Final answer:
The efficient cloud architecture for handling increasing workloads includes implementing AWS Auto Scaling, utilizing spot instances for cost savings, and considering AWS Lambda or AWS Batch. Using workload-specific EC2 instances can also optimize processing power.
Step-by-step explanation:
The subject of this question is efficient cloud architecture to handle increasing workload for batch jobs on Amazon EC2 instances. Given that the workload is expected to double each month with proportional increases in processing time, the architecture needs to be scalable and flexible.
One efficient approach is to use Auto Scaling with Amazon Elastic Compute Cloud (EC2). By setting up an auto-scaling policy, the company can automatically adjust the number of EC2 instances in use based on the processing demands. For computational efficiency and cost-effectiveness, the company could also leverage spot instances.
Another strategy involves employing services like AWS Lambda for batch processing tasks that can be broken down into stateless, independent chunks. For tasks that are not inherently parallelizable, AWS Batch could be used to optimize resource allocation and reduce execution times.
Finally, using EC2 instances that are optimized for the company's specific workload (such as compute-optimized or memory-optimized instances) can provide more processing power to handle the increasing demands.