# Amazon S3 Amazon S3 is an object storage service that stores data as objects within buckets. You can use Amazon Kendra to index your Amazon S3 bucket repository of documents. **Warning** Amazon Kendra doesn't use a bucket policy that grants permissions to an Amazon Kendra principal to interact with an S3 bucket. Instead, it uses IAM roles. Make sure that Amazon Kendra isn't included as a trusted member in your bucket policy to avoid any data security issues in accidentally granting permissions to arbitrary principals. However, you can add a bucket policy to use an Amazon S3 bucket across different accounts. For more information, see [Policies to use Amazon S3 across accounts](https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html#iam-roles-ds-s3-cross-accounts) (within the S3 IAM roles tab, under **IAM roles for data sources**). For information about IAM roles for S3 data sources, see [IAM roles](https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html#iam-roles-ds-s3). **Note** Amazon Kendra now supports an upgraded Amazon S3 connector. The console has been automatically upgraded for you. Any new connectors you create in the console will use the upgraded architecture. If you use the API, you must now use the [https://docs.aws.amazon.com/kendra/latest/APIReference/API_TemplateConfiguration.html](https://docs.aws.amazon.com/kendra/latest/APIReference/API_TemplateConfiguration.html) object instead of the `S3DataSourceConfiguration` object to configure your connector. Connectors configured using the older console and API architecture will continue to function as configured. However, you won’t be able to edit or update them. If you want to edit or update your connector configuration, you must create a new connector. We recommended migrating your connector workflow to the upgraded version. Support for connectors configured using the older architecture is scheduled to end by June 2024. You can connect to your Amazon S3 data source using the the [Amazon Kendra console](https://console.aws.amazon.com/kendra/) or the [TemplateConfiguration](https://docs.aws.amazon.com/kendra/latest/APIReference/API_TemplateConfiguration.html) API. **Note** To generate a sync status report for your Amazon S3 data source, see [Troubleshooting data sources](https://docs.aws.amazon.com/kendra/latest/dg/troubleshooting-data-sources.html#troubleshooting-data-sources-sync-status-manifest). For troubleshooting your Amazon Kendra S3 data source connector, see [Troubleshooting data sources](troubleshooting-data-sources.md). **Topics** + [Supported features](#supported-features-s3) + [Prerequisites](#prerequisites-s3) + [Connection instructions](#data-source-procedure-s3) + [Creating an Amazon S3 data source](create-ds-s3.md) + [Amazon S3 document metadata](s3-metadata.md) + [Access control for Amazon S3 data sources](s3-acl.md) + [Using Amazon VPC with an Amazon S3 data source](s3-vpc-example-1.md) ## Supported features + Field mappings + User access control + Inclusion/exclusion filters + Full and incremental content syncs + Virtual private cloud (VPC) ## Prerequisites Before you can use Amazon Kendra to index your S3 data source, make these changes in your S3 and AWS accounts. **In S3, make sure you have:** + Copied the name of your Amazon S3 bucket. **Note** Your bucket must be in the same region as your Amazon Kendra index and your index must have permission to access the bucket that contains your documents. + Checked each document is unique in S3 and across other data sources you plan to use for the same index. Each data source that you want to use for an index must not contain the same document across the data sources. Document IDs are global to an index and must be unique per index. **In your AWS account, make sure you have:** + [Created an Amazon Kendra index](https://docs.aws.amazon.com/kendra/latest/dg/create-index.html) and, if using the API, noted the index ID. + [Created an IAM role](https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html#iam-roles-ds) for your data source and, if using the API, noted the ARN of the IAM role. If you don’t have an existing IAM role, you can use the console to create a new IAM role when you connect your S3 data source to Amazon Kendra. If you are using the API, you must provide the ARN of an existing IAM role and an index ID. ## Connection instructions To connect Amazon Kendra to your S3 data source, you must provide the necessary details of your S3 data source so that Amazon Kendra can access your data. If you have not yet configured S3 for Amazon Kendra, see [Prerequisites](#prerequisites-s3). ------ #### [ Console ] **To connect Amazon Kendra to Amazon S3 ** 1. Sign in to the AWS Management Console and open the [Amazon Kendra console](https://console.aws.amazon.com/kendra/). 