- 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
Basic setup for Databricks encryption and masking
This section describes how to install and configure the Privacera Encryption jar file UDF in Privacera Manager Databricks to create UDFs for encryption and masking and to create policies for users and groups.
The overall approach is as follows:
Install the Privacera Manager Encryption Jar in Databricks with the Databricks CLI or UI
Upload Privacera Manager configuration files to Databricks
Define UDFs in Databricks to call the Privacera Manager encryption
protect
andunprotect
methods.
Prerequisites
In Databricks, make sure that the users who will use the UDFs have sufficient access to write the pertinent tables.
In Privacera Manager, make sure to configure the Databricks datasource: Databricks Spark Plugin (Python/SQL) on AWS, Azure, or GCP.
In Privacera Manager, make sure that Privacera Encryption has been enabled.
In Privacera Manager, make sure that the users who will use the UDFs in Databricks have been given permission to access the encryption scheme policies that are part of the UDF syntax.
In Privacera Manager, make sure that these same users have been given permission to access the encryption keys in the Ranger KMS.
Methods for Installing Encryption jar
You can install the Privacera encryption jar file in the following ways:
Via the Databricks command-line interface.
Via the Databricks web-based user interface.
After you install the jar file, you need to define some configuration properties and User-Defined Functions (UDFs) to call the Privacera encryption /protect
and /unprotect
API endpoints.
Install Encryption jar via Databricks CLI
Download the jar to a local machine.
The variable
PRIVACERA_BASE_DOWNLOAD_URL
depends on the version of the Privacera software you want. See Configure and Install Core Services.export PRIVACERA_BASE_DOWNLOAD_URL=$<PRIVACERA_BASE_DOWNLOAD_URL> wget $<PRIVACERA_BASE_DOWNLOAD_URL>/privacera-crypto-jar-with-dependencies.jar -O privacera-crypto-jar-with-dependencies.jar
Upload the jar file to DBFS or an S3 location from where the Databricks cluster can access it.
With the Databricks CLI, upload the jar into DBFS:
databricks fs ls databricks fs mkdirs dbfs:/privacera/crypto/jars databricks fs cp privacera-crypto-jar-with-dependencies.jar dbfs:/privacera/crypto/jars/privacera-crypto-jar-with-dependencies.jar
Install Encryption jar via Databricks UI
Go to the Databricks cluster details page: Clusters > cluster name > Libraries.
Click Install > New.
Drop or upload the jar file.
dbfs:/privacera/crypto/jars/privacera-crypto-jar-with-dependencies.jar
Wait until the jar file is installed.
Create and Upload Encryption Configuration Files
The steps here rely on the default location of the Privacera crypto properties file. However, you can change this location to a directory of your choice. Follow the steps here and then see Custom Path to Crypto Properties File in Databricks.
Create the configuration file on your local machine. In the next step, upload the file to the Databricks cluster.
mkdir -p privacera/crypto/configs cd privacera/crypto/configs # Edit the crypto_default.properties file to set the following variables. vi crypto_default.properties privacera.portal.base.url=http://<APP_HOSTNAME.>:6868 privacera.portal.username=<SOME_USERNAME> privacera.portal.password=<SOME_PASSWORD> # Mode of encryption/decryption: rpc or native privacera.crypto.mode=native
Upload the configuration file to DBFS.
databricks fs ls databricks fs mkdirs dbfs:/privacera/crypto/configs databricks fs cp crypto_default.properties dbfs:/privacera/crypto/configs/crypto_default.properties