Introduction

The “Invalid Storage Credentials” error in Databricks occurs when Databricks fails to authenticate with cloud storage (AWS S3, Azure Data Lake Storage (ADLS), or Google Cloud Storage (GCS)). This error can prevent data access, break ETL jobs, and cause failures in Unity Catalog, Delta tables, and external data sources.

🚨 Common symptoms of the “Invalid Storage Credentials” error:

• Cannot read or write data from cloud storage.
• Cluster initialization fails due to missing credentials.
• Unity Catalog tables return “Storage Credentials Invalid” error.
• dbutils.fs.mount() fails to mount storage.

This guide walks through troubleshooting steps and solutions to resolve this error for AWS, Azure, and GCP storage in Databricks.

1. Verify Cloud Storage Credentials Are Correct

Symptoms:

• Error: “Invalid credentials: The provided credentials are incorrect or missing.”
• Cloud storage authentication failures in logs.

Causes:

• Incorrect storage access keys, tokens, or IAM role assignments.
• Databricks cluster does not have the required permissions to access storage.
• Storage credentials expired or revoked.

Fix:

✅ Verify the credentials used to access storage:

dbutils.secrets.get(scope="my-secret-scope", key="storage-access-key")

✅ Ensure correct IAM role or access keys are set up for the storage provider (AWS, Azure, or GCP).

2. Fixing “Invalid Storage Credentials” for AWS S3

Symptoms:

• Databricks cannot access S3 buckets.
• Error: “Invalid credentials for AWS S3.”
• Databricks Unity Catalog tables return a “storage credentials invalid” error.

Causes:

• IAM Role assigned to Databricks cluster does not have S3 access.
• S3 bucket policy is misconfigured.
• AWS Access Key and Secret Key are incorrect.

Fix:

✅ Verify IAM Role Permissions for Databricks Cluster:

{
  "Effect": "Allow",
  "Action": [
    "s3:GetObject",
    "s3:PutObject",
    "s3:ListBucket"
  ],
  "Resource": [
    "arn:aws:s3:::my-databricks-bucket",
    "arn:aws:s3:::my-databricks-bucket/*"
  ]
}

✅ Assign IAM Role to Databricks Cluster:

aws iam attach-role-policy --role-name my-databricks-role --policy-arn arn:aws:iam::aws:policy/AmazonS3FullAccess

✅ Ensure Databricks is using the correct credentials:

spark.conf.set("fs.s3a.access.key", "YOUR_ACCESS_KEY")
spark.conf.set("fs.s3a.secret.key", "YOUR_SECRET_KEY")

✅ Test S3 connectivity from Databricks:

dbutils.fs.ls("s3://my-databricks-bucket/")

3. Fixing “Invalid Storage Credentials” for Azure ADLS

Symptoms:

• Databricks cannot access Azure Data Lake (ADLS).
• Error: “Invalid credentials: Access denied to storage account.”
• Unity Catalog fails to access external tables.

Causes:

• Azure Service Principal lacks permissions on ADLS.
• Databricks cluster is not configured with correct authentication.
• Managed Identity permissions missing for ADLS.

Fix:

✅ Ensure Databricks Service Principal has correct Storage Blob Data Reader role:

az role assignment create --assignee <databricks-service-principal> --role "Storage Blob Data Reader" --scope /subscriptions/<sub-id>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage-account>

✅ Configure Databricks to use Azure AD Authentication for ADLS:

spark.conf.set("fs.azure.account.auth.type.<storage-account>.dfs.core.windows.net", "OAuth")
spark.conf.set("fs.azure.account.oauth.provider.type.<storage-account>.dfs.core.windows.net", "org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider")
spark.conf.set("fs.azure.account.oauth2.client.id.<storage-account>.dfs.core.windows.net", "<client-id>")
spark.conf.set("fs.azure.account.oauth2.client.secret.<storage-account>.dfs.core.windows.net", "<client-secret>")
spark.conf.set("fs.azure.account.oauth2.client.endpoint.<storage-account>.dfs.core.windows.net", "https://login.microsoftonline.com/<tenant-id>/oauth2/token")

✅ Test ADLS connectivity from Databricks:

dbutils.fs.ls("abfss://container@storageaccount.dfs.core.windows.net/")

4. Fixing “Invalid Storage Credentials” for Google Cloud Storage (GCS)

Symptoms:

• Databricks cannot access GCS buckets.
• Error: “Invalid credentials: The provided service account key is incorrect.”
• Unity Catalog fails to read external tables stored in GCS.

Causes:

• Databricks does not have the correct service account credentials.
• GCS bucket IAM policy does not allow access.
• Service account key is invalid or expired.

Fix:

✅ Ensure the correct IAM role is assigned to the Databricks service account:

gcloud projects add-iam-policy-binding <project-id> --member="serviceAccount:databricks@my-project.iam.gserviceaccount.com" --role="roles/storage.objectAdmin"

✅ Upload a valid service account key to Databricks and configure access:

spark.conf.set("fs.gs.auth.service.account.enable", "true")
spark.conf.set("google.cloud.auth.service.account.json.keyfile", "/dbfs/gcs-key.json")

✅ Test GCS connectivity from Databricks:

dbutils.fs.ls("gs://my-gcs-bucket/")

5. Fixing “Invalid Storage Credentials” for Unity Catalog External Tables

Symptoms:

• Error: “Unity Catalog external table storage credentials invalid.”
• Cannot read or write to external tables.

Causes:

• Unity Catalog storage credentials are not set up correctly.
• Databricks lacks IAM permissions to access the external storage location.

Fix:

✅ Check Unity Catalog storage credentials:

SHOW STORAGE CREDENTIALS;

✅ If credentials are missing, create them:

CREATE STORAGE CREDENTIAL my_credential
WITH IAM ROLE 'arn:aws:iam::123456789012:role/my-databricks-role';

✅ Grant access to the storage credential:

GRANT USAGE ON STORAGE CREDENTIAL my_credential TO `user@example.com`;

✅ Recreate the external table with correct storage credentials:

CREATE EXTERNAL TABLE my_catalog.my_schema.my_table
LOCATION 's3://my-bucket/path/'
WITH CREDENTIAL my_credential;

6. Verify That Storage Credentials Are Set Correctly in Databricks

Step 1: Check Configured Storage Credentials

spark.conf.get("fs.s3a.access.key")
spark.conf.get("fs.azure.account.key.<storage-account>.blob.core.windows.net")

Step 2: Check If Storage Authentication Is Working

dbutils.fs.ls("s3://my-bucket/")
dbutils.fs.ls("abfss://my-container@my-storage-account.dfs.core.windows.net/")
dbutils.fs.ls("gs://my-gcs-bucket/")

Step 3: Check If Databricks Cluster Has Correct IAM Role

• Verify AWS IAM role, Azure AD permissions, or Google Cloud Service Account is correctly assigned to Databricks.

Conclusion

If you encounter “Invalid Storage Credentials” errors in Databricks, check:
✅ Storage authentication methods (IAM roles, access keys, service accounts).
✅ Databricks cluster permissions for accessing cloud storage.
✅ Unity Catalog external table credentials and IAM policies.
✅ Databricks secrets for storing sensitive credentials securely.

By following these steps, you can resolve storage authentication issues and ensure smooth data access in Databricks.

Mohammad Gufran Jahangir