1. From the left navigation pane, choose **Indexes** and then choose the index you want to use from the list of indexes. **Note** You can choose to configure or edit your **User access control** settings under **Index settings**. 1. On the **Getting started** page, choose **Add data source**. 1. On the **Add data source** page, choose **S3 connector**, and then choose **Add connector**. If using version 2 (if applicable), choose **S3 connector** with the "V2.0" tag. 1. On the **Specify data source details** page, enter the following information: 1. In **Name and description**, for **Data source name**—Enter a name for your data source. You can include hyphens but not spaces. 1. (Optional)** Description**—Enter an optional description for your data source. 1. In **Default language**—Choose a language to filter your documents for the index. Unless you specify otherwise, the language defaults to English. Language specified in the document metadata overrides the selected language. 1. In **Tags**, for **Add new tag**—Include optional tags to search and filter your resources or track your AWS costs. 1. Choose **Next**. 1. On the **Define access and security** page, enter the following optional information: 1. **IAM role**—Choose an existing IAM role or create a new IAM role to access your repository credentials and index content. **Note** IAM roles used for indexes cannot be used for data sources. If you are unsure if an existing role is used for an index or FAQ, choose **Create a new role** to avoid errors. 1. **Virtual Private Cloud (VPC)**—You can choose to use a VPC. If so, you must add **Subnets** and **VPC security groups**. 1. Choose **Next**. 1. On the **Configure sync settings** page, enter the following information: 1. For **Data source location**—Specify the path to the Amazon S3 bucket where your data is stored. Select **Browse S3** to choose your S3 bucket. 1. For **Maximum file size**—Specify a limit in MB to only crawl files under this limit. The maximum file size Amazon Kendra can allow is 50 MB. 1. For (Optional) **Metadata files prefix folder location**—Specify the path to the folder in which your fields/attributes and other document metadata is stored. Select **Browse S3** to locate your metadata folder. 1. For (Optional) **Access control list configuration file location**—Specify the path to the file that contains a JSON structure of your users and their access to documents. Select **Browse S3** to locate your ACL file. 1. (Optional) **Select decryption key**—Select to use a decryption key. You can choose to use an existing AWS KMS key. 1. For (Optional) **Additional configuration**—Add patterns to include or exclude certain files. All paths are relative to the data source location S3 bucket. 1. **Sync mode**—Choose how you want to update your index when your data source content changes. When you sync your data source with Amazon Kendra for the first time, all content is crawled and indexed by default. You must run a full sync of your data if your initial sync failed, even if you don't choose full sync as your sync mode option. + Full sync: Freshly index all content, replacing existing content each time your data source syncs with your index. + New, modified, deleted sync: Index only new, modified, and deleted content each time your data source syncs with your index. Amazon Kendra can use your data source's mechanism for tracking content changes and index content that changed since the last sync. 1. In **Sync run schedule**, for **Frequency**—Choose how often to sync your data source content and update your index. 1. Choose **Next**. 1. On the **Set field mappings** page, enter the following optional information: 1. **Default field mappings**—Select from the Amazon Kendra generated default data source fields you want to map to your index. 1. **Add field**—Choose to add custom data source fields to create an index field name to map to and the field data type. 1. Choose **Next**. 1. On the **Review and create** page, check that the information you have entered is correct and then select **Add data source**. You can also choose to edit your information from this page. Your data source will appear on the **Data sources** page after the data source has been added successfully. ------ #### [ API ] **To connect Amazon Kendra to Amazon S3** You must specify a JSON of the [data source schema](https://docs.aws.amazon.com/kendra/latest/dg/ds-schemas.html) using the [TemplateConfiguration](https://docs.aws.amazon.com/kendra/latest/APIReference/API_TemplateConfiguration.html) API. You must provide the following information: + **Data source**—Specify the data source type as `S3` when you use the [https://docs.aws.amazon.com/kendra/latest/dg/API_TemplateConfiguration.html](https://docs.aws.amazon.com/kendra/latest/dg/API_TemplateConfiguration.html) JSON