Q29 — AWS SAP-C02 Ch.1

Question 29 of 75 | ← Chapter 1

Q104. A company uses an on-premises data analytics platform. The system is highly available in a fully redundant configuration across 12 servers in the company's data center. The system runs scheduled jobs, both hourly and daily, in addition to one-time requests from users. Scheduled jobs can take between 20 minutes and 2 hours to finish running and have tight SLAs. The scheduled jobs account for 65% of the system usage. User jobs typically finish running in less than 5 minutes and have no SLA. The user jobs account for 35% of system usage. During system failures, scheduled jobs must continue to meet SLAs. However, user jobs can be delayed. A solutions architect needs to move the system to Amazon EC2instances and adopt a consumption-based model to reduce costs with no long-term commitments. The solution must maintain high availability and must not affect the SLAs.Which solution will meet these requirements MOST cost-effectively?

Correct Answer: D. Split the 12 instances across three Availability Zones in the chosen AWS Region. Run three instances in each Availability Zone as On-Demand Instances with Capacity Reservations. Run one instance in each Availability Zone as a Spot Instance.

Explanation

The correct answer is: D. Split the 12 instances across three Availability Zones in the chosen AWS Region. Run three instances in each Availability Zone as On-Demand Instances with Capacity Reservations. Run one instance in each Availability Zone as a Spot Instance. Option D provides a solution that maintains high availability, reduces costs through a consumption-based model, and does not affect SLAs. By splitting the 12 instances across three Availability Zones, you ensure redundancy and high availability for the system. This distributes the workload and mitigates the impact of any Availability Zone failures. Running three instances in each Availability Zone as On-Demand Instances with Capacity Reservations ensures that there is sufficient reserved capacity to handle the scheduled jobs with tight SLAs. Capacity Reservations provide reserved capacity, allowing you to have guaranteed access to instances when needed. Running one instance in each Availability Zone as a Spot Instance helps optimize costs. Spot Instances offer significant cost savings compared to On-Demand instances but can be interrupted with a two-minute notice when the Spot price exceeds your bid. User jobs, which have no strict SLAs and can be delayed, are suitable for running on Spot Instances. This solution effectively balances cost optimization and high availability while ensuring scheduled jobs meet their SLAs. By using a combination of On-Demand Instances with Capacity Reservations and Spot Instances, you can achieve cost-effectiveness without compromising system performance or availability. Option A (mixing On-Demand Instances with Capacity Reservations and Spot Instances) does not provide enough reserved capacity for the scheduled jobs with tight SLAs. Option B (running all instances as On-Demand Instances with Capacity Reservations except for one Availability Zone with Spot Instances) does not distribute the workload across Availability Zones as evenly as necessary. Option C (mixing On-Demand Instances with a Savings Plan and Spot Instances) does not provide enough reserved capacity for the scheduled jobs with tight SLAs. Therefore, the best solution for this scenario is Option D.