When a user reports slow performance for a newly-published workbook on Tableau Server, troubleshooting requires isolating the cause—e.g., data source issues, server load, workbook design, or caching. Thefirst questionshould establish a baseline to narrow the scope. Let’s analyze this step-by-step with depth:

Performance Context:

A workbook’s speed depends on:

Data Source: Query complexity, size, network latency (e.g., database vs. extract).

Workbook Design: Filters, calculations, dashboard complexity.

Server Resources: VizQL rendering, Backgrounder load, caching.

"Newly-published" implies it’s not yet optimized or cached on the server.

Option A (Does it run any faster in Tableau Desktop?): Correct.

Why First: Comparing Desktop vs. Server performance is the most foundational diagnostic step:

Desktop Baseline: If it’s slow in Desktop (local machine), the issue likely lies in the workbook (e.g., complex queries, large data) or data source (e.g., slow database)—not Server-specific.

Server Difference: If it’s fast in Desktop but slow on Server, the problem could be server-side (e.g., resource contention, network latency to the data source from Server).

Practical Next Steps:

Slow in Desktop: Optimize workbook (e.g., simplify calcs, use extracts).

Fast in Desktop: Check Server (e.g., caching, VizQL load).

Why Critical: Establishes whether the issue is inherent to the workbook/data or introduced by Server—guides all further investigation.

Option B (Does the workbook always run slowly or does performance vary?): Useful but secondary.

Why Not First: Variability (e.g., slow at peak times) points to server load, but without a Desktop baseline, you can’t rule out workbook design. It’s a follow-up question after A.

Detail: Variability might suggest caching or concurrent user impact, but it assumes Server-side causation prematurely.

Option C (How many times have you opened the workbook in Tableau Server?): Less relevant initially.

Why Not First: Frequency of access might affect caching (first load is slower, subsequent loads faster), but it’s too specific and doesn’t isolate Desktop vs. Server. It’s a niche follow-up.

Option D (Did you enable caching on the workbook?): Misleading and incorrect.

Why Not First: Caching is server-managed (e.g., VizQL cache settings via tsm data-access caching set), not a user-toggle per workbook. Users don’t "enable" it—admins do. Plus, it’s premature without a baseline.

Why This Matters: Starting with Desktop performance cuts through assumptions, pinpointing whether the root cause is client-side (workbook/data) or server-side—essential for efficient resolution in production.

Tableau Server’s minimum hardware recommendations for a production single-node deployment ensure reliable performance for small to medium workloads. As of the latest documentation:

CPU: 8 cores (2.0 GHz or higher) to handle concurrent users, rendering, and background tasks.

RAM: 32 GB to support in-memory processing (e.g., VizQL, Data Engine) and caching.

Disk Space: 50 GB free for installation, logs, extracts, and temporary files.

Let’s break it down:

Option C (8-Core CPU, 32 GB RAM, 50 GB free disk space): Correct. This matches Tableau’s official minimum for production:

8 cores ensure sufficient parallelism for processes like Backgrounder and VizQL.

32 GB RAM supports multiple users and extract refreshes.

50 GB disk space accommodates growth (initial install is ~1–2 GB, but logs and extracts expand).

Option A (4-Core, 16 GB RAM, 50 GB): Incorrect. Too low for production—4 cores and 16 GB RAM are below the threshold for reliable performance under load.

Option B (2-Core, 8 GB RAM, 15 GB): Incorrect. This is for non-production (e.g., trial) setups, insufficient for production stability.

Option D (4-Core, 64 GB RAM, 50 GB): Incorrect. 4 cores are inadequate, though 64 GB RAM exceeds the minimum (32 GB).

Why This Matters: Under-spec hardware can lead to slow performance, failed refreshes, or crashes in production—adhering to the minimum ensures stability.

The VizQL Server process in Tableau Server handles rendering visualizations and processing queries for users viewing dashboards or workbooks. During installation, Tableau Server automatically configures the number of VizQL instances based on the number of processor cores on the machine, following this rule:

Default VizQL instances = 2 per node, unless manually adjusted post-installation.

In multi-node setups, additional instances may be added based on core count, but the question specifies a single server with 16 cores.

The installer does not scale VizQL instances linearly with core count by default (e.g., it doesn’t set 1 instance per 4 cores). Instead:

For a single-node installation, the default is 2 VizQL instances, regardless of core count (assuming the minimum hardware requirements are met: 8 cores, 32 GB RAM).

Administrators can later adjust this using TSM (e.g., tsm topology set-process) based on performance needs, but the question asks for the default configured by the installer.

Option A (4): Incorrect. Four instances might be configured manually for a 16-core server, but it’s not the default.

Option B (6): Incorrect. Six instances exceed the default for a single node.

Option C (10): Incorrect. Ten instances are far beyond the default and would require manual configuration.

Option D (2): Correct. The installer sets 2 VizQL instances by default on a single-node installation.

In Tableau Server,projectsorganize content (workbooks, data sources) and use permissions to control access. "Locking permissions" restricts how permissions are managed within a project—let’s explore this exhaustively:

Permission Management Modes:

Managed by Owner: Default mode. Content owners (e.g., workbook publishers) can set permissions on their items, inheriting project defaults as a starting point.

Locked to the Project: Project-level permissions are enforced, and content owners cannot modify them. This ensures consistency across all items in the project.

How to Lock:

In the Tableau Server web UI:

Go toContent > Projects.

Select a project, clickActions > Permissions.

