> ## Documentation Index > Fetch the complete documentation index at: https://docs.getcollate.io/llms.txt > Use this file to discover all available pages before exploring further. # SSIS Connector > Ingest SSIS pipeline metadata, pipeline status, and lineage into Collate. export const ConnectorDetailsHeader = ({name, icon, stage, availableFeatures, unavailableFeatures = [], availableFeaturesCollate = []}) => { const showSubHeading = availableFeatures?.length > 0 || unavailableFeatures?.length > 0 || availableFeaturesCollate?.length > 0; const totalAvailableFeatures = [...availableFeatures || [], ...availableFeaturesCollate || []]; return

{icon &&

}

{name}

{stage}

{showSubHeading &&

Feature List

{totalAvailableFeatures.map(feature =>

✓ {feature}

)} {unavailableFeatures.map(feature =>

✕ {feature}

)}

}

; }; This section provides guides and references to use the SSIS connector. Configure and schedule SSIS metadata workflow from the Collate UI: * [Requirements](#requirements) * [Metadata Ingestion](#metadata-ingestion) * [Troubleshooting](/ai-2-0/connectors/pipeline/ssis/troubleshooting) ## Requirements To extract SSIS metadata, we need the database connection details where the SSIS metadata is stored. * `API` Permission (while creating the user, from **Admin** > **User**) * To retrieve lineage data, make the SSIS package XML files available through a local path or an S3 bucket. ## Metadata Ingestion To ingest metadata from SSIS, you need to create a service connection. The service connects SSIS with Collate. Once you create a service, Collate automatically starts ingesting metadata. ### Step 1: Add New Service 1. In the left navigation, click **Connections**. 2. On the **Connections** page, click **Add New Service**.

### Step 2: Select a Service and Connector From the service type dropdown, select **Pipeline Services**, then click the **SSIS** connector tile. Select Service

### Step 3: Add Service Name and Description * Enter a unique, descriptive **Service Name**. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other SSIS services you are ingesting metadata from. * Optional: Enter a **Description** for the service. Add New Service Name

**Note**: The service name cannot be changed after it is set. ### Step 4: Configure Connection Options Specify where ingestion runs, provide your source credentials, and verify the connection. #### Select Ingestion Runner Select an **Ingestion Runner**: the runner where the ingestion pipeline will execute. Add Name and Select Ingestion Runner

#### Enter Connection Details Enter the connection details for SSIS. The right-hand panel in the UI displays inline help for each field. Configure Service Connection

* **Connection**: SSIS metadata database connection. In terms of `connection` we support the following selections: * **Microsoft SQL Server**: To connect to the SSIS metadata database: * Provide the SQL Server connection credentials including username and password * Specify the database name where SSIS metadata is stored * Enter the host and port for the SQL Server instance * The connector will establish a connection to this database to extract SSIS pipeline metadata To fetch task dependencies and lineage information from your SSIS pipelines, the connector requires access to the SSIS package XML files. You have two options to provide these files: * **Local Path**: Specify the local directory path where your SSIS package files are stored. The connector will read the XML files directly from this location during metadata extraction. **Important**: If you are using the **Local Path** option to provide your SSIS package files, you must run the ingestion workflow through the **CLI** instead of the UI. This is because the ingestion process needs direct access to your local filesystem, which is not available when running ingestion jobs from the UI or server. * **S3 Bucket**: Upload your SSIS project folders containing the package XML files to an S3 bucket. Then, provide the S3 credentials (such as `awsAccessKeyId`, `awsSecretAccessKey`, and region) along with the bucket name in the connector configuration. The connector will retrieve the package files from your S3 storage. Choose the method that best fits your environment to ensure the connector can access the necessary package XML files for comprehensive metadata and lineage extraction. **Note**: When configuring the SSIS connector to extract metadata from S3 storage, you need to upload your SSIS project folders containing all your package files to your S3 bucket. Typically, SSIS organizes projects in a structure like: ``` repos/ project1/ project1/ ... .dtsx files project2/ project2/ ... .dtsx files ``` You should upload the inner project folders (e.g., `project1/project1/`, `project2/project2/`, etc.) into your S3 bucket. For example, if your bucket name is `packages`, the structure in your bucket should look like: ``` packages/ project1/ project1/ ... .dtsx files project2/ project2/ ... .dtsx files ``` It is necessary to provide the same bucket name (e.g., `packages`) along with the credentials for your S3 storage when configuring the connector. **Note**: When configuring the SSIS connector to extract metadata from a **local path**, you need to provide the path up to the directory containing your SSIS project folders. For example, if your projects are organized as: ``` /home/user/repos/ project1/ project1/ ... .dtsx files project2/ project2/ ... .dtsx files ``` You should specify the path up to `/home/user/repos/` in your connector configuration. The connector will recursively scan this directory to locate all SSIS project folders and their package XML files. Ensure that the user running the ingestion workflow has read permissions for the specified local path and all its subdirectories. * **S3 Storage Service**: To connect to the bucket having xml files: * Provide the s3 credentials including awsAccessKeyId and awsSecretAccessKey * Provide the appropriate AWS region (e.g., `us-east-2`) for your S3 bucket. * Specify the endpoint URL for your S3-compatible storage. * It is necessary to provide the bucket name containing the SSIS project folders. #### Test Connection Once the credentials have been added, click on **Test Connection** and **Save** the changes.

