Hi @amitjangid,
This is a known issue that comes up from time to time, especially on Free Trial accounts on GCP. The RESOURCE_EXHAUSTED: Limit reached for workspace creation error is a provisioning rate limit that Databricks enforces on trial accounts, and it can be triggered even when you have zero active workspaces. The key thing to understand is that this limit counts creation attempts, not the number of workspaces that currently exist. So if a previous attempt failed partway through (for example, due to a transient backend issue or a GCP configuration problem), that attempt still counts toward your daily quota.
You are right that this specific daily creation rate limit for Free Trial accounts is not explicitly called out in the
Databricks resource limits documentation. The docs do mention a per-account workspace limit (which on GCP defaults to 20 workspaces) and a creation rate limit of up to 200 workspaces per week per GCP project for paid accounts. A community thread discussing
GCP workspace limits clarifies the distinction between the total workspace cap and the creation rate limit. For Free Trial accounts, the daily creation rate limit is more restrictive and is enforced at the account level.
To answer your specific questions:
Does the limit reset automatically? Yes. The error message itself says "Please try again in 24 hours," and the limit does reset automatically after that window. You do not need to take any action to clear it.
Could this be triggered by something other than existing workspaces? Absolutely. Failed creation attempts, cancelled provisioning, or even repeated retries in the UI all count toward the daily cap. If you clicked "Create Workspace" multiple times after seeing errors, each attempt may have been counted.
What to do next: Wait 24 hours and try again with a single, clean attempt. Before you retry, double-check that your GCP project has the necessary APIs enabled and that your IAM permissions are correct, so the creation succeeds on the first try. The
Databricks on GCP workspace creation guide walks through the prerequisites. If you are using the "serverless compute with default storage" option (as shown in your screenshot), the setup is simpler, but the underlying provisioning still needs to succeed on the GCP side.
If the error persists after 24 hours with a fresh attempt, it may point to a backend provisioning issue in your region. Other community members have reported similar RESOURCE_EXHAUSTED errors tied to
regional capacity constraints. In that case, you could try selecting a different GCP region (for example, us-central1 instead of us-west1) to see if the issue is region-specific.
If none of that resolves it, your best path forward is to contact Databricks support directly. Since you are on a Free Trial, you can reach out via the
Databricks Help Center with your account ID, the region you're targeting, and the approximate time of the failed attempts. They can check whether there's an account-level block or a regional provisioning issue on the backend.
Hope this helps, and good luck getting your workspace up and running!
If this answer resolves your question, could you mark it as “Accept as Solution”? That helps other users quickly find the correct fix.
Regards,
Ashwin | Delivery Solution Architect @ Databricks
Helping you build and scale the Data Intelligence Platform.
***Opinions are my own***