> For the complete documentation index, see [llms.txt](https://developer.harness.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.harness.io/database-devops/troubleshooting-and-resources/troubleshooting-guide/troubleshooting.md).

# Troubleshooting Guide

This guide outlines common issues encountered while using Harness Database DevOps and their corresponding solutions.

### searchPath parameter issue <a href="#searchpath-parameter-issue" id="searchpath-parameter-issue"></a>

When working with a changelog file that includes other changelog files, Liquibase might throw an error due to improper handling of file paths. This can occur when the "file" path is not set correctly:

**Error Message**:

![Issue with searchPath](/files/MhKzN9Ocp2ms19U4gNkm)

**Example usage in a master changelog:**

```yaml
## db/changelog/changelog.yaml <a href="#dbchangelogchangelogyaml" id="dbchangelogchangelogyaml"></a>
databaseChangeLog:
  - include:
      file: db/changelog/changes/001-create-users-table.yaml
  - include:
      file: db/changelog/changes/002-add-sample-data.yaml
```

**How to Solve**:

The `searchPath` parameter is used to specify the schema search order for database objects. If the changelog file includes other changelogs, ensure that the paths are correctly specified relative to location of the master changelog file, which is considered the master file.

For example, if the master changelog is located in `db/changelog/master.yaml`, the path to the included changelogs should be relative to that file. Correct example:

```yaml
## db/changelog/changelog.yaml <a href="#dbchangelogchangelogyaml" id="dbchangelogchangelogyaml"></a>
databaseChangeLog:
  - include:
      file: changes/001-create-users-table.yaml
  - include:
      file: changes/002-add-sample-data.yaml
```

This way, Liquibase can correctly resolve the paths to the included changelogs, and the error should be resolved.

{% hint style="info" %}
**IMPORTANT NOTE**

Liquibase uses the full path to the changelog file as part of the identifier of unique change ids. If your changelog has already been applied to an existing database, and your changelog path needs to change, you can add a change of type ''- logicalFilePath: example-changelog.yaml' to specify the path to the changelog that should be used for uniquely identifying change IDs.
{% endhint %}

### changelog.yaml does not exist <a href="#changelogyaml-does-not-exist" id="changelogyaml-does-not-exist"></a>

Liquibase throws this error when it cannot find the changelog file. This can occur when the path is incorrect or the file is missing.

**Error Message**:

![Changelog does not exist](/files/fFI3T6WjlJ51jzZsR2IA)

**How to Solve**:

* Verify that the changelog file exists at the specified location.
* Ensure the filename and path in your configuration exactly match the file in your repository or working directory.
* Cross-check for typos or incorrect directory structures.

### Could not find databaseChangeLog node <a href="#could-not-find-databasechangelog-node" id="could-not-find-databasechangelog-node"></a>

This error comes up when Harness DB DevOps cannot find the `databaseChangeLog` node in the changelog file. This can occur if the file is not formatted correctly or is missing the required node. This issue typically surfaces when the changelog file contains unexpected content.

{% hint style="info" %}
Most common occurrence of this issue will be while setting up DB Schema with a custom script.
{% endhint %}

**Error Message**:

![DatabaseChangeLog does not found](/files/N8cKaOJVl9iMweYJ8x91)

**Example** for such a incorrect custom script:

```sh
if [ ! -d "db" ]; then
  mkdir db
  curl https://api.github.com/repos/Sonichigo/mux-sql/main/liquibase.yml -o db/changelog.yml
fi
```

Above we have an invalid API call to fetch the changelog file, which resulted in an error response, which was mistakenly written to the changelog output file. As a result, instead of a valid changelog XML or YAML, the file contained an error log or HTML/JSON response and when the system attempted to run `Update SQL`, it failed due to the absence of the required `databaseChangeLog` node.

**How to Solve**:

Ensure while fetching the changelog file, you are calling the correct API endpoint and the response is in the expected format. You can also check the contents of the changelog file to ensure it contains the correct `databaseChangeLog` node, after the API call.

**Example** for a correct custom script:

```sh
if [ ! -d "db" ]; then
  mkdir db
  curl -H 'Accept: application/vnd.github.v3.raw' -L https://api.github.com/repos/Sonichigo/mux-sql/contents/liquibase.yml?ref=main -o db/changelog.yml
fi
```

### ImagePullError of alpine/curl:latest <a href="#imagepullerror-of-alpinecurllatest" id="imagepullerror-of-alpinecurllatest"></a>

This error is generally limited to Custom Script steps.

