Troubleshoot

Run the gcloud sql operations list command to list all operations for the given Cloud SQL instance.

Look in the logs and filter by text to find the user. You may need to use audit logs for private information. Relevant log files include:

• cloudsql.googleapis.com/sqlagent.out
• cloudsql.googleapis.com/sqlserver.err
• If Cloud Audit Logs is enabled and you have the required permissions to view them, cloudaudit.googleapis.com/activity may also be available.

After an instance is purged, no data recovery is possible. However, if the instance is restored, then its backups are also restored. For more information on recovering a deleted instance, see Recovery backups.

If you have done an export operation, create a new instance and then do an import operation to recreate the database. Exports are written to Cloud Storage and imports are read from there.

If you really need to cancel the operation, you can ask customer support to force restart the instance.

Create the database users before restoring the SQL dump.

To keep backups indefinitely, you can create an on-demand backup, as they are not deleted in the same way as automated backups. On-demand backups remain indefinitely. That is, they remain until they're deleted or the instance they belong to is deleted. Because that type of backup is not deleted automatically, it can affect billing.

Remove all Authorized Networks entries from the Cloud SQL instance if you can. Otherwise, create a replica without any Authorized Networks entries.

You're trying to use the Google Cloud console to clone an instance with a private IP address, but you didn't specify the allocated IP range that you want to use and the source instance isn't created with the specified range. As a result, the cloned instance is created in a random range.

Use gcloud to clone the instance and provide a value for the
--allocated-ip-range-name parameter. For more information, see Cloning an instance with a private IP.

• Networking instability.
• No response to TCP keep-alive commands (either the client or the server isn't responsive, possibly overloaded)
• The database engine connection lifetime was exceeded and the server ends the connection.

Applications must tolerate network failures and follow best practices such as connection pooling and retrying. Most connection poolers catch these errors where possible. Otherwise the application must either retry or fail gracefully.

For connection retry, we recommend the following methods:

1. Exponential backoff. Increase the time interval between each retry, exponentially.
2. Add randomized backoff also.

Combining these methods helps reduce throttling.

You could build your own automated export system using Google Cloud products such as Cloud Scheduler, Pub/Sub, and Cloud Run functions, similar to this article on automating backups.

To see how to update an instance's time zone, see Instance settings.

In Cloud SQL for SQL Server, you can use the AT TIME ZONE function for time conversions and more. For more information about this function, see AT TIME ZONE (Transact-SQL).

Edit the instance to upgrade to a larger machine size to get more CPUs and memory.

Close unused operations. Check the CPU and memory usage of your Cloud SQL instance to make sure there are plenty of resources available. The best way to ensure maximum resources for the import is to restart the instance before beginning the operation.

A restart:

• Closes all connections.
• Ends any tasks that may be consuming resources.

Create the database users before importing.

EXEC sp_serveroption
    @server='LINKED_SERVER_NAME',
    @optname='data access',
    @optvalue='TRUE'

Replace LINKED_SERVER_NAME with the name of the linked server.

EXEC master.dbo.sp_addlinkedserver
   @server = N'LINKED_SERVER_NAME',
   @srvproduct= N'',
   @provider= N'SQLNCLI',
   @datasrc= N'TARGET_SERVER_ID',
   @provstr= N'Encrypt=yes;TrustServerCertificate=yes;User ID=USER_ID'

Replace the following:

• LINKED_SERVER_NAME with the name of the linked server.
• TARGET_SERVER_ID with the name of the target server, or the IP address and port number for the target server.
• USER_ID with the user logging in.

For example, a user was deleted but you can't find out who did it. The logs show the operation started but don't provide any more information. You must enable audit logging for detailed and personal identifying information (PII) like this to be logged.

To download the logs as JSON:

gcloud logging read \
"resource.type=cloudsql_database \
AND logName=projects/PROJECT_ID \
/logs/cloudsql.googleapis.com%2FLOG_NAME" \
--format json \
--project=PROJECT_ID \
--freshness="1d" \
> downloaded-log.json
    

To download the logs as TEXT:

gcloud logging read \
"resource.type=cloudsql_database \
AND logName=projects/PROJECT_ID \
/logs/cloudsql.googleapis.com%2FLOG_NAME" \
--format json \
--project=PROJECT_ID \
--freshness="1d"| jq -rnc --stream 'fromstream(1|truncate_stream(inputs)) \
| .textPayload' \
--order=asc
> downloaded-log.txt
   

Restart deletes the temporary files but not reduce the storage. Only customer support can reset the instance size.

Look in the logs around the time of the deletion and see if there's a rogue script running from a dashboard or another automated process.

Some possible explanations include:

• Another operation is in progress. Cloud SQL operations do not run concurrently. Wait for the other operation to complete.
• The INSTANCE_RISKY_FLAG_CONFIG warning is triggered whenever at least one beta flag is being used. Remove the risky flag settings and restart the instance

Unfortunately, you can't shrink the ibtmp1 file by any method other than restarting the service.

One mitigation option is to create the temporary table with ROW_FORMAT=COMPRESSED, so it is stored in file-per-table tablespaces in the temporary file directory. However, the downside is performance costs associated with creating and removing a file-per-table tablespace for each temporary table.

If your instance runs out of storage, and the automatic storage increase capability isn't enabled, your instance goes offline. To avoid this issue, you can edit the instance to enable automatic storage increase.