### Step 5: Configure Ingestion Options In the **What to Ingest** step, use filter patterns to control which assets Collate ingests from your pipeline service. Filter patterns use regular expressions applied to pipeline names. #### How Filter Patterns Work * **Include**: Add one or more comma-separated regular expressions. Collate ingests only assets whose names match at least one expression. Leave blank to include all assets. * **Exclude**: Add one or more comma-separated regular expressions. Collate skips any asset whose name matches an expression. Leave blank to exclude nothing. Rules match asset names using one of five expressions: * **contains**: matches any name containing the value. For example, `sales` matches `my_sales_data` and `sales_2024`. * **starts with**: matches names beginning with the value. For example, `prod_` matches `prod_db` and `prod_schema`. * **ends with**: matches names ending with the value. For example, `_raw` matches `events_raw` and `logs_raw`. * **is exactly**: matches the exact name only. For example, `analytics` matches only `analytics`. * **matches regex**: matches names using a regular expression. For example, `^prod_.*_v\d+$` matches `prod_events_v1`. When both Include and Exclude are set, Exclude takes priority. **Tip**: Leave the filter pattern empty to ingest all pipelines available in the source. **Filter Options** The Pipeline section includes the following filter options: * **Pipeline**: Controls which pipelines (DAGs, jobs, or workflows) Collate ingests from the source. Each section provides the following controls: * **Scan Mode**: You can choose between the following scan modes: * **Scan all**: Ingests every asset of that type the connector can access. This is the default. * **Only specific**: Enables include rules so only assets matching at least one rule are ingested. * **Exclude system toggle**: Use this toggle to automatically filter out system-reserved names defined by the connector — for example, **Exclude system databases** for the Databases section. * **Always exclude**: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules. * **Preview**: Shows a real-time summary of what will be in scope based on your current rules. * **Include rules** *(available only in **Only specific** mode)*: Click **+ Add** to define a rule. Added rules appear as chips; an asset is included if it matches any rule. **Tip**: If [AutoPilot](/ai-2-0/admin-guide/applications/autopilot) is enabled, lineage between pipeline tasks and data assets is tracked automatically after the first metadata ingestion completes. ### Step 6: Create & Deploy Click **Create & Deploy** to deploy the agent and start the first metadata ingestion run. Collate saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to **Connections** in the left navigation and select your service. ## Configure Metadata Agent and Schedule Ingestion The **Metadata Agent** extracts pipelines, tasks, and other structural metadata from your source and keeps your Collate catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click **Create & Deploy**, Collate automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the **Agents** tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps: 1. In the left navigation, click **Connections** and select your service. 2. Click the **Agents** tab. 3. Click **Add Agent** and select **Metadata** from the dropdown. Add Metadata Agent

For some services, the dropdown is not available and clicking **Add Agent** takes you directly to the agent configuration page. 4. On the **Configure Ingestion** page, do the following and click **Next**. * **Name this Ingestion**: Enter a unique recognizable name for this ingestion pipeline.

* **Agent Setup**: Configure the core parameters for this agent. The following fields are available: | Field | Default | Description | | ---------------------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Ownership Update Mode | replace | Set how owners from source metadata update Pipeline owners. In replace mode, resolved owners from the current source replace existing owners. In append mode, resolved owners are appended to active existing Pipeline owners. | | Db Service Names | — | List of database service names used for lineage resolution. | | Storage Service Names | — | List of storage service names used for lineage resolution. | | Messaging Service Names | — | List of messaging service names used for lineage resolution. | | Status Lookback Days | 1 | Number of days of pipeline run status history to ingest. Only runs within the last N days will be fetched. | | Include Lineage | On | Turn off to stop fetching lineage from pipelines. | | Mark Deleted Pipeline | On | Soft-delete pipelines in Collate when they are removed from the source. Associated entities like lineage are also deleted. | | Include UnDeployed Pipelines | On | Toggle whether un-deployed pipelines should be ingested. If set to false, only deployed pipelines will be ingested. | Agent Setup

* **Filter Patterns**: Apply include or exclude rules to scope which pipelines this agent ingests. These follow the same filter options described in **Step 5**.

* **Scope & Behaviour**: Control what metadata to include and how to handle deletions. Toggle each option on or off based on your needs: | Toggle | Default | Description | | ----------------- | ------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Enable Debug Log | Off | Sets the ingestion log level to DEBUG. Useful for troubleshooting. | | Override Metadata | Off | When on, source values overwrite existing descriptions, tags, owners, and display names in Collate. When off, Collate only updates fields that have no existing value. | | Override Lineage | Off | When on, existing lineage is replaced with newly extracted lineage on each run. | Scope & Behaviour

5. On the **Schedule Interval** page, set when the agent runs: * **Schedule**: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression. * **On-Demand**: No automatic schedule; trigger the agent manually when needed.

6. Click **Add** to deploy the agent. ## Troubleshooting Learn more about how to troubleshoot common SSIS connector issues and resolve configuration or ingestion errors.