When using the Custom Script step to set up a DB schema in a pipeline with the default image registry (Harness Docker Registry), you may encounter an `ImagePullError` for the `alpine/curl:latest` image. This happens as the image available in the specified default image registry contains only related to Harness Platform.

However, you may also encounter the `ImagePullError` in other steps if your configured image repository does not contain the required out-of-the-box Drone images (e.g., alpine/curl, plugins/git, etc.). In such cases, these base images must be manually added to your image registry.

**Error Message**:

![ImagePullError](/files/yMWZpNWxQncK2jpljKS0)

**How to Solve**:

Ensure you are using the correct container registry for your environment. Go to [Docker Registry connector settings](/harness-ai/use-harness-platform/connectors/cloud-providers/ref-cloud-providers/docker-registry-connector-settings-reference.md) to configure this custom image Registry. Make sure that in the new registry Connector, the `alpine/curl:latest` image is available.

### Authentication error: could not read username <a href="#authentication-error-could-not-read-username" id="authentication-error-could-not-read-username"></a>

While adding a remote repository and pushing changes in a pipeline or shell environment, you may encounter an authentication error. This typically occurs when the credentials for the remote repository are not set up in a specified manner.

**Error Message**:

![Authentication Error](/files/hJwSbM19xtNxnbgpU6q0)

**How to Solve**:

Use a properly formatted Git URL that includes:

* The email address (URL encoded) as the username.
* A secret-based Personal Access Token (PAT) for secure authentication.

**Example** for a properly formatted URL:

```sh
git remote add origin https://my.email%40gmail.com:<+secrets.getValue("PAT_TOKEN")>@gitlab.com/<John_Doe>/changelog.git
git push -u origin main
```

{% hint style="info" %}
**NOTE**

* Replace `my.email@gmail.com` with your Git account email (URL-encoded as %40 for @).
* Replace `PAT_TOKEN` with the name of the Harness secret containing your GitLab PAT.
* Make sure the secret is securely stored in Harness under **Project Settings → Secrets**.
  {% endhint %}

### Rollback behavior for dropTable and dropColumn changesets <a href="#rollback-behavior-for-droptable-and-dropcolumn-changesets" id="rollback-behavior-for-droptable-and-dropcolumn-changesets"></a>

When a dropTable or dropColumn operation is executed and subsequently rolled back, only the schema structure can potentially be recreated, and the original data will not be restored. While it is technically possible to instruct the rollback to recreate the table or column definition, the associated data is permanently lost unless a backup was taken beforehand.

In scenarios involving destructive operations like DROP, the rollback cannot magically recover deleted data. The only viable recovery strategy would be to restore from a database backup taken prior to the drop operation, which still results in some level of data loss and operational risk.

{% hint style="info" %}
**WARNING**

Dropping tables or columns in production environments should be treated with extreme caution. It is highly recommended to adopt a backup-first approach and validate rollback strategies before applying such changes.
{% endhint %}

### Rollback error messages <a href="#rollback-error-messages" id="rollback-error-messages"></a>

This error occurs in PostgreSQL when replication is enabled, and the databasechangelog table (created by Liquibase) has no primary key or replica identity. PostgreSQL requires a replica identity to process DELETE operations during rollback.

**Error Message**: `ERROR: cannot delete from table "databasechangelog" because it does not have a replica identity and publishes deletes.`

**How to Solve**:

Run the following SQL to allow deletes even without a primary key:

```sql
ALTER TABLE databasechangelog REPLICA IDENTITY FULL;
```

This tells PostgreSQL to use the full row for replication tracking. We are planning to update DB DevOps to add a primary key to this table automatically in future versions.

{% hint style="info" %}
**NOTE**

Apply the workaround only if your environment uses logical replication and encounters this error. In non-replicated environments, this issue typically does not occur
{% endhint %}

**Long-Term Fix (Planned):**

We plan to update Harness DB DevOps to include a primary key on the databasechangelog table upon creation to ensure better compatibility with replication-enabled PostgreSQL environments. Until then, applying the above workaround will unblock affected users.