By having connections that last less than 60 seconds, most unclean shutdowns can be avoided, including connections from the database command prompt. If you keep these connections open for hours or days, shutdowns can be unclean.

Find out which objects are dependent on the user, then drop or reassign those objects to a different user.

Refer to general performance tips in particular.

For slow database inserts, updates, or deletes, consider the following actions:

• Check the locations of the writer and database; sending data a long distance introduces latency.
• Check the location of the reader and database; latency affects read performance even more than write performance

To reduce the latency the recommendation is to locate both the source and destination resources in the same region.

There are other factors beside your workload that can impact memory usage, such as the number of active connections and internal overhead processes. These aren't always reflected in the monitoring charts.

Ensure that the instance has enough overhead to account for your workload plus some additional overhead.

To preserve your data, export it to Cloud Storage before you delete an instance.

The Cloud SQL Admin role includes the permission to delete the instance. To prevent accidental deletion, grant this role only as needed.

There are other ways to accomplish the goal by creating a new instance.

• You can clone the instance you want to rename and set a new name for the cloned instance. This allows you to create the new instance without having to import data manually. Just as when creating a new instance, the cloned instance has a new IP address.
• You can export data from your instance into a Cloud Storage bucket, create a new instance with the new name you want, and then import the data into the new instance.

In both cases, you can delete your old instance after the operation is done. We recommend going with the cloning route since it has no impact on performance and doesn't require you to redo any instance configuration settings such as flags, machine type, storage size and memory.

1. Check the endpoint's status.

   gcloud

   To check the status, use the
   gcloud compute forwarding-rules describe command.

   gcloud compute forwarding-rules describe ENDPOINT_NAME \
   --project=PROJECT_ID \
   --region=REGION_NAME \
   | grep pscConnectionStatus

   Make the following replacements:

   • ENDPOINT_NAME: the name of the endpoint
   • PROJECT_ID: the ID or project number of the Google Cloud project that contains the endpoint
   • REGION_NAME: the region name for the endpoint

   REST

   Before using any of the request data, make the following replacements:

   • PROJECT_ID: the ID or project number of the Google Cloud project that contains the Private Service Connect endpoint
   • REGION_NAME: the name of the region
   • ENDPOINT_NAME: the name of the endpoint

   HTTP method and URL:

   GET https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME/forwardingRules/ENDPOINT_NAME

   To send your request, expand one of these options:

   curl (Linux, macOS, or Cloud Shell)

   Execute the following command:

   curl -X GET \
        -H "Authorization: Bearer $(gcloud auth print-access-token)" \
        "https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME/forwardingRules/ENDPOINT_NAME"

   PowerShell (Windows)

   Execute the following command:

   $cred = gcloud auth print-access-token
   $headers = @{ "Authorization" = "Bearer $cred" }
   
   Invoke-WebRequest `
       -Method GET `
       -Headers $headers `
       -Uri "https://compute.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME/forwardingRules/ENDPOINT_NAME" | Select-Object -Expand Content

   You should receive a JSON response similar to the following:

   {
     "kind": "compute#forwardingRule",
     "id": "ENDPOINT_ID",
     "creationTimestamp": "2024-05-09T12:03:21.383-07:00",
     "name": "ENDPOINT_NAME",
     "region": "https://www.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME",
     "IPAddress": "IP_ADDRESS",
     "target": "https://www.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME/serviceAttachments/SERVICE_ATTACHMENT_NAME",
     "selfLink": "https://www.googleapis.com/compute/v1/projects/PROJECT_ID/regions/REGION_NAME/forwardingRules/ENDPOINT_NAME",
     "network": "https://www.googleapis.com/compute/v1/projects/PROJECT_ID/global/networks/default",
     "serviceDirectoryRegistrations": [
       {
         "namespace": "goog-psc-default"
       }
     ],
     "networkTier": "PREMIUM",
     "labelFingerprint": "LABEL_FINGERPRINT_ID",
     "fingerprint": "FINGERPRINT_ID",
     "pscConnectionId": "CONNECTION_ID",
     "pscConnectionStatus": "ACCEPTED",
     "allowPscGlobalAccess": true
   }
   

2. Verify that the status of the endpoint is ACCEPTED. If the status is PENDING, then the instance isn't allowing the Google Cloud project that contains the endpoint. Make sure that the network project in which the endpoint is created is allowed. For more information, see Edit an instance with Private Service Connect enabled.

First, check that the value of the max_connections flag is greater than or equal to the value on the primary.

If the max_connections flag is set appropriately, inspect the logs in Cloud Logging to find the actual error.

If the error is: set Service Networking service account as servicenetworking.serviceAgent role on consumer project, then disable and re-enable the Service Networking API. This action creates the service account necessary to continue with the process.

Restart the replica instance to reclaim the temporary memory space.

Edit the instance to enable automatic storage increase.

• Slow queries on the replica. Find and fix them.
• Queries like DELETE ... WHERE field < 50000000 cause replication lag with row-based replication since a huge number of updates are piled up on the replica.

Some possible solutions include:

• Edit the instance to increase the size of the replica.
• Reduce the load on the database.
• Send read traffic to the read replica.
• Index the tables.
• Identify and fix slow write queries.
• Recreate the replica.

Recreate the replica after stopping all running queries.