Entries: We need to add a list of entries. Each inner JSON structure will be ingested as a child container of the top-level one. In this case, we will be ingesting 4 children.

Simple Container: The simplest container we can have would be structured, but without partitions. Note that we still need to bring information about:

• dataPath: Where we can find the data. This should be a path relative to the top-level container.
• structureFormat: What is the format of the data we are going to find. This information will be used to read the data.
• separator: Optionally, for delimiter-separated formats such as CSV, you can specify the separator to use when reading the file. If you don't, we will use , for CSV and /t for TSV files.

After ingesting this container, we will bring in the schema of the data in the dataPath.

Partitioned Container: We can ingest partitioned data without bringing in any further details.

By informing the isPartitioned field as true, we'll flag the container as Partitioned. We will be reading the source files schemas', but won't add any other information.

Single-Partition Container: We can bring partition information by specifying the partitionColumns. Their definition is based on the JSON Schema definition for table columns. The minimum required information is the name and dataType.

When passing partitionColumns, these values will be added to the schema, on top of the inferred information from the files.

Multiple-Partition Container: We can add multiple columns as partitions.

Note how in the example we even bring our custom displayName for the column dataTypeDisplay for its type.

Again, this information will be added on top of the inferred schema from the data files.

Unstructured Container: OpenMetadata supports ingesting unstructured files like images, pdf's etc. We support fetching the file names, size and tags associates to such files.

In case you want to ingest a single unstructured file, then just specifying the full path of the unstructured file in datapath would be enough for ingestion.

In case you want to ingest all unstructured files with a specific extension for example pdf & png then you can provide the folder name containing such files in dataPath and list of extensions in the unstructuredFormats field.

In case you want to ingest all unstructured files with irrespective of their file type or extension then you can provide the folder name containing such files in dataPath and ["*"] in the unstructuredFormats field.

The fields shown above (dataPath, structureFormat, isPartitioned, etc.) are still valid.

Container Name: Since we are using a single manifest for all your containers, the field containerName will help us identify which container (or Bucket in S3, etc.), contains the presented information.

• Client ID: This is the unique identifier for your application registered in Azure AD. It’s used in conjunction with the Client Secret to authenticate your application.

• Client Secret: A key that your application uses, along with the Client ID, to access Azure resources.

1. Log into Microsoft Azure.
2. Search for App registrations and select the App registrations link.
3. Select the Azure AD app you're using for this connection.
4. Under Manage, select Certificates & secrets.
5. Under Client secrets, select New client secret.
6. In the Add a client secret pop-up window, provide a description for your application secret. Choose when the application should expire, and select Add.
7. From the Client secrets section, copy the string in the Value column of the newly created application secret.

• Tenant ID: The unique identifier of the Azure AD instance under which your account and application are registered.

To get the tenant ID, follow these steps:

1. Log into Microsoft Azure.
2. Search for App registrations and select the App registrations link.
3. Select the Azure AD app you're using for Power BI.
4. From the Overview section, copy the Directory (tenant) ID.

• Account Name: The name of your ADLS account.

Here are the step-by-step instructions for finding the account name for an Azure Data Lake Storage account:

1. Sign in to the Azure portal and navigate to the Storage accounts page.
2. Find the Data Lake Storage account you want to access and click on its name.
3. In the account overview page, locate the Account name field. This is the unique identifier for the Data Lake Storage account.
4. You can use this account name to access and manage the resources associated with the account, such as creating and managing containers and directories.

• Key Vault: Azure Key Vault serves as a centralized secrets manager, securely storing and managing sensitive information, such as connection strings and cryptographic keys.

The sourceConfig is defined here:

containerFilterPattern: Note that the filter supports regex as include or exclude. You can find examples here.

storageMetadataConfigSource: Path to the openmetadata_storage_manifest.json global manifest file. It can be located in S3, a local path or as a URL to the file.

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.

Logger Level

You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.

JWT Token

JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.

You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

SSL Configuration

If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.

Find more information on how to troubleshoot SSL issues here.

Connection Options (Optional): Enter the details for any additional connection options that can be sent to storage service during the connection. These details must be added as Key-Value pairs.

Connection Arguments (Optional): Enter the details for any additional connection arguments such as security or protocol configs that can be sent to storage service during the connection. These details must be added as Key-Value pairs.