Radius Streaming Data Masking: Real-Time Protection for Sensitive Data

Radius handles masking at the speed of your data pipeline. It works on real-time streams—Kafka, Kinesis, Pulsar—and applies consistent, rules-based masking without slowing throughput. This means customer names, credit card numbers, emails, API keys, and any defined sensitive fields are automatically protected while still passing the structure your apps need.

Unlike batch masking, Radius Streaming Data Masking operates inline. The system intercepts data in motion, applies transformations, and emits masked payloads with minimal latency. You can define rules using regex, JSONPath, or schema-based conditions. Masking can be reversible—using encryption for downstream authorized services—or irreversible for strict compliance with GDPR, HIPAA, or PCI DSS.

Integration is direct. The Radius SDK and connectors require no rewriting of producers or consumers. Masking happens at the edge of the stream, close to the source. You maintain throughput, preserve formats, and meet compliance objectives at once.

Monitoring is built in. Dashboards display masking events, transformation counts, and anomalies detected. Alerts can be sent to Slack, PagerDuty, or any webhook. Logs ensure full auditability for security teams.

Radius Streaming Data Masking is engineered for scale. Whether you have millions or billions of events per day, the masking rules apply consistently and deterministically across partitions and brokers. No drift. No missed fields.

Data streams will not slow down. They will not wait for manual review. Radius makes sure they do not leak.

See Radius Streaming Data Masking live in minutes at hoop.dev and turn on full stream protection before the next packet moves.