High-Performing Architecture III
Learn to design AWS architectures that manage diverse computational jobs efficiently, optimize costs, and support real-time data processing. This lesson guides you through selecting solutions like AWS Batch, Lambda, and analytics services to build scalable, resilient systems tailored for varied workloads and interactive applications.
We'll cover the following...
Question 61
A research organization needs to efficiently scale and manage a diverse array of computational jobs, varying in size and complexity, to optimize costs. The solution should also handle job dependencies and dynamically allocate resources based on computational demands.
As a solutions architect, suggest a solution that effectively manages diverse computational jobs, optimizes costs, and ensures reliable job execution.
A. Integrate AWS Lambda to dynamically invoke EC2 Spot Instances, optimizing the scheduling and scaling of data processing jobs based on varying data volumes.
B. Implement AWS Batch, utilizing on-demand Amazon EC2 instances within job queues that prioritize tasks based on computational needs and cost-effectiveness.
C. Deploy AWS Elastic Beanstalk with a worker environment configuration for automated scaling and resource management, adapting resource levels to job requirements and application demands.
D. Configure AWS Step Functions to manage task workflows, using EC2 Reserved Instances to handle stable, predictable loads and reduce costs in long-term operations.
Question 62
An international software firm plans to create an integrated real-time analytical system for aggregating ...