Cloud Engineer Research & Evidence-Based Practice 2 — Questions and Answers
Question 1: A cloud engineering team wants to evaluate whether migrating from VMs to containers will reduce infrastructure costs. Which methodology best supports this evidence-based decision?
- Conduct a proof-of-concept with representative workloads and measure actual resource utilization (Correct answer)
- Ask the container vendor for benchmark data from similar companies
- Review blog posts from companies that completed similar migrations
- Use theoretical calculations based on average container overhead figures
Correct answer: Conduct a proof-of-concept with representative workloads and measure actual resource utilization
A PoC with real workloads produces organization-specific data that reflects actual usage patterns rather than generalized benchmarks.
Question 2: When reviewing cloud vendor whitepapers to inform architectural decisions, what is the most important critical evaluation step?
- Check the publication date for currency
- Identify potential conflicts of interest in the sponsoring organization (Correct answer)
- Verify the author's credentials and certifications
- Confirm the whitepaper is hosted on an HTTPS domain
Correct answer: Identify potential conflicts of interest in the sponsoring organization
Vendor-sponsored research may have inherent bias toward their own products, so evaluating conflicts of interest is the primary critical lens.
Question 3: A team is selecting a cloud database service and finds two contradictory performance studies. What is the best next step?
- Default to the study with the larger sample size
- Examine the testing methodology, workload type, and conditions of each study (Correct answer)
- Choose the more recent study regardless of methodology
- Average the results of both studies
Correct answer: Examine the testing methodology, workload type, and conditions of each study
Contradictory results often stem from differences in methodology or workload characteristics, so comparing study conditions reveals which is more applicable.
Question 4: Which metric is most appropriate for measuring the business impact of a cloud cost-optimization initiative?
- Number of infrastructure tickets resolved per sprint
- Reduction in cloud spend as a percentage of revenue or equivalent business output (Correct answer)
- Total number of cloud resources decommissioned
- Average engineer hours saved per week
Correct answer: Reduction in cloud spend as a percentage of revenue or equivalent business output
Normalizing cost savings against a business output metric provides a meaningful, comparable measure of impact rather than an absolute dollar figure in isolation.
Question 5: A cloud architect wants to apply chaos engineering principles based on published research. Which source provides the most rigorous, peer-reviewed foundation?
- Netflix Tech Blog posts on their chaos experiments
- Peer-reviewed ACM or IEEE conference papers on fault injection testing (Correct answer)
- GitHub repositories with chaos testing frameworks
- Community wiki documentation for chaos tools
Correct answer: Peer-reviewed ACM or IEEE conference papers on fault injection testing
ACM and IEEE peer-reviewed papers undergo independent review for methodology rigor, making them the most credible academic sources.
Question 6: When establishing SLOs (Service Level Objectives) for a new cloud service, what evidence-based approach is most effective?
- Set SLOs at 99.99% availability to match industry marketing claims
- Analyze historical performance data of similar services and align with documented user tolerance thresholds (Correct answer)
- Copy SLOs from the largest competitor's public status page
- Use the cloud provider's default SLA as the internal SLO
Correct answer: Analyze historical performance data of similar services and align with documented user tolerance thresholds
Historical data and user research provide empirical grounding for SLOs that are both achievable and meaningful to end users.
Question 7: A team implements a new auto-scaling policy and wants to validate its effectiveness. Which approach best demonstrates evidence-based practice?
- Monitor the system for a week and report that it 'feels better'
- Define measurable success criteria before deployment, then compare pre- and post-deployment metrics against those criteria (Correct answer)
- Ask the on-call engineer whether incidents have decreased
- Review the cost dashboard once after two weeks
Correct answer: Define measurable success criteria before deployment, then compare pre- and post-deployment metrics against those criteria
Pre-defining success criteria prevents confirmation bias and ensures evaluation is objective and tied to quantifiable outcomes.
Cloud Engineer Research & Evidence-Based Practice 2
A cloud engineering team wants to evaluate whether migrating from VMs to containers will reduce infrastructure costs.
Which methodology best supports this evidence-based decision?