### DB Instance connector cannot be an expression error <a href="#db-instance-connector-cannot-be-an-expression-error" id="db-instance-connector-cannot-be-an-expression-error"></a>

This is by design - features like drift detection depend on resolving the database schema, instance, and connector outside of pipeline execution. To support such functionality, the connector must be fully defined and cannot be referenced as a runtime or expression value.

{% hint style="info" %}
Use a fixed connector when defining your DB Instance in order to enable full DB DevOps capabilities.
{% endhint %}

### Extra memory release version requirement <a href="#extra-memory-release-version-requirement" id="extra-memory-release-version-requirement"></a>

In latest versions, memory is allocated based on your changelog complexity. If your changesets are large in number or size, increase the memory allocation from the default 200 MB to 500 MB to avoid unexpected OOM (Out of Memory) events during changelog parsing and SQL generation.

Go to [Override resource limits](/continuous-integration/use-harness-ci/use-harness-ci/set-up-build-infrastructure/resource-limits.md#override-resource-limits) to update memory allocation in step configuration.

{% hint style="info" %}
**NOTE**

If you are upgrading from any version prior to 1.9.0, ensure your deployment configuration reflects the updated 500 MB memory requirement.
{% endhint %}

### Unexpected resource lock with no database-level locks <a href="#unexpected-resource-lock-with-no-database-level-locks" id="unexpected-resource-lock-with-no-database-level-locks"></a>

In many scenarios, the “lock” you encounter is not a database engine–level lock but a Liquibase changelog lock. Liquibase uses an internal DATABASECHANGELOGLOCK table to coordinate concurrent change executions. If a pipeline fails, times out, or terminates unexpectedly, the lock may remain active even when the underlying database shows no locks.

This residual lock prevents subsequent runs from proceeding until the lock is manually released.

**How to Identify Liquibase Locks:** Liquibase stores the lock state in the DATABASECHANGELOGLOCK table. If the LOCKED column is true, Liquibase considers the schema locked.

**How to Solve:** Use the liquibase step to run the Liquibase command:

```sh
release-locks
```

This clears any stale Liquibase-level locks and restores normal pipeline execution.

### kinit fails with client not found in Kerberos database <a href="#kinit-fails-with-client-not-found-in-kerberos-database" id="kinit-fails-with-client-not-found-in-kerberos-database"></a>

The principal does not exist in the realm, or the realm name is incorrect (case sensitive).

**How to Solve**:

* Verify the principal exists in the KDC/Active Directory.
* Verify the principal format: `user@REALM`
* Ensure the realm is uppercase (e.g., DBDEMO.ORG)
* Regenerate the keytab if necessary

### Connection fails despite kinit succeeding <a href="#connection-fails-despite-kinit-succeeding" id="connection-fails-despite-kinit-succeeding"></a>

`kinit` only proves that the principal is valid. The database connection requires a properly registered SPN.

**How to Solve**:

* Verify SPN registration in AD
  * MSSQL format: `MSSQLSvc/hostname:1433@REALM`
  * Oracle format: `oracle/hostname@REALM`
* Ensure the hostname in the JDBC URL matches the SPN
* Avoid using IP addresses in JDBC URLs

### Clock skew too great errors <a href="#clock-skew-too-great-errors" id="clock-skew-too-great-errors"></a>

This error occurs when there is a significant time difference between the client machine (where kinit is run) and the KDC/AD server. Kerberos requires synchronized time for ticket validation.

### Delegate fails to resolve the KDC server <a href="#delegate-fails-to-resolve-the-kdc-server" id="delegate-fails-to-resolve-the-kdc-server"></a>

This can occur if the Delegate's DNS configuration cannot resolve the KDC hostname specified in krb5.conf.

**How to Solve**:

* Validate resolution using: `nslookup dc1.dbdemo.org`
* Ensure the Delegate has proper DNS settings to resolve the KDC hostname.

### No Kerberos credentials available error <a href="#no-kerberos-credentials-available-error" id="no-kerberos-credentials-available-error"></a>

This error indicates that the Kerberos credentials obtained via `kinit` are not accessible to the pipeline execution environment. The TGT was not generated, expired, or is not accessible to the JVM process.

**How to Solve**: Ensure the keytab is mounted at the correct path and the path is correctly referenced in the Delegate YAML configuration. Then restart the Delegate to pick up the new credentials. Also, confirm that the environment variables for Kerberos are set correctly in the Delegate configuration.

