# Suboptimal Use of On-Demand Instances in Non-Production Clusters

Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/suboptimal-use-of-on-demand-instances-in-non-production-clusters

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

# Suboptimal Use of On-Demand Instances in Non-Production Clusters

## Explanation

In Databricks, on-demand instances provide reliable performance but come at a premium cost. For non-production workloads-such as development, testing, or exploratory analysis-high availability is often unnecessary. Spot instances provide equivalent performance at a lower price, with the tradeoff of occasional interruptions. If teams default to on-demand usage in lower environments, they may be incurring unnecessary compute costs. Using compute policies to limit on-demand usage ensures greater consistency and efficiency across environments.

## Relevant Billing Model

Databricks charges for compute based on:

- Databricks Units (DBUs): Varies by cluster configuration, including node type and pricing model (on-demand vs. Spot)

- Cloud Infrastructure Charges: Passed through from the cloud provider and dependent on instance pricing model

On-demand nodes incur the highest cost. Spot instances offer significant discounts but may be interrupted and are best used for dev/test workloads.

## Detection

- Query system tables to identify non-production clusters with high or full on-demand usage

- Review workspace and cluster policies to determine if Spot usage is being enforced

- Confirm whether the workloads running on these clusters are tolerant to interruptions

- Evaluate whether the use of on-demand instances is justified for each environment

## Remediation

- Implement compute policies that cap the percentage of on-demand nodes in relevant workloads

- Update existing cluster configurations to prioritize Spot usage for dev/test workloads

- Allow exceptions only when reliability or performance constraints are well documented

## Relevant Documentation

- Spot Instances in Databricks

- Compute Policies Overview

[Submit Feedback](https://hub.pointfive.co/inefficiencies/suboptimal-use-of-on-demand-instances-in-non-production-clusters)

## At a glance

Reference

CER-0023

Cloud provider

Databricks

Service

Databricks Clusters

Category

[Compute](https://www.pointfive.co/efficiency-hub/service-category/compute)

Inefficiency type

Suboptimal Pricing Model

## Contributed by

- ### Matt Weingarten

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Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.