How much time will my students receive?

There are 2 offerings: (a) An environment for 2 months with Cluster Uptime of 72 hours. (b) An environment for 4 months with Cluster Uptime of 136 hours.

How should I allocate time to my students?

The time assigned for each student is calculated as 8 hours per week.

What management capabilities do I possess as an instructor?

As an instructor you would have admin access over the workspace, along with permissions to create catalogs and manage permissions for users.

What permissions do I have in the lab, and what permissions do students have?

As an instructor you would have "Can Manage" permissions over Clusters and SQL Warehouse, while students will have "Can Restart" permissions over the cluster and "Can Use" permissions over the SQL Warehouse.

What features are at my disposal as an instructor?

As an instructor you will be able to access and manage student environments.

What limitations exist within the environments?

For students there would be a restriction to create a personal/all-purpose compute cluster, SQL Warehouse, deploy DLT pipelines, and use the Partner Connect feature.

What if I require additional time?

If you require additional time, you can let us know in advance and we can increase the lab uptime, which would be available for an additional cost.

What if I need to install additional libraries?

As an instructor you have permissions to install libraries yourself. Alternatively, you can share the list of libraries to be pre-installed with us and we will take care of it at the backend.

On which cloud platform is it available?

The Databricks compute resources will be hosted on AWS.

What if I prefer a different platform?

If you wish to host the Databricks compute resources on a different cloud platform, you can reach out to us and we will assist with the custom request. It can be hosted on Azure and GCP as well — there won't be any difference in the Databricks workspace features, though cloud costs may differ.

What occurs when the allotted time ends, and what happens to progress and data?

There are two separate concepts. Lab Uptime Hours — the time during which students have access to the Databricks Cluster or SQL Warehouse to perform operations. If lab uptime is exhausted, students can no longer run operations but all data remains intact; you can request an increase by contacting us. Lab Duration — the total time the lab environment is available. If it expires, students lose access and data will be lost; however, lab duration can be extended before expiry upon advance request. Example: for a 2-month semester with bi-weekly 4-hour classes, students need 8 hours/week on Databricks, giving a total uptime of 72 hours (including a buffer).

Databricks

Databricks Lab Environment for Academics

Transforming education with a secure, scalable, budget-friendly, and fully managed Databricks Lab Environment, tailored for both teaching and learning AI, Cloud, and Data skills.

Watch overview

Secure & fully managed Budget-friendly Built for education

Trusted globally

Institutions that trust CloudLabs

Powering hands-on learning for universities, ed-tech platforms, enterprises, and ISVs worldwide.

17K+

Databricks clusters powered at Data+AI Summit
200+

Institutions trust CloudLabs
80%

Reduction in lab infrastructure costs
99.9%

Platform uptime SLA

Who is it for?

A lab environment built for every learner

Teaching simplified, learning amplified

If you're teaching Data and AI Technologies in your university curriculum, our managed Databricks lab environment can seamlessly integrate with your existing course structure across various departments.

Seamless course integration
Pre-configured Databricks workspaces align with your syllabus — zero setup required for students or instructors.
Multi-department support
Compatible across Computer Science, Business Analytics, Data Science, and Engineering programs.
Instructor dashboard
Monitor student progress, lab utilization, and completion rates from a single control panel.
Budget controls
Per-lab spending caps and auto-shutdown policies keep departmental costs predictable.
Buy for your Institute

University instructor teaching data science in a classroom

Why Choose CloudLabs?

Everything you need, nothing you don't.

Fixed-Cost Access to Managed Databricks Lab Environments

Access fully managed Databricks lab environments at a transparent, fixed cost — no surprise cloud bills, no per-cluster pricing. Budget with confidence from day one.

Fixed Time on CPU/GPU Labs, Extensions Available On-Demand

Each lab comes with a pre-allocated time window on CPU or GPU environments. Need more time? Extensions are available on-demand without any disruption to your workflow.

No Requirement for Your Own Databricks or Cloud Accounts

CloudLabs provisions everything. No Databricks subscription, no cloud account, no credit card required — just a ready-to-use environment for your students or team.

Lab Environments with Unlimited DBU Credits

Labs include unlimited Databricks Unit (DBU) credits within the session window, so learners can run notebooks, ML workloads, and data pipelines without hitting credit limits.

Databricks Lab Environment Accessible from Anywhere

The Databricks lab environment is fully browser-based and accessible from any device, anywhere in the world — no VPN, no local installation required.

24×7 Support Available

Our dedicated support team is available 24 hours a day, 7 days a week to help instructors, learners, and professionals get the most out of their lab experience.

Databricks University Alliance

CloudLabs Collaboration with Databricks University Alliance

CloudLabs is proud to announce its collaboration with Databricks University Alliance (DBUA), facilitating a fixed-cost access to Databricks lab environments for teaching Data and AI. With CloudLabs, educators can focus more on cognition rather than building tech stacks, making the teaching experience easier and more efficient.

Reach out for customized lab duration — psm-cloudlabs@spektrasystems.com

CloudLabs and Databricks University Alliance partnership

CloudLabs — Databricks Offerings

Databricks Lab Environment
Configuration SKUs

Five cluster configurations to match every teaching and learning scenario. Available in two durations: 2 months (1,460 hrs lab · 72 hrs cluster uptime) or 4 months (2,920 hrs lab · 136 hrs cluster uptime).

CPU Cluster

Shared workspace access with an All-Purpose Compute Cluster and full Cluster Capacity controls. Includes Instructor and Student permission management and access to Data Engineering, Machine Learning, Vector Search, and Databricks Assistant.

CPU Cluster & SQL Warehouse

Combines All-Purpose Compute with SQL Warehouse Capacity — ideal for data engineering and analytics curricula. Includes Shared Workspace, Instructor and Student permissions, Data Engineering, Machine Learning, Vector Search, and Databricks Assistant.

GPU Cluster

High-performance GPU compute for AI and machine learning workloads. Shared workspace with a GPU-accelerated All-Purpose Cluster, full Cluster Capacity controls, and complete access to Machine Learning, Vector Search, and Databricks Assistant.

SQL Warehouse

Dedicated SQL Warehouse with SQL Warehouse Capacity for analytics and BI workloads. Includes Shared Workspace, Instructor and Student permissions, Vector Search, and Databricks Assistant.

GPU Cluster & SQL Warehouse

The most comprehensive configuration — GPU computing power paired with SQL Warehouse Capacity. Full access to all Databricks features: Data Engineering, Machine Learning, Vector Search, and Databricks Assistant.

Detailed Comparison

Databricks Lab Environment Configuration

Feature-by-feature breakdown across all five cluster configuration SKUs.

Databricks Lab Environment Configuration
	CPU Cluster	CPU Cluster & SQL Warehouse	GPU Cluster	SQL Warehouse	GPU Cluster & SQL Warehouse
Access to Shared Workspace	Yes	Yes	Yes	Yes	Yes
All-Purpose Compute Cluster	Yes	Yes	Yes	—	Yes
Cluster Capacity	i3.xlarge	i3.xlarge	g4dn.xlarge	—	g4dn.xlarge
Instructor Permissions	Can Manage	Can Manage	Can Manage	Can Manage	Can Manage
Student Permissions	Can Restart	Can Restart	Can Restart	Can Use	Can Use
SQL Warehouse Capacity	—	2X-Small	—	2X-Small	2X-Small

Custom setup

Need a Custom Databricks Lab Setup for Your Institution?

Every university has a different curriculum, class size, and budget. Whether you need GPU-enabled clusters for a deep learning course, a semester-long environment for 500 students, or a custom Databricks configuration we haven't listed — our team will design it for you. Tell us what you're teaching, and we'll handle the rest.

Can't find what you are looking for? Let's talk!

About CloudLabs

CloudLabs is unwavering in its commitment to revolutionizing the education sector. We firmly believe that accessible, practical, and flexible education should be a cornerstone of learning for all. Headquartered in USA, CloudLabs operates globally, serving top-tier educational institutions to deliver cutting-edge technology education.

"Our goal is to drive innovation across the data and AI community. With the CloudLabs learning platform, we hope to accelerate access to cutting-edge resources and make data intelligence more easily integrated into teaching and learning environments, empowering the next generation of data science and machine learning professionals."

"At CloudLabs, our goal is to empower learning and enablement through modern and immersive technological experiences. By collaborating with Databricks University Alliance, we aim to provide access to a stimulative and demonstrative learning environment comprising hands-on labs that are secure, budget-friendly, and tailor-made for teaching and learning — Data, AI, and Cloud skills."

FAQ's

Questions, answered.

There are two separate concepts. Lab Uptime Hours — the time during which students have access to the Databricks Cluster or SQL Warehouse to perform operations. If lab uptime is exhausted, students can no longer run operations but all data remains intact; you can request an increase by contacting us. Lab Duration — the total time the lab environment is available. If it expires, students lose access and data will be lost; however, lab duration can be extended before expiry upon advance request. Example: for a 2-month semester with bi-weekly 4-hour classes, students need 8 hours/week on Databricks, giving a total uptime of 72 hours (including a buffer).