QScan Guides
Hands-on guides for deploying and using QScan, Qpoint's PII and sensitive data scanning engine. QScan analyzes HTTP traffic captured by Qtap to detect personally identifiable information flowing through your network.
What You'll Learn
These guides cover:
End-to-end setup - Standing up the full pipeline from object storage to PII detections
Configuration - Tuning monitors, sampling rates, and scan behavior
Production deployment - Running QScan in Kubernetes and Cloud Run environments
Interpreting results - Understanding PII findings in the Pulse dashboard
Available Guides
Getting Started
The "hello world" for QScan. Walk through the complete pipeline from nothing to seeing PII detections in the Pulse dashboard.
What you'll learn:
Setting up local S3-compatible object storage with MinIO
Configuring Qtap to capture and store HTTP artifacts
Deploying QScan to scan captured traffic for PII
Generating test traffic and verifying detections
Perfect for:
First-time QScan users
Evaluating PII scanning capabilities
Development and testing environments
Time to complete: 30 minutes Skill level: Beginner-Intermediate
Deploy QScan on Amazon EKS with S3 for artifact storage and Qplane for centralized management. Covers migrating from standalone YAML to Helm-managed Qplane, configuring S3 object storage, deploying QScan, and enabling PII scanning.
What you'll learn:
Verifying egress access to Qpoint services
Connecting Qtap to Qplane via Helm
Configuring AWS S3 object storage for artifact capture
Deploying QScan and enabling PII scanning in Qplane
Scaling and production considerations (IRSA, GPU, monitoring)
Perfect for:
Teams running EKS with EC2 node groups
Production AWS deployments with Qplane
Migrating from standalone Qtap to cloud-managed
Time to complete: 30 minutes Skill level: Intermediate
How QScan Works
QScan operates as an asynchronous scanning pipeline:
Qtap captures HTTP request and response bodies during normal traffic flow
Captured artifacts are stored in S3-compatible object storage
Pulse schedules scan jobs based on the captured artifacts
QScan polls for jobs, downloads artifacts, and runs PII detection models
Results appear in the Pulse dashboard with entity types and confidence scores
This architecture means QScan never sits in the request path -- it processes captured data after the fact, with zero impact on application latency.
Next Steps
New to QScan? Start with the End-to-End Setup guide.
Looking for installation docs? See the QScan Installation reference for Docker, Kubernetes, and Cloud Run.
Need to configure Qtap for scanning? The end-to-end guide covers this, or see Stacks and Plugins for the qscan plugin reference.
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