The most appropriate initial action is to follow a systematic performance tuning methodology. This involves analyzing server configurations, performance recordings, and log files to identify the specific bottleneck causing the increased response times. Issues often stem from suboptimal caching, inefficient workbook design, or poorly configured server processes. Addressing these software-level issues is more cost-effective and targeted than immediately scaling hardware, which might not solve the root cause. This analytical approach ensures that any subsequent hardware investment is justified and necessary.

A. Adding hardware without analysis is a costly guess that may not address the actual performance bottleneck, which could be software or configuration related.

C. Reducing user access is a restrictive workaround that negatively impacts business operations and fails to solve the underlying performance problem.

D. Ignoring significant performance degradation found during testing defeats the purpose of the test and risks future production system failures.

1. Tableau Server Help Documentation: The official documentation outlines a structured approach to performance tuning that prioritizes analysis over immediate hardware changes. It recommends a process of creating a performance baseline

identifying bottlenecks through monitoring and analysis

and then tuning the server configuration. This methodology is detailed in the "Performance Tuning" section.

Source: Tableau Help

"General Performance Guidelines". (Accessed via Tableau's official documentation portal). Section: "Performance Tuning".

2. Tableau Whitepaper on Scalability: This technical guide emphasizes the importance of understanding the environment and workload before making scaling decisions. It states

"Before scaling Tableau Server

it is important to understand the factors that affect performance... Tuning can often yield significant performance improvements." This supports the principle of tuning before scaling hardware.

Source: Tableau. (2020). Tableau Server Scalability: A Technical Deployment Guide for Server Administrators. Section: "Factors that Affect Performance and Scalability"

p. 5.

3. University Courseware on Systems Performance: Reputable computer science and data systems courses teach that performance tuning is a hierarchical process. Optimization should first occur at the application and configuration level (e.g.

query optimization

caching strategies) before resorting to more expensive hardware scaling. This is a fundamental principle in systems architecture.

Source: DeWitt

D. J.

& Gray

J. (1992). Parallel database systems: The future of high performance database systems. Communications of the ACM

35(6)

85-98. (This foundational academic paper discusses tuning and architecture

establishing the principle of optimizing software/queries before scaling hardware). DOI: https://doi.org/10.1145/129888.129894