Failing to align a cloud workload with a suitable architecture is a fundamental error in cloud strategy. The primary consequences are twofold: suboptimal performance and excessive cost. If a workload is placed on an under-provisioned architecture (e.g., an I/O-intensive database on a general-purpose instance), it will suffer from performance bottlenecks. Conversely, placing a workload on an over-provisioned architecture results in paying for unused capacity, leading to significant overspending. This dual risk of poor performance and wasted budget is the most significant and direct outcome of architectural misalignment.

A. Increased WAN bandwidth utilization is a potential symptom of poor geographic placement, but it is not a universal risk for all types of architectural misalignment.

C. Misaligned architectures, particularly those spanning different regions or providers, inherently complicate the enforcement of compliance, security, and data sovereignty policies.

D. CPU clock speed is a static hardware attribute of a cloud instance. Architectural misalignment is the act of choosing an inappropriate instance, not an action that causes a change in its hardware specifications.

1. HPE Solution Brief, "HPE Right Mix Advisor for HPE GreenLake," Document ID: a50002228enw, Published: March 2021.

Page 2, "The challenge" section: This document explicitly states that without a data-driven approach, organizations risk "placing workloads on platforms that are not optimized for cost or performance." This directly supports the conclusion that suboptimal performance and overspending (cost) are the major risks.

2. HPE White Paper, "Workload-optimized infrastructure from HPE," Document ID: 4AA5-6429ENW, Published: April 2016.

Page 3, "Workload-optimized solutions": The paper argues that a "one-size-fits-all" approach is inefficient and that infrastructure must be tuned to the specific demands of the workload. It states, "The result is a solution that is neither over-provisioned and costly nor under-provisioned and unable to meet performance SLAs." This reinforces that cost and performance are the key variables at risk.

3. HPE Education Services, Course Data Sheet, "Architecting HPE GreenLake Solutions, Rev. 21.41," Document ID: H9PH3S.

"Course Objectives" section: A key objective listed for this official training course is to "Describe workload/use case placement considerations." This highlights the centrality of proper workload alignment in the HPE GreenLake curriculum, underscoring its importance in avoiding common pitfalls like poor performance and cost inefficiency.