### Oracle Kerberos authentication fails while MSSQL works <a href="#oracle-kerberos-authentication-fails-while-mssql-works" id="oracle-kerberos-authentication-fails-while-mssql-works"></a>

Oracle has additional **server-side requirements** for Kerberos authentication, such as correct `sqlnet.ora` configuration and correct keytab usage. Whereas, MSSQL is often more straightforward to set up for Kerberos.

### Connection works locally but fails in Harness <a href="#connection-works-locally-but-fails-in-harness" id="connection-works-locally-but-fails-in-harness"></a>

This is often due to differences in the environment where `kinit` is executed and where the pipeline runs. The local environment may have access to Kerberos credentials, while the pipeline environment does not.

**How to Solve**:

* Compare `krb5.conf` files
* Confirm mounted keytab path inside Delegate container
* Validate environment variables in Delegate YAML
* Ensure network policies allow traffic to KDC and database

### ORA-12514 TNS listener error with Oracle Kerberos <a href="#ora-12514-tns-listener-error-with-oracle-kerberos" id="ora-12514-tns-listener-error-with-oracle-kerberos"></a>

This error indicates that the Oracle listener does not recognize the service name specified in the JDBC URL.

**How to Solve**: Either incorrect service name is specified in the JDBC URL or the Oracle listener is configured to listen on the correct port. Verify the service name in the JDBC URL matches the one registered with the Oracle listener. Also, ensure the listener is running and configured to accept connections for that service.

### Oracle encryption type for Kerberos keytab entry <a href="#oracle-encryption-type-for-kerberos-keytab-entry" id="oracle-encryption-type-for-kerberos-keytab-entry"></a>

Oracle requires `aes256-cts-hmac-sha1-96` and `aes128-cts-hmac-sha1-96` as the encryption type for modern oracle versions. Older version of Oracle also support `rc4-hmac` encryption type, but Oracle has deprecated this encryption type in modern versions due to RC4's known cryptographic weaknesses.

### Spanner connection fails or does not establish <a href="#spanner-connection-fails-or-does-not-establish" id="spanner-connection-fails-or-does-not-establish"></a>

* Ensure Workload Identity is enabled on your GKE cluster.
* Verify the Kubernetes Service Account (KSA) is correctly annotated with the GCP Service Account
* Confirm the required IAM roles are assigned to the GCP Service Account (GSA)

### Permission or access denied errors <a href="#permission-or-access-denied-errors" id="permission-or-access-denied-errors"></a>

Check that the roles/iam.workloadIdentityUser binding is correctly configured and then validate that the GSA has the required database IAM roles (e.g., `roles/spanner.databaseUser`, `roles/spanner.databaseAdmin`)

### Intermittent or unreliable pipeline executions <a href="#intermittent-or-unreliable-pipeline-executions" id="intermittent-or-unreliable-pipeline-executions"></a>

* Scale up the Harness Delegate replicas to handle load
* Increase CPU and memory resources allocated to the delegate
* Ensure the delegate remains consistently connected and healthy

### Connection failure <a href="#connection-failure" id="connection-failure"></a>

The connection will fail if Workload Identity not enabled or missing KSA annotation/IAM roles on GSA.

### Permission errors <a href="#permission-errors" id="permission-errors"></a>

Either there is missing `roles/iam.workloadIdentityUser` or Incorrect database IAM roles

### BigQuery access denied error with OIDC <a href="#bigquery-access-denied-error-with-oidc" id="bigquery-access-denied-error-with-oidc"></a>

This error indicates that the service account used for OIDC authentication does not have the required BigQuery IAM roles.

**How to Solve**:

* Verify that the service account has `roles/bigquery.dataViewer` or `roles/bigquery.admin` for dataset access.
* Ensure the service account has `roles/bigquery.jobUser` to run queries and schema operations.
* Confirm the service account has `roles/iam.serviceAccountTokenCreator` for OIDC token exchange.
* Check that the Workload Identity Pool binding includes the service account with `roles/iam.workloadIdentityUser`.

**Verify roles:**

```bash
gcloud projects get-iam-policy PROJECT_ID \
  --flatten="bindings[].members" \
  --filter="bindings.members:serviceAccount:SA_EMAIL"
```

### BigQuery OIDC token exchange failure <a href="#bigquery-oidc-token-exchange-failure" id="bigquery-oidc-token-exchange-failure"></a>

The OIDC token exchange follows a two-step process. Failures can occur at either step.

