provisions and manages the resources needed to run it. You can still configure the environment and access its underlying AWS resources, giving it more visibility and control than a more fully managed web-service approach.
A team with an existing Java or Python web application might use Beanstalk to deploy it to a managed platform and scale its EC2-backed environment without assembling every deployment component itself. Standard environments can also include a worker tier for background tasks delivered through Amazon SQS.
Beanstalk environment types and control
Elastic Beanstalk documents two environment types with different compute models. A can include EC2 instances and an Auto Scaling group; a load-balanced web environment can also include a load balancer. Standard environments can include a worker tier for background tasks delivered through Amazon SQS.
A runs applications as containers on an Amazon EKS cluster operated by Beanstalk. Check the environment type and its requirements when choosing Beanstalk, because Standard and Cluster use different compute models. Choose Beanstalk when you want a managed application-deployment workflow but still need to configure or inspect more of the environment than a simpler web-service option typically exposes. Choose direct EC2 or container orchestration when you need greater control over infrastructure or container design and operation.
Match the service to the workload
Start with the workload’s execution pattern and the amount of infrastructure control you need:
Many independent jobs that can wait, run, and finish point toward , which queues and schedules jobs against configured compute capacity.
A web application or API with minimal infrastructure setup points toward , which deploys source code or a container image as a managed web service.
A web application needing managed deployment and a configurable application environment points toward , which provisions and manages the environment while allowing configuration of underlying resources.
A need for maximum control over virtual machines or container orchestration points toward Amazon EC2 or a container service, where you design and operate more of the compute platform yourself.
Short, event-triggered code execution points toward , which is suited to function-based tasks rather than a continuously available web service or queued job system.
These services reduce different kinds of operational work. The choice still depends on application requirements, permissions, networking, monitoring, and cost.