Faasera supports seamless deployment of its core components via cloud-native Functions-as-a-Service (FaaS) on AWS, Azure, and Google Cloud. This guide covers deploying Faasera Profiler and Masking services using cloud functions.
| Cloud Platform | Function Type | Use Cases |
|---|---|---|
| AWS | Lambda | Real-time masking/profiling via API Gateway |
| Azure | Azure Functions | Batch & stream data compliance workflows |
| Google Cloud | Cloud Functions | Lightweight API-based masking for GCS/BigQuery |
All Faasera cloud functions follow the same deployment pattern:
For Java-based functions:
/faasera-function/
├── build/libs/faasera.jar
├── config/
│ └── policy.json
└── handler/
└── FunctionHandler.java
For Python:
/faasera-function/
├── main.py
├── requirements.txt
└── config/
└── policy.json
aws lambda create-function --function-name FaaseraFunction --runtime java11 --handler com.faasera.FunctionHandler --zip-file fileb://faasera.zip --role arn:aws:iam::123456789:role/lambda-role
func azure functionapp publish faasera-comply-function
Ensure you set the
FUNCTIONS_WORKER_RUNTIMEtojavaorpythonas per your implementation.
gcloud functions deploy faasera-function --runtime java11 --trigger-http --entry-point com.faasera.FunctionHandler --memory 512MB
Pass configurations using:
All functions support:
{
"requestId": "xyz-123",
"mode": "MULTI_RULE_BATCH",
"records": [
{
"ruleName": "EMAIL_ADDRESS",
"value": "john.doe@example.com"
}
]
}