This document lists the visible errors captured and surfaced by Data Agent Kit extension for VS Code. These errors are typically shown as Notifications (pop-ups) or as Status Bar Warnings in the IDE. Use this guide to identify and resolve issues.
If you're not able to identify the source of an issue after reviewing the possible error listed here, try signing out and signing back in.
Authentication and gcloud CLI errors
These errors impact the foundational connectivity of the extension.
Error message |
Possible cause |
Remediation |
|---|---|---|
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The |
Install the Google Cloud CLI and restart VS Code. |
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Click the status bar or notification to trigger the login flow in the terminal. |
Status bar shows a |
The logged-in extension account differs from the active gcloud CLI account. |
Run |
Status bar shows a |
Extension settings such as project ID, region, or billing project ID don't match gcloud CLI settings. |
Click the warning icon in the project status bar to synchronize settings between the extension and the gcloud CLI. Alternatively, manually update the configurations in either tool to ensure they match. |
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Attempting to sync settings while accounts are inconsistent. |
Align accounts between the gcloud CLI and the extension. Ensure that they are using the same user account, project, region, and billing project. |
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Attempting to sync settings while the gcloud CLI isn't installed. |
Install the gcloud CLI. |
Explorer and API fetching errors
The following are general errors encountered when browsing cloud resources in the Google Cloud Data Agent Kit menu tree.
Error message |
Possible cause |
Remediation |
|---|---|---|
|
The server can't authorize your request ( |
Verify Identity and Access Management (IAM) permissions; ensure the relevant API, such as BigQuery, is enabled in settings. |
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A feature was triggered without an active project. |
Use the project picker in the status bar to select a project. |
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Incorrect naming convention (missing project ID or dataset ID). |
Use the fully qualified name: |
BigQuery and Dataform errors
The following errors are specific to SQL transformations and Dataform project management.
Error message |
Possible cause |
Remediation |
|---|---|---|
|
The |
Click Install Dataform CLI in the dialog to automate installation. |
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Syntax errors in |
Check the Dataform |
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BigQuery job execution failure. |
Review the BigQuery job history for detailed execution logs. |
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The Knowledge Catalog or BigQuery entry exists but has NoSQL content. |
Verify the query content by running it in the Google Cloud console. |
Managed Service for Apache Spark and Spark errors
The following errors are related to cluster management and Spark execution.
Error message |
Possible cause |
Remediation |
|---|---|---|
|
Insufficient IAM permissions or cluster in transition. |
Ensure you have the |
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Internal reference error in the tree view. |
Refresh the Spark Resource Explorer view. |
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Cluster is stopped or Component Gateway is disabled. |
Start the cluster and ensure Component Gateway is enabled in the cluster configuration. |
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API error |
Refresh the Spark Resource Explorer view. |
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Local Jupyter server startup failed or installation of required packages failed. |
Open a new Spark Notebook with the remote kernel. |
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Sample notebooks for the selected kernel type (local or remote) are not available. |
Not applicable |
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This is specifically for Windows users when long paths are not enabled on your machine. |
Enable long paths by referring to the link in the notification. |
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This comes up when the user tries to use a remote kernel for the first time. |
Install dependencies by clicking the notification and selecting Yes in the confirmation dialog. |
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Shown in the kernel picker description next to Remote Kernel if Jupyter dependencies are missing. |
Install dependencies by clicking the notification and selecting Yes in the confirmation dialog. |
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Shown in the kernel picker description when user runs an existing notebook on Remote Kernel |
Install dependencies by clicking the notification and selecting Yes in the confirmation dialog. |
Cloud Storage errors
The following errors are surfaced while managing buckets and objects.
Error message |
Possible cause |
Remediation |
|---|---|---|
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Naming collision in the bucket. |
Choose a unique folder name. |
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Permission denied or network timeout. |
Verify |
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Name already taken globally or invalid characters. |
Generic interface errors
These errors indicate UI-level failures.
Error message |
Possible cause |
Remediation |
|---|---|---|
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User is in No Folder mode in VS Code. |
Open a folder using |
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You are running Spark or SQL commands without an open notebook. |
Open a |
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Attempting to drag-and-drop a resource that has NoSQL string representation. |
Only tables, views, and columns can be inserted into editors. |
Database errors
The following errors are returned when querying Google Cloud databases.
AlloyDB
Error message |
Possible cause |
Remediation |
|
The user logged into the extension has not been added as an IAM user to the instance. |
See Manage IAM authentication to add the user as an IAM user. |
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The IAM user does not have permission for the object. |
See Grant appropriate database permissions to IAM users to grant permission to the IAM user for the object. |
Cloud SQL for MySQL
| Error message | Possible cause | Remediation |
|---|---|---|
Invalid request: Some of your SQL statements failed to execute.
Details: Error 1045 (28000): Access denied for user '[USER]'@'localhost'
(using password: YES). |
The user logged into the extension has not been added as an IAM user to the instance. | See IAM authentication to add the user as an IAM user for the instance. |
Invalid request: Some of your SQL statements failed to execute.
Details: Error 1044 (42000): Access denied for user '[USER]'@'%' to
database '[DB_NAME]'. |
The IAM user does not have permission to access the database. | See Grant database privileges to an individual IAM user or service account to grant privileges to IAM users for the database. |
Invalid request: The instance doesn't allow using ExecuteSql to
access this instance. You can allow it by patching the instance with
{settings: { dataApiAccess: "ALLOW_DATA_API" }}. |
Data API access is not enabled. | Enable Data API access from the query settings or see Execute SQL statements using the Cloud SQL Data API to enable it from the Google Cloud console or gcloud CLI. |
Invalid request: IAM authentication is not
enabled for the instance [PROJECT_ID]:[INSTANCE_NAME]. |
The IAM authentication flag is not enabled. | Enable the IAM authentication flag from the query settings or see IAM authentication to enable it from the Google Cloud console or gcloud CLI. |
Cloud SQL for PostgreSQL
| Error message | Possible cause | Remediation |
|---|---|---|
Invalid request: The instance doesn't allow using ExecuteSql to
access this instance. You can allow it by patching the instance with
{settings: { dataApiAccess: "ALLOW_DATA_API" }}. |
The Data API Access is not enabled. | Enable Data API access from the query settings or see Execute SQL statements using the Cloud SQL Data API to enable it from the Google Cloud console or gcloud CLI. |
Invalid request: IAM authentication is not
enabled for the instance [PROJECT_ID]:[INSTANCE_NAME]. |
The IAM authentication flag is not enabled. | Enable the IAM authentication flag from the query settings or see IAM authentication to enable it from the Google Cloud console or gcloud CLI. |
Invalid request: Some of your SQL statements failed to execute.
Details: pq: password authentication failed for user
"[USER_EMAIL]". |
The user logged into the extension has not been added as an IAM user to the instance. | See IAM authentication to add the user as an IAM user for the instance. |
Execution failed. All statements are aborted. Details: pq:
permission denied for table [TABLE_NAME] |
The IAM user does not have permission to access the object. | See Manage users with IAM database authentication to grant privileges to IAM users for the database. |
Spanner
Error message |
Possible cause |
Remediation |
|---|---|---|
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Result sizes larger than 10.00 MiB are not supported. |
See
|