Which solution will meet these requirements?
Use AWS App2Container (A2C) to containerize the job. Run the job as an Amazon Elastic Container Service (Amazon ECS) task on AWS Fargate with 0.5 virtual CPU (vCPU) and 1 GB of memory.
Copy the code into an AWS Lambda function that has 1 GB of memory. Create an Amazon EventBridge scheduled rule to run the code each hour.
Use AWS App2Container (A2C) to containerize the job. Install the container in the existing Amazon Machine Image (AMI). Ensure that the schedule stops the container when the task finishes.
Configure the existing schedule to stop the EC2 instance at the completion of the job and restart the EC2 instance when the next job starts.
Explanations:
While using AWS App2Container (A2C) and running the job on Amazon ECS with Fargate could optimize resource utilization, it may not be the most cost-effective option. The job runs infrequently (every hour) for a short duration (10 seconds), making the continuous running of ECS tasks less economical compared to serverless options.
AWS Lambda is a serverless solution that charges only for the compute time used, making it cost-effective for infrequently run jobs. By scheduling the Lambda function to run every hour with EventBridge, the job will incur minimal costs and still meet the memory requirements (1 GB) for execution.
While containerizing the job using A2C and running it on an existing AMI is feasible, this approach does not fully optimize costs as it would still require maintaining an EC2 instance running continuously or stopping/starting it, which can incur costs and operational overhead.
Stopping the EC2 instance after the job completion and restarting it before the next run may save costs, but it involves a longer startup time for the instance. This approach could lead to inefficiencies, especially with the scheduling overhead and potential delays in execution, making it less optimal compared to a serverless solution.