**How to Solve**:

**Step 1 failure (Harness JWT to GCP Workload Access Token):**

* Ensure `sts.googleapis.com` (Security Token Service API) is enabled in your GCP project.
* Verify the Workload Identity Pool and Provider are configured with the correct Harness issuer URL.
* Check that the attribute mapping includes `google.subject = assertion.sub`.
* Confirm the pool conditions filter by `account_id` only (not pipeline-specific attributes).

**Step 2 failure (Workload Token to Service Account Access Token):**

* Ensure `iamcredentials.googleapis.com` (IAM Service Account Credentials API) is enabled.
* Verify the service account has `roles/iam.serviceAccountTokenCreator` bound to itself:

  ```bash
  gcloud iam service-accounts add-iam-policy-binding SA_EMAIL \
    --project=PROJECT_ID \
    --role="roles/iam.serviceAccountTokenCreator" \
    --member="serviceAccount:SA_EMAIL"
  ```

### BigQuery dataset not found error with OIDC <a href="#bigquery-dataset-not-found-error-with-oidc" id="bigquery-dataset-not-found-error-with-oidc"></a>

This error occurs when the BigQuery dataset specified in the JDBC URL does not exist or the service account does not have access to it.

**How to Solve**:

* Verify the `DefaultDataset` parameter in your JDBC URL matches an existing BigQuery dataset in your project.
* Ensure the `Location` parameter matches the dataset region (for example, `us-central1`, `asia-south1`).
* Check that the service account has access to the specified dataset:

  ```bash
  bq show --format=prettyjson PROJECT_ID:DATASET_NAME
  ```
* For dataset-level permissions, grant access explicitly:

  ```bash
  bq update --dataset \
    --add_iam_binding_member="serviceAccount:SA_EMAIL" \
    --add_iam_binding_role="roles/bigquery.dataViewer" \
    PROJECT_ID:DATASET_NAME
  ```

### BigQuery pipeline fails with invalid JDBC URL <a href="#bigquery-pipeline-fails-with-invalid-jdbc-url" id="bigquery-pipeline-fails-with-invalid-jdbc-url"></a>

This error occurs when the BigQuery JDBC URL format is incorrect or contains invalid parameters for OIDC authentication.

**How to Solve**:

* Ensure your JDBC URL follows the correct format:

  ```bash
  jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;ProjectId=PROJECT_ID;DefaultDataset=DATASET;Location=REGION;
  ```
* Do not include `OAuthType` or `OAuthAccessToken` parameters when using OIDC authentication. The access token is injected automatically by Harness.
* Verify all required parameters are present:
  * `ProjectId`: Your GCP project ID
  * `DefaultDataset`: Target BigQuery dataset
  * `Location`: Dataset region
* Check for syntax errors (missing semicolons, incorrect parameter names).

### BigQuery connection test succeeds but pipeline execution fails <a href="#bigquery-connection-test-succeeds-but-pipeline-execution-fails" id="bigquery-connection-test-succeeds-but-pipeline-execution-fails"></a>

Connection tests and pipeline executions generate OIDC tokens with different custom attributes. This can cause authentication to work in one context but fail in the other.

**How to Solve**:

* Ensure your Workload Identity Pool attribute conditions accept both connector validation and pipeline execution contexts.
* The pool conditions should filter by `account_id` only, not by pipeline-specific attributes like `org_id`, `project_id`, or `pipeline_id`.
* Update the attribute condition in the service account's IAM policy:

  ```
  attribute.account_id = "YOUR_HARNESS_ACCOUNT_ID"
  ```
* Avoid overly restrictive conditions that might block pipeline execution tokens.

### BigQuery API not enabled error <a href="#bigquery-api-not-enabled-error" id="bigquery-api-not-enabled-error"></a>

This error occurs when the BigQuery API is not enabled in your GCP project.

