Secure User Profile Sharing in Microservices: A Quiz Quiz

1. API Gateway Authorization

   Which of the following is the most secure and recommended approach for handling user profile access control at the API Gateway level in a microservices architecture?

   1. Rely solely on IP address whitelisting for microservice access.
   2. Implement basic authentication using a shared secret key for all microservices.
   3. Utilize JWT (JSON Web Tokens) for authentication and authorization, with each microservice validating the token and its claims.
   4. Expose all user profile data publicly and rely on rate limiting to prevent abuse.
   5. Store user credentials directly in the API Gateway configuration.

2. Data Ownership and Updates

   In a microservices architecture where the profile service owns the core user profile data, what is the recommended way for other microservices, like the activity feed service, to update specific parts of a user's profile?

   1. Directly update the profile service's database from the activity feed service.
   2. Send an event to a message queue (e.g., Kafka, RabbitMQ) indicating the desired update, which the profile service consumes and processes.
   3. Make a synchronous REST API call to the profile service's update endpoint, directly from the activity feed service.
   4. Replicate the entire user profile database in the activity feed service for local updates.
   5. Share a common database schema between the profile service and the activity feed service.

3. Data Consistency

   What pattern helps maintain eventual consistency when a user profile is updated across multiple microservices (e.g., profile service, recommendation service) through asynchronous events?

   1. Two