You have been hired as an AWS Architect in a global financial firm. They provide daily consolidated reports to their clients for trades in stock markets. For a large amount of data processing, they store daily trading transaction data in S3 buckets, which triggers the AWS Lambda function. This function submits a new AWS Batch job in the Job queue. These queues use EC2 compute resources with this customized AMI and Amazon ECS to complete the job. 
You have been working on an application created using the above requirements. While performing a trial for the application, even though it has enough memory/CPU resources, the job is stuck in a Runnable state. Which of the following checks would help to resolve the issue?

Answer options:

A.Ensure that AWS logs driver is configured on compute resources.
B.AWS Batch does not support customized AMI, use ECS-optimized AMI.
C.Check dependencies for the job which holds the job in Runnable state.
D.Use only On-Demand EC2 instance in compute resources.

Correct Answer – A
If your compute environment contains compute resources, but your jobs don`t progress beyond the 
RUNNABLE
 status, then there is something preventing the jobs from actually being placed on a compute resource. Here are some common causes for this issue:
The 
awslogs
 log driver isn`t configured on your compute resources
Insufficient resources
No internet access for compute resources
Amazon EC2 instance limit reached
Option A is correct as this is one of the reasons which is preventing the jobs from actually being placed on a compute resource.
Option B is incorrect as AWS Batch supports both customized AMI and Amazon ECS-optimized AMI. This is not a reason for Job being stuck in the Runnable state.
Option C is incorrect as a Job moves into a Runnable state only after all dependencies are processed. If there are any dependencies, Job stays in the Pending state, not the Runnable state.
Option D is incorrect as Compute resource can be an On-Demand Instance or a Spot Instance. In the question, it is given that the application has enough memory/CPU resources, so this is not a reason for Job being stuck in the Runnable state.
For more information on AWS Batch Job state & troubleshooting, if a job is stuck in Runnable state, refer to the following URLs-
https://docs.aws.amazon.com/batch/latest/userguide/job_states.html
https://docs.aws.amazon.com/batch/latest/userguide/troubleshooting.html#job_stuck_in_runnable