In the Permissions dialog, changePermissions Managementfrom "Customizable" (Managed by Owner) to "Locked."

Set the desired permissions (e.g., Viewer, Editor) for users/groups, which then apply uniformly to all content.

Via REST API: Use the updateProject endpoint with "permissionsLocked": true.

Option B (You can lock permissions to a project by changing Customizable to Locked): Correct.

Details: This is the precise action in the UI—switching from "Customizable" to "Locked" locks permissions at the project level.

Impact: Owners lose the ability to override permissions on individual workbooks/data sources, enforcing governance.

Example: Set "All Users" to Viewer (Locked)—all content in the project is view-only, regardless of owner intent.

Option A (Locking permissions must be enabled on the Server Settings page): Incorrect.

Why: Locking is a per-project setting, not a server-wide toggle. The Server Settings page (via TSM) controls global configs (e.g., authentication), not project permissions.

Option C (Content permissions are locked by default): Incorrect.

Default: New projects are "Managed by Owner" (Customizable), allowing flexibility unless explicitly locked by an admin.

Option D (By setting the appropriate Project permission role): Incorrect.

Confusion: "Project permission role" isn’t a term—permissions are set via rules (e.g., Viewer, Editor), but locking is a separate action (Customizable → Locked).

Why This Matters: Locking permissions ensures uniform access control, critical for regulated environments or large teams where consistency trumps flexibility.

Tableau Server uses internal secrets (tokens) for secure communication between its processes (e.g., Repository, File Store). These are automatically generated during installation and can be regenerated if compromised or for security maintenance. The command to update these is:

tsm security regenerate-internal-tokens: This regenerates the internal security tokens, ensuring all processes use the new tokens after a restart.

Option C (tsm security regenerate-internal-tokens): Correct. This is the documented command for updating internal secrets.

Option A (tsm data-access caching set -r 1): Incorrect. This command configures caching behavior, not security tokens.

Option B (tsm licenses refresh): Incorrect. This refreshes license data, unrelated to internal secrets.

Option D (tsm security validate-asset-keys): Incorrect. This validates encryption keys for assets, not internal tokens.

Tableau Server has specific hardware requirements for production environments to ensure stability and performance. The minimum recommended free disk space for a production installation is50 GB. This accounts for:

The installation itself (approximately 1–2 GB).

Space for log files, temporary files, and extracts managed by the File Store and Data Engine.

Room for backups and operational overhead.

The full minimum hardware recommendations for a single-node production deployment are:

8 CPU cores(2.0 GHz or faster).

32 GB RAM.

50 GB free disk space(on the system drive, typically C: on Windows).

Option A (32 GB): Incorrect. While 32 GB is the minimum RAM requirement, it’s insufficient for disk space in production.

Option B (50 GB): Correct. This matches Tableau’s official recommendation for production environments.

Option C (15 GB): Incorrect. 15 GB is the minimum for a non-production or trial installation, not production.

Option D (64 GB): Incorrect. While 64 GB exceeds the minimum, it’s not the specified requirement—50 GB is sufficient.

Tableau Desktop and Tableau Server have versioning considerations when publishing content, particularly regarding compatibility between older Desktop versions (e.g., 10.5) and newer Server versions (e.g., 2020.1). Let’s break this down step-by-step:

Version Context: Tableau Desktop 10.5 was released in 2017 and used the .tde (Tableau Data Extract) format for extracts. Tableau Server 2020.1, released in 2020, introduced the .hyper extract format (starting with version 10.5, but fully standardized later). When publishing from an older Desktop version to a newer Server version, Tableau ensures backward compatibility but may upgrade certain components.

Publishing Process: With a Creator site role and Publisher permissions, you have the rights to publish workbooks to the specified project. Tableau Server accepts workbooks from older Desktop versions (e.g., 10.5) and upgrades them to the current Server version (2020.1) duringpublishing. This process is seamless for the workbook itself, but extracts require special handling.

Extract Handling: If the workbook contains embedded .tde extracts (stored within the .twb or .twbx file), Tableau Server 2020.1 converts these to .hyper format upon publishing. This conversion is necessary because .hyper replaced .tde as the default extract engine starting in Tableau 10.5 and beyond, offering better performance and scalability. During this process, Tableau Desktop or Server displays a warning to inform the user of the upgrade, as it’s a one-way conversion (you can’t revert to .tde on the Server).

Now, let’s evaluate the options:

Option A (You will successfully publish without any errors or warnings): Incorrect. While the publishing succeeds, a warning about the .tde to .hyper conversion appears if the workbook contains embedded extracts. Without extracts, no warning occurs, but the question’s context implies extracts are likely involved (common in visualizations).

Option B (Error message: unable to publish to a newer version): Incorrect. Tableau supports publishing from older Desktop versions to newer Server versions. There’s no outright error blocking this; compatibility is maintained.

Option C (Warning: embedded .tde extracts will be upgraded to .hyper): Correct. This is the precise warning displayed when a workbook with .tde extracts is published to a Server version that uses .hyper. It ensures the user is aware of the format change, which might affect extract refresh schedules or performance expectations.

Option D (Warning: workbook will be upgraded to a new version): Partially correct but less specific. The workbook is upgraded to 2020.1 compatibility, but the warning focuses on the extract format change (.tde to .hyper), not the workbook version generically. Option C is more accurate.

Why This Matters: The .tde to .hyper shift improves query performance and supports larger datasets, but users need to know about it for planning (e.g., extract refresh schedules might need adjustment). The warning ensures transparency.