schema. Also specify the data source as `TEMPLATE` when you call the [https://docs.aws.amazon.com/kendra/latest/dg/API_CreateDataSource.html](https://docs.aws.amazon.com/kendra/latest/dg/API_CreateDataSource.html) API. + **BucketName**—The name of the bucket that contains the documents. + **Sync mode**—Specify how Amazon Kendra should update your index when your data source content changes. When you sync your data source with Amazon Kendra for the first time, all content is crawled and indexed by default. You must run a full sync of your data if your initial sync failed, even if you don't choose full sync as your sync mode option. You can choose between: + `FORCED_FULL_CRAWL` to freshly index all content, replacing existing content each time your data source syncs with your index. + `FULL_CRAWL` to index only new, modified, and deleted content each time your data source syncs with your index. Amazon Kendra can use your data source’s mechanism for tracking content changes and index content that changed since the last sync. + **IAM role**—Specify `RoleArn` when you call `CreateDataSource` to provide an IAM role with permissions to access your Secrets Manager secret and to call the required public APIs for the S3 connector and Amazon Kendra. For more information, see [IAM roles for S3 data sources](https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html#iam-roles-ds). You can also add the following optional features: + **Virtual Private Cloud (VPC)**—Specify `VpcConfiguration` when you call `CreateDataSource`. For more information, see [Configuring Amazon Kendra to use an Amazon VPC](vpc-configuration.md). + **Inclusion and exclusion filters**—Specify whether to include or exclude certain file names, file types, file paths. You use glob patterns (patterns that can expand a wildcard pattern into a list of path names that match the given pattern). For examples, see [Use of Exclude and Include Filters](https://docs.aws.amazon.com/cli/latest/reference/s3/#use-of-exclude-and-include-filters) in the AWS CLI Command Reference. + **Document metadata and access control configuration**—Add document metadata and access control files that contain information such as the source URI, document author, or custom document attributes/fields, and your users and which documents they can access. Each metadata file contains metadata about a single document. + **Field mappings**—Choose to map your S3 data source fields to your Amazon Kendra index fields. For more information, see [Mapping data source fields](https://docs.aws.amazon.com/kendra/latest/dg/field-mapping.html). **Note** The document body field or the document body equivalent for your documents is required in order for Amazon Kendra to search your documents. You must map your document body field name in your data source to the index field name `_document_body`. All other fields are optional. For a list of other important JSON keys to configure, see [S3 template schema](https://docs.aws.amazon.com/kendra/latest/dg/ds-schemas.html#ds-s3-schema). ------ ### Learn more To learn more about integrating Amazon Kendra with your S3 data source, see: + [Search for answers accurately using Amazon Kendra S3 Connector with VPC support](https://aws.amazon.com/blogs/machine-learning/search-for-answers-accurately-using-amazon-kendra-s3-connector-with-vpc-support/) # Creating an Amazon S3 data source The following examples demonstrate creating an Amazon S3 data source. The examples assume that you have already created an index and an IAM role with permission to read the data from the index. For more information about the IAM role, see [IAM access roles](https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html#iam-roles-ds). For more information about creating an index, see [Creating an index](https://docs.aws.amazon.com/kendra/latest/dg/create-index.html). ------ #### [ CLI ] ``` aws kendra create-data-source \ --index-id index ID \ --name example-data-source \ --type S3 \ --configuration '{"S3Configuration":{"BucketName":"bucket name"}}' --role-arn 'arn:aws:iam::account id:role:/role name ``` ------ #### [ Python ] The following snippet of Python code creates an Amazon S3 data source. For the complete example, see [Getting started (AWS SDK for Python (Boto3))](gs-python.md). ``` print("Create an Amazon S3 data source.") # Provide a name for the data source name = "getting-started-data-source" # Provide an optional description for the data source description = "Getting started data source." # Provide the IAM role ARN required for data sources role_arn = "arn:aws:iam::${accountID}:role/${roleName}" # Provide the data soource connection information s3_bucket_name = "S3-bucket-name" type = "S3" # Configure the data source configuration = {"S3DataSourceConfiguration": { "BucketName": s3_bucket_name } } data_source_response = kendra.create_data_source( Configuration = configuration, Name = name, Description = description, RoleArn = role_arn, Type = type, IndexId = index_id ) ``` ------ It can take some time to create your data source. You can monitor the progress by using the [DescribeDataSource](https://docs.aws.amazon.com/kendra/latest/APIReference/API_DescribeDataSource.html) API. When the data source status is `ACTIVE` the data source is ready to use. The following examples demonstrate getting the status of a data source. ------ #### [ CLI ] ``` aws kendra describe-data-source \ --index-id index ID \ --id data source ID ``` ------ #### [ Python ] The following snippet of Python code gets information about an S3 data source. For the complete example, see [Getting started (AWS SDK for Python (Boto3))](gs-python.md). ``` print("Wait for Amazon Kendra to create the data source.") while True: data_source_description = kendra.describe_data_source( Id = "data-source-id", IndexId = "index-id" ) status = data_source_description["Status"] print(" Creating data source. Status: "+status) time.sleep(60) if status != "CREATING": break ``` ------ This data source doesn't have a schedule, so it doesn't run automatically. To index the data source, you call [StartDataSourceSyncJob](https://docs.aws.amazon.com/kendra/latest/APIReference/API_StartDataSourceSyncJob.html) to synchronize the index with the data source. The following examples demonstrate synchronizing a data source. ------ #### [ CLI ] ``` aws kendra start-data-source-sync-job \ --index-id index ID \ --id data source ID ``` ------ #### [ Python ] The following snippet of Python code synchronizes an Amazon S3 data source. For the complete example, see [Getting started (AWS SDK for Python (Boto3))](gs-python.md). ``` print("Synchronize the data source.") sync_response = kendra.start_data_source_sync_job( Id = "data-source-id", IndexId = "index-id" ) ``` ------ # Amazon S3 document metadata You can add metadata, additional information about a document, to documents in an Amazon S3 bucket using a metadata file. Each metadata file is associated with an indexed document. Your metadata files must be stored in the same bucket as your indexed files. You can specify a location within the bucket for your metadata files using the console or the `S3Prefix` field of the `DocumentsMetadataConfiguration` parameter when you create an Amazon S3 data source. If you don't specify an Amazon S3 prefix, your metadata files must be stored in the same location as your indexed documents. If you specify an Amazon S3 prefix for your metadata files, they are in a directory structure parallel to your indexed documents. Amazon Kendra looks only in the specified directory for your metadata. If the metadata isn't read, check that the directory location matches the location of your metadata. The following examples show how the indexed document location maps to the metadata file location. Note that the document's Amazon S3 key is appended to the metadata's Amazon S3 prefix and then suffixed with `.metadata.json` to form the metadata file's Amazon S3 path. The combined Amazon S3 key, with the metadata's Amazon S3 prefix and `.metadata.json` suffix must be no more than a total of 1024 characters. It is recommended that you keep your Amazon S3 key below 1000 characters to account for addtional characters when combining your key with the prefix and suffix. ``` Bucket name: s3://bucketName Document path: documents Metadata path: none File mapping s3://bucketName/documents/file.txt -> s3://bucketName/documents/file.txt.metadata.json ``` ``` Bucket name: s3://bucketName Document path: documents/legal Metadata path: metadata File mapping s3://bucketName/documents/legal/file.txt -> s3://bucketName/metadata/documents/legal/file.txt.metadata.json ``` Your document metadata is defined in a JSON file. The file must be a UTF-8 text file without a BOM marker. The file name of the JSON file must be `..metadata.json`. In this example, "document" is the name of the document that the metadata applies to and "extension" is the file extension for the document. The document ID must be unique in `..metadata.json`. The content of the JSON file follows this template. All of the attributes/fields are optional, so it's not necessary to include all attributes. You must provide a value for each attribute you want to include; the value cannot be empty. If you don't specify the `_source_uri`, then the links returned by Amazon Kendra in the search results point to the Amazon S3 bucket that contains the document. `DocumentId` is mapped to the field `s3_document_id` and is the absolute path to the document in S3. ``` { "DocumentId": "S3 document ID, the S3 path to doc", "Attributes": { "_category": "document category", "_created_at": "ISO 8601 encoded string", "_last_updated_at": "ISO 8601 encoded string", "_source_uri": "document URI", "_version": "file version", "_view_count": number of times document has been viewed, "custom attribute key": "custom attribute value", additional custom attributes }, "AccessControlList": [ { "Name": "user name", "Type": "GROUP | USER", "Access": "ALLOW | DENY" } ], "Title": "document title", "ContentType": "For example HTML | PDF. For supported content types, see [Types of documents](https://docs.aws.amazon.com/kendra/latest/dg/index-document-types.html)." } ``` The `_created_at` and `_last_updated_at` metadata fields are ISO 8601 encoded dates. For example, 2012-03-25T12:30:10\$101:00 is the ISO 8601 date-time format for March 25, 2012, at 12:30PM (plus 10 seconds) in the Central European Time time zone. You can add additional information to the `Attributes` field about a document that you use to filter queries or to group query responses. For more information, see [Creating custom document fields](custom-attributes.md). You can use the `AccessControlList` field to filter the response from a query. This way, only certain users and groups have access to documents. For more information, see [Filtering on user context](user-context-filter.md). # Access control for Amazon S3 data sources You can control access to documents in an Amazon S3 data source using a configuration file. You specify the file in the console or as the `AccessControlListConfiguration` parameter when you call the [CreateDataSource](https://docs.aws.amazon.com/kendra/latest/APIReference/API_CreateDataSource.html) or [UpdateDataSource](https://docs.aws.amazon.com/kendra/latest/APIReference/API_UpdateDataSource.html) API. The configuration file contains a JSON structure that identifies an S3 prefix and lists the access settings for the prefix. The prefix can be a path, or it can be an individual file. If the prefix is a path, the access settings apply to all of the files in that path. There is a maximum number of S3 prefixes in the JSON configuration file and a default maximum file size. For more information, see [Quotas for Amazon Kendra](quotas.md) You can specify both users and groups in the access settings. When you query the index, you specify user and group information. For more information, see [Filtering by user attribute](user-context-filter.md#context-filter-attribute). The JSON structure for the configuration file must be in the following format: ``` [ { "keyPrefix": "s3://BUCKETNAME/prefix1/", "aclEntries": [ { "Name": "user1", "Type": "USER", "Access": "ALLOW" }, { "Name": "group1", "Type": "GROUP", "Access": "DENY" } ] }, { "keyPrefix": "s3://prefix2", "aclEntries": [ { "Name": "user2", "Type": "USER", "Access": "ALLOW" }, { "Name": "user1", "Type": "USER", "Access": "DENY" }, { "Name": "group1", "Type": "GROUP", "Access": "DENY" } ] } ] ``` # Using Amazon VPC with an Amazon S3 data source This topic provides a step-by-step example that shows how to connect to an Amazon S3 bucket by using an Amazon S3 connector through Amazon VPC. The example assumes that you're starting with an existing S3 bucket. We recommend that you upload just a few documents to your S3 bucket to test the example. You can connect Amazon Kendra to your Amazon S3 bucket through Amazon VPC. To do so, you must specify the Amazon VPC subnet and Amazon VPC security groups when creating your Amazon S3 data source connector. **Important** So that an Amazon Kendra Amazon S3 connector can access your Amazon S3 bucket, make sure that you have assigned an Amazon S3 endpoint to your virtual private cloud (VPC). For Amazon Kendra to sync documents from your Amazon S3 bucket through Amazon VPC, you must complete the following steps: + Set up an Amazon S3 endpoint for Amazon VPC. For more information about how to set up an Amazon S3 endpoint, see [Gateway endpoints for Amazon S3](https://docs.aws.amazon.com/vpc/latest/privatelink/vpc-endpoints-s3.html) in the *AWS PrivateLink Guide*. + (Optional) Checked your Amazon S3 bucket policies to make sure that the Amazon S3 bucket is accessible from the virtual private cloud (VPC) that you assigned to Amazon Kendra. For more information, see [Controlling access from VPC endpoints with bucket policies](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies-vpc-endpoint.html) in the *Amazon S3 User Guide* **Topics** + [Step 1: Configure an Amazon VPC](#s3-configure-vpc) + [(Optional) Step 2: Configure Amazon S3 bucket policy](#s3-configure-bucket-policy) + [Step 3: Create a test Amazon S3 data source connector](#s3-connect-vpc) ## Step 1: Configure an Amazon VPC Create a VPC network including a private subnet with an Amazon S3 gateway endpoint and a security group for Amazon Kendra to use later. **To configure a VPC with a private subnet, an S3 endpoint, and a security group** 1. Sign in to the AWS Management Console and open the Amazon VPC console at [https://console.aws.amazon.com/vpc/](https://console.aws.amazon.com/vpc/). 1. **Create a VPC with a private subnet and an S3 endpoint for Amazon Kendra to use:** From the navigation pane, choose **Your VPCs**, and then choose **Create VPC**. 1. For **Resources to create**, choose **VPC and more**. 1. For **Name tag**, enable **Auto-generate**, then enter **kendra-s3-example**. 1. For **IPv4 / IPv6 CIDR block**, keep the default values. 1. For **Number of Availability Zones (AZs)**, choose **number 1**. 1. Select **Customize AZs**, and then select an Availability Zone from the **First availability zone** list. Amazon Kendra only supports a specific set of Availability Zones. 1. For **Number of public subnets**, choose **number 0**. 1. For **Number of private subnets**, choose **number 1**. 1. For **NAT gateways**, choose **None**. 1. For **VPC endpoints**, choose **Amazon S3 gateway.**. 1. Leave the rest of the values at their default settings. 1. Select **Create VPC**. Wait until the **Create VPC** workflow finishes. Then, choose **View VPC** to check the **VPC** you just created. You have now created a VPC network with a private subnet, which does not have access to the public internet. 1. **Copy your VPC endpoint ID of your Amazon S3 endpoint:** 1. From the navigation pane, choose **Endpoints**. 1. In the **Endpoints** list, find the Amazon S3 endpoint `kendra-s3-example-vpce-s3` that you just created together with your VPC. 1. Make a note of the **VPC endpoint ID**. You have now created an Amazon S3 gateway endpoint to access your Amazon S3 bucket through a subnet. 1. **Create a **Security Group** for Amazon Kendra to use:** 1. From the navigation pane, choose **Security Groups**, then select **Create security group**. 1. For **Security group name**, enter **s3-data-source-security-group**. 1. Choose your VPC from the **Amazon VPC** list. 1. Leave **inbound rules** and **outbound rules** as the default. 1. Choose **Create security group**. You have now created a VPC security group. You assign the subnet and security group that you created to your Amazon Kendra Amazon S3 data source connector during the connector configuration process. ## (Optional) Step 2: Configure Amazon S3 bucket policy In this optional step, learn how to configure an Amazon S3 bucket policy so that your Amazon S3 bucket is only accessible from the VPC that you assign to Amazon Kendra. Amazon Kendra uses IAM roles to access your Amazon S3 bucket and doesn't require that you configure an Amazon S3 bucket policy. However, you might find it useful to create a bucket policy if you want to configure an Amazon S3 connector using an Amazon S3 bucket that has existing policies restricting access to it from the public internet. **To configure your Amazon S3 bucket policy** 1. Open the Amazon S3 console at [https://console.aws.amazon.com/s3/](https://console.aws.amazon.com/s3/). 1. From the navigation pane, choose **Buckets**. 1. Choose the name of the Amazon S3 bucket that you want to sync with Amazon Kendra. 1. Choose the **Permissions** tab, scroll down to **Bucket policy**, and then click on **Edit**. 1. Add or modify your bucket policy to allow access only from the VPC endpoint that you created. The following is an example bucket policy. Replace *`bucket-name`* and *`vpce-id`* with your Amazon S3 bucket name and the Amazon S3 endpoint ID that you noted earlier. 1. Select **Save changes**. Your S3 bucket is now accessible only from the specific VPC that you created. ## Step 3: Create a test Amazon S3 data source connector To test your Amazon VPC configuration, create an Amazon S3 connector. Then, configure it with the VPC that you created by following the steps outlined in [Amazon S3](https://docs.aws.amazon.com/kendra/latest/dg/data-source-s3.html). For Amazon VPC configuration values, choose the values that you created during this example: + **Amazon VPC(VPC)** – `kendra-s3-example-vpc` + **Subnets** – `kendra-s3-example-subnet-private1-[availability zone]` + **Security groups** – `s3-data-source-security-group` Wait for your connector to finish creating. After the Amazon S3 connector has been created, choose **Sync now** to initiate a sync. It might take several minutes to several hours to finish the sync, depending on how many documents are in your Amazon S3 bucket. To test the example, we recommend that you upload just a few documents to your S3 bucket. If your configuration is correct, you should eventually see a **Sync status** of **Completed**. If you encounter any errors, see [Troubleshooting Amazon VPC connection](https://docs.aws.amazon.com/kendra/latest/dg/vpc-connector-troubleshoot.html).