Evaluating Databricks' Cost Control Features: A Closer Look at Budgets and Cost Dashboard

Introduction

Cost control is crucial for managing expenses, ensuring projects stay within financial boundaries, and ultimately safeguarding our budgets. With Databricks recently introducing "Budgets" and an enhanced cost dashboard, let's dive into how well these features enable users to control their spending. Here are my quick thoughts:

Pros:

• Granular Cost Tracking: Databricks excels in providing tag-level granularity, allowing users to track costs at a very detailed level. This is well-designed and thoughtfully implemented.

• Easy Budget Setup: Setting up a budget in Databricks is straightforward and user-friendly.

• Clean Interface: The interface is intuitive, and the simple reporting available at the account level console is highly useful.

• Cost Transparency: The inclusion of budgets enhances cost transparency, giving users a sense of control over their spending.

• Comprehensive Dashboard: The new in-workspace dashboard offers extensive reporting capabilities, making it a valuable tool for monitoring expenses.

Neutral:

• Tag-Level Tracking vs. Compute Cost Control: While Databricks supports tag-level tracking, it lacks the ability to directly attach cost controls to compute resources, a feature available in Snowflake. This would be a beneficial addition to Databricks.

Considerations:

• Lack of Automated Alerts: Currently, there are no automated warnings when budgets are nearing their limits, nor are there any mechanisms to hard stop compute when limits are reached. This could lead to unexpected overspending.

• Limited Account Console Reporting: The reporting inside the account console could be richer. Users often have to rely on in-workspace reporting with AI/BI dashboards for detailed insights.

• Partial Expense Tracking: The system tracks only the Databricks portion of expenses, excluding costs related to resources like EC2.

Overall Impression

Databricks is doing a commendable job with their new cost control features, but there are areas for improvement. The lack of proactive capabilities to prevent thresholds from being exceeded and the absence of notifications when nearing a limit are notable weak points. However, as these features are still in Public Preview, there is hope for continued enhancements and refinements.

Conclusion

Despite its current limitations, Databricks' efforts in cost control are better than expected. Users can look forward to future improvements that will make budget management more robust and comprehensive.

Watch a Quick Walkthrough

For a more in-depth look at these features, check out this video: Video with work.

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