- Platform Release 6.5
- Privacera Platform Installation
- About Privacera Manager (PM)
- Install overview
- Prerequisites
- Installation
- Default services configuration
- Component services configurations
- Access Management
- Data Server
- PolicySync
- Snowflake
- Redshift
- Redshift Spectrum
- PostgreSQL
- Microsoft SQL Server
- Databricks SQL
- RocksDB
- Google BigQuery
- Power BI
- UserSync
- Privacera Plugin
- Databricks
- Spark standalone
- Spark on EKS
- Trino Open Source
- Dremio
- AWS EMR
- AWS EMR with Native Apache Ranger
- GCP Dataproc
- Starburst Enterprise
- Privacera services (Data Assets)
- Audit Fluentd
- Grafana
- Access Request Manager (ARM)
- Ranger Tagsync
- Discovery
- Encryption & Masking
- Privacera Encryption Gateway (PEG) and Cryptography with Ranger KMS
- AWS S3 bucket encryption
- Ranger KMS
- AuthZ / AuthN
- Security
- Access Management
- Reference - Custom Properties
- Validation
- Additional Privacera Manager configurations
- CLI actions
- Debugging and logging
- Advanced service configuration
- Increase Privacera portal timeout for large requests
- Order of precedence in PolicySync filter
- Configure system properties
- PolicySync
- Databricks
- Table properties
- Upgrade Privacera Manager
- Troubleshooting
- Possible Errors and Solutions in Privacera Manager
-
- Unable to Connect to Docker
- Terminate Installation
- 6.5 Platform Installation fails with invalid apiVersion
- Ansible Kubernetes Module does not load
- Unable to connect to Kubernetes Cluster
- Common Errors/Warnings in YAML Config Files
- Delete old unused Privacera Docker images
- Unable to debug error for an Ansible task
- Unable to upgrade from 4.x to 5.x or 6.x due to Zookeeper snapshot issue
- Storage issue in Privacera UserSync & PolicySync
- Permission Denied Errors in PM Docker Installation
- Unable to initialize the Discovery Kubernetes pod
- Portal service
- Grafana service
- Audit server
- Audit Fluentd
- Privacera Plugin
-
- Possible Errors and Solutions in Privacera Manager
- How-to
- Appendix
- AWS topics
- AWS CLI
- AWS IAM
- Configure S3 for real-time scanning
- Install Docker and Docker compose (AWS-Linux-RHEL)
- AWS S3 MinIO quick setup
- Cross account IAM role for Databricks
- Integrate Privacera services in separate VPC
- Securely access S3 buckets ssing IAM roles
- Multiple AWS account support in Dataserver using Databricks
- Multiple AWS S3 IAM role support in Dataserver
- Azure topics
- GCP topics
- Kubernetes
- Microsoft SQL topics
- Snowflake configuration for PolicySync
- Create Azure resources
- Databricks
- Spark Plug-in
- Azure key vault
- Add custom properties
- Migrate Ranger KMS master key
- IAM policy for AWS controller
- Customize topic and table names
- Configure SSL for Privacera
- Configure Real-time scan across projects in GCP
- Upload custom SSL certificates
- Deployment size
- Service-level system properties
- PrestoSQL standalone installation
- AWS topics
- Privacera Platform User Guide
- Introduction to Privacera Platform
- Settings
- Data inventory
- Token generator
- System configuration
- Diagnostics
- Notifications
- How-to
- Privacera Discovery User Guide
- What is Discovery?