**How to Solve**: Enable the required GCP APIs for BigQuery with OIDC authentication:

```bash
gcloud services enable bigquery.googleapis.com \
  iamcredentials.googleapis.com \
  sts.googleapis.com \
  --project=YOUR_PROJECT_ID
```

Verify the APIs are enabled:

```bash
gcloud services list --enabled --project=YOUR_PROJECT_ID | grep -E 'bigquery|iamcredentials|sts'
```

### DB DevOps pipelines falsely queued on resource constraint locks <a href="#db-devops-pipelines-falsely-queued-on-resource-constraint-locks" id="db-devops-pipelines-falsely-queued-on-resource-constraint-locks"></a>

When executing DB DevOps pipelines that utilize dynamic resource constraint locks (e.g., schema or instance-level locks), the pipeline fails or remains indefinitely queued with the following message:

**Error Message:** `Current execution is queued as another execution is running with given resource key.`

This occurs even when no other active pipeline runs are targetting or executing against the specified database instance or schema.

Because the key was encoded before variable resolution, the pipeline engine failed to resolve dynamic Harness expressions, such as `<+stage.variables.schema>` or target instance identifiers at runtime. Consequently, the literal expression string was evaluated as a fixed static lock key across all pipeline executions, causing unrelated pipeline runs to block one another under a single shared lock key.

**Resolution**: This issue is resolved automatically in `db-devops-service` in version `1.111.0` and above. Ensure your environment is running `db-devops-service` 1.111.x and that `ng-manager` has been upgraded to `v1.160.0`.

### AI impact analysis conditional approval <a href="#ai-impact-analysis-conditional-approval" id="ai-impact-analysis-conditional-approval"></a>

The following issues apply to the Database Impact Analysis agent step and its conditional approval pattern.

#### Approval step runs when agent returned PASS <a href="#approval-step-runs-when-agent-returned-pass" id="approval-step-runs-when-agent-returned-pass"></a>

**Cause:** The conditional execution expression does not exactly match the output variable path.

**How to Solve:**

* Verify that the step group identifier, agent step identifier, and variable name in the condition expression are correct and match what is configured in the pipeline.
* Expression references are case-sensitive. For example, `Preview_SQL` and `preview_sql` are different identifiers.
* Confirm the full path follows the pattern:

  ```bash
  <+execution.steps.<StepGroupId>.steps.<AgentStepId>.steps.agent.output.outputVariables.VALIDATION_STATUS>!="PASS"
  ```

#### Agent step fails with missing SQL input or empty sqlCommands <a href="#agent-step-fails-with-missing-sql-input-or-empty-sqlcommands" id="agent-step-fails-with-missing-sql-input-or-empty-sqlcommands"></a>

**Cause:** The expression referencing the Preview SQL step output is incorrect, or the Preview SQL step did not complete successfully.

**How to Solve:**

* Confirm that the Preview SQL step completed without errors before the agent step runs.
* Verify the `sqlCommands` expression uses the correct step group identifier and step identifier from the Preview SQL step:

  ```bash
  <+execution.steps.<StepGroupId>.steps.<PreviewSQLStepId>.output.sqlCommands>
  ```
* Check that both the Preview SQL step and the agent step are inside the same step group.

#### Approval message shows blank SUMMARY or raw SQL <a href="#approval-message-shows-blank-summary-or-raw-sql" id="approval-message-shows-blank-summary-or-raw-sql"></a>

**Cause:** The expression path for `SUMMARY` or `sqlCommands` in the approval message is incorrect or incomplete.

**How to Solve:**

* The `SUMMARY` variable requires the full stage path, including the stage identifier, step group identifier, and agent sub-step:

  ```bash
  <+pipeline.stages.<StageId>.spec.execution.steps.<StepGroupId>.steps.<AgentStepId>.steps.agent.output.outputVariables.SUMMARY>
  ```
* The raw SQL expression uses the shorter execution-scoped path:

  ```bash
  <+execution.steps.<StepGroupId>.steps.<PreviewSQLStepId>.output.sqlCommands>
  ```
* Go to [AI-powered SQL impact analysis with conditional approval](/database-devops/use-db-devops/governance-and-compliance/ai-impact-analysis-pipeline.md) to review the full expression examples.

### Next steps <a href="#next-steps" id="next-steps"></a>

* Go to [Set up JDBC connectors](/database-devops/setup-db-devops/jdbc-connection-string/set-up-connectors.md) to verify connector configuration for connection issues.
* Go to [Rollback for database schemas](/database-devops/use-db-devops/deployment-pipeline-configuration/rollback-and-failure-strategies/rollback-for-database-schemas.md) to configure rollback strategies for failed deployments.