[FREE TRIAL] Missing All-Purpose Clusters Access - New Account

[pabloratache]

Issue Description: I created a new Databricks Free Trial account ("For Work" plan with $400 credits) but I don't have access to All-Purpose Clusters or PySpark compute. My workspace only shows SQL-only features.

Current Setup:

- Account Email: ronel.ratache@gmail.com
- Workspace Name: ronel.ratache
- Trial Plan: For Work (Premium Trial)
- Cloud Provider: AWS
- Region: us-west-2
- Account Status: Active, successfully deployed

What I Can Access:

- SQL Warehouses
- Vector Search
- Apps
- Lakehouse Postgres

What I Cannot Access (Missing):

- All-Purpose Clusters
- PySpark Compute
- Structured Streaming
- Job Clusters

What I See in the UI:

Left Sidebar → Compute

Only shows:
- Job Runs
- Data Ingestion

NO option for:
- All-Purpose Clusters
- Compute Resources
- Spark Clusters

Why I Need This: I'm building a Databricks Lakehouse POC project for my data engineering portfolio that specifically requires:

1. PySpark Development - Write and test Spark code
2. Structured Streaming - Real-time data ingestion pipelines
3. Delta Lake Transactions - ACID compliance
4. Medallion Architecture - Bronze/Silver/Gold layers

Questions

1. Is this a provisioning delay?
2. Do I need to request manual enablement for All-Purpose Clusters?
3. Is there a different Free Trial tier that includes PySpark?

Thank you for your help!

@databricks-support or @community-engineers

[Louis_Frolio]

Greetings @pabloratache , quick clarification question: are you working on Databricks Free Edition or on a Databricks 14-day Free Trial? The two are quite different in terms of capabilities and workspace behavior. Please advise when you can. Cheers, Louis.

[pabloratache]

Hi Louis,

Thank you for the quick response!

To clarify: I'm on a **Databricks 14-day Free Trial** (not Free Edition).

Signup path: https://www.databricks.com/try-databricks -> "For Work" plan

The issue is specifically that the Free Trial is provisioned with SQL-only access. I need All-Purpose Clusters enabled for PySpark development.

Is this a provisioning limitation, or can it be manually enabled for Free Trials?

Thank you!

[Louis_Frolio · Accepted solution]

Ah, got it @pabloratache , I did some digging and here is what I found (learned a few things myself).

Thanks for the detailed context — this behavior is expected for the current Databricks 14‑day Free Trial (“For Work” plan).

What’s happening with your Free Trial

• The 14‑day For Work trial provisions a serverless workspace by design, which exposes SQL Warehouses and serverless compute, not classic All‑Purpose clusters.
• During the trial, serverless compute is available for notebooks, jobs, and Lakeflow Declarative Pipelines, with scaling capped to 50 DBUs/hr. One SQL warehouse per workspace is allowed (also capped), and GPUs are not available.
• External network access is limited in trial workspaces, which can affect streaming sources/sinks; the recommended workaround is to upload data into the workspace for use in pipelines.

Answers to your questions

• 1) Is this a provisioning delay?
  No — this is by design for the Free Trial serverless workspace, not a delay.
• 2) Do I need manual enablement for All‑Purpose Clusters?
  Manual enablement isn’t available on Free Trials. To use All‑Purpose clusters, you need to upgrade to a paid workspace (Standard/Premium); then you can create clusters (subject to your cloud account quotas).
• 3) Is there a different Free Trial tier that includes PySpark?
  The trial does include PySpark, but via serverless compute in notebooks (not classic clusters). In a notebook, click Connect (top right) and choose Serverless to run Python/PySpark code.

How to run PySpark now (without clusters)

• Create or open a notebook, click Connect (top‑right), choose Serverless, set the language to Python, and run your PySpark code there.

# Quick smoke test in a serverless notebook
from pyspark.sql import functions as F

df = spark.range(0, 10).withColumn("ts", F.current_timestamp())
df.write.format("delta").mode("overwrite").saveAsTable("demo.bronze_range")

display(spark.table("demo.bronze_range"))

• You can orchestrate pipelines with Lakeflow Jobs or Jobs on serverless compute during the trial; note the 50 DBUs/hr cap and external network limits.

Why your UI looks SQL‑only under Compute

• In serverless trial workspaces, you won’t see the classic “Clusters” page; compute for notebooks is requested inline via the Connect → Serverless flow rather than through the Clusters UI.

If you need classic All‑Purpose clusters now

• Upgrade to a paid plan and use a traditional workspace deployed in your AWS account; then create All‑Purpose clusters and run PySpark/Streaming as needed (you’ll pay cloud infra costs in addition to DBUs after trial).

FYI: Trial page contact

• For onboarding questions, you can email onboarding‑help@databricks.com from the trial page.

Hope this makes things clear.

Cheers, Louis.

[pabloratache]

Thank you for taking the time to investigate and explain this. Really appreciate it!

Best regards,
Pablo