- Discovery Dashboard
- Scan Techniques
- Processing order of scan techniques
- Add and scan resources in a data source
- Start or cancel a scan
- Tags
- Dictionaries
- Patterns
- Scan status
- Data zone movement
- Models
- Disallowed Tags Policy
- Rules
- Types of rules
- Example rules and classifications
- Create a structured rule
- Create an unstructured rule
- Create a rule mapping
- Export rules and mappings
- Import rules and mappings
- Post-processing in real-time and offline scans
- Enable post-processing
- Example of post-processing rules on tags
- List of structured rules
- Supported scan file formats
- Data Source Scanning
- Data Inventory
- TagSync using Apache Ranger
- Compliance Workflow
- Data zones and workflow policies
- Workflow Policies
- Alerts Dashboard
- Data Zone Dashboard
- Data zone movement
- Example Workflow Usage
- Discovery health check
- Reports
- Built-in Reports
- Saved reports
- Offline reports
- Reports with the query builder
- How-to
- Privacera Encryption Guide
- Essential Privacera Encryption terminology
- Install Privacera Encryption
- Encryption Key Management
- Schemes
- Scheme Policies
- Encryption Schemes
- Presentation Schemes
- Masking schemes
- Encryption formats, algorithms, and scopes
- Deprecated encryption formats, algorithms, and scopes
- Encryption with PEG REST API
- PEG REST API on Privacera Platform
- PEG API Endpoint
- Encryption Endpoint Summary for Privacera Platform
- Authentication Methods on Privacera Platform
- Anatomy of the /protect API Endpoint on Privacera Platform
- About Constructing the datalist for protect
- About Deconstructing the datalist for unprotect
- Example of Data Transformation with /unprotect and Presentation Scheme
- Example PEG API endpoints
- /unprotect with masking scheme
- REST API Response Partial Success on Bulk Operations
- Audit Details for PEG REST API Accesses
- REST API Reference
- Make calls on behalf of another user
- Troubleshoot REST API Issues on Privacera Platform
- PEG REST API on Privacera Platform
- Encryption with Databricks, Hive, Streamsets, Trino
- Databricks UDFs for encryption and masking
- Hive UDFs
- Streamsets
- Trino UDFs
- Privacera Access Management User Guide
- Privacera Access Management
- How Polices are evaluated
- Resource policies
- Policies overview
- Creating Resource Based Policies
- Configure Policy with Attribute-Based Access Control
- Configuring Policy with Conditional Masking
- Tag Policies
- Entitlement
- Request Access
- Approve access requests
- Service Explorer
- User/Groups/Roles
- Permissions
- Reports
- Audit
- Security Zone
- Access Control using APIs
- AWS User Guide
- Overview of Privacera on AWS
- Set policies for AWS services
- Using Athena with data access server
- Using DynamoDB with data access server
- Databricks access manager policy
- Accessing Kinesis with data access server
- Accessing Firehose with Data Access Server
- EMR user guide
- AWS S3 bucket encryption
- S3 browser
- Getting started with Minio
- Plugins
- How to Get Support
- Coordinated Vulnerability Disclosure (CVD) Program of Privacera
- Shared Security Model
- Privacera documentation changelog
Add and scan resources in a data source
Steps
The following example enables scanning on an AWS-Aurora DB resource. It is recommended that you familiarize yourself with the names of the resources you want to enable before scanning as they will appear in a drop-down menu.
To enable scanning on an AWS resource:
From the navigation menu, select Discovery > Data Source.
From the Applications list, select AWS-Aurora DB.
Click Add to add a resource for scanning.
Type the text of the resource and it will display the list of resources that matches the text.
Select the scan type.
Click Save.
Click the Status toggle to globally enable scanning.
For real-time scan, resources will be automatically scanned when they are added to the Included Resources list.
For offline scan, click Scan Resource button to initiate a scan.
Repeat these steps as needed for other data resources or applications you intend to enable for scanning.
The names of displayed fields will be different depending on the type of resource or application you are configuring (for example, Include Resource or Include Database or Table).
Resources in the landing zones are automatically scanned by Privacera. For more information on Data Zones see Data Zones.
Google Cloud Storageand Google BigQuery
Using a single Google Cloud Storage or Google BigQuery data source, you can scan resources from multiple projects. You can search for projects to be added, and select resources from the project to be included for scanning. To retrieve the list of projects in Google Cloud Storage or Google BigQuery, configure the Google Cloud Manager API.
Note
Data Explorer does not support showing resources from multiple projects. It only shows resources for the project with which the data source is configured.
Prerequisites
To allow Privacera search for projects on your Google account, you need to enable the API services in the GCP project you registered as a data source. Refer the Google documentation to enable API services.
Add resources to Google Cloud Storage or Google BigQuery data sources
Before you can add resources to a data source, your data source must be registered and the prerequisite requirements must be met in order to continue. For more information on registering a data source, see data source registration.
From the navigation menu, select Discovery > Data Source.
From the Applications section, select a Google Cloud Storage or Google BigQuery data source.
Click Add.
In the Add Resource dialog, enter the following:
Enter the Project ID of the resource you want to scan. You can enter an asterisk (*) to get a list of projects.
For Google BigQuery, the Project ID will be appended to the dataset or table name.
For Google Cloud Storage, the Project ID will not append to the bucket name as they are unique across a project.
Enter the Resource you are including in the project.
Note
Resources can be added from multiple projects. Existing resources will be updated with a project ID. If you have resources in a specific directory, you can add this location path so that all of the databases/tables in that location are scanned.
For Google Cloud Storage, add the bucket resources.
For Google BigQuery, add the datasets or tables.
Select a scan type:
Scan: Select this option if you want to perform real-time/offline scan.
Incremental: Select this option if you want to scan the resource once. During a re-scan, the resource gets added in the Excluded Resources list.
Multi-input: Turn on this button if you want to switch to a multiple input view and add multiple resources, one per line.
Click Save.
To enable the real-time/offline scan for the Google Cloud Storage or Google BigQuery data source, click the Status toggle.