Architecture & System Design Flashcards

When designing a microservices architecture that processes personal data, which pattern best ensures GDPR compliance by minimizing data exposure across services?

Answer: Data ownership pattern where each service owns its own data store

The data ownership pattern ensures each microservice controls its own data store, limiting personal data exposure to only the services that legitimately need it.

A system architect is designing an API gateway for a GDPR-regulated platform. Which feature is MOST critical for compliance from an accountability perspective?

Answer: Comprehensive request and response logging with PII redaction

Comprehensive logging with PII redaction enables demonstrable accountability while preventing the gateway itself from becoming a source of unauthorized personal data exposure.

Under GDPR, when a system uses a data lake architecture, what is the PRIMARY architectural risk that must be mitigated?

Answer: Loss of data context making purpose limitation and erasure difficult to enforce

Data lakes aggregate raw data from multiple sources, making it difficult to track the original purpose of collection and enforce deletion rights without robust metadata management.

A Privacy Enhancing Technology (PET) that allows computations on encrypted data without decrypting it first is called:

Answer: Homomorphic encryption

Homomorphic encryption enables processing of encrypted data, meaning personal data can be analyzed without ever being exposed in plaintext.

Which architectural approach to consent management best supports GDPR's requirement that consent be as easy to withdraw as to give?

Answer: A centralized consent management platform with real-time propagation to all downstream systems

A centralized consent management platform with real-time propagation ensures withdrawal of consent is immediately reflected across all systems processing data under that consent.

When architecting a system to support GDPR's right to erasure, which database design decision creates the MOST difficulty?

Answer: Using immutable append-only event sourcing without a deletion strategy

Immutable event logs make erasure inherently complex because overwriting or deleting historical events breaks the integrity of the event stream.

A GDPR-compliant system design requires 'data minimization' at the collection layer. Which architectural control BEST enforces this at the API level?

Answer: Using strict input schemas that reject any fields not required for the stated purpose

Strict input schema validation at the API layer prevents collection of unnecessary personal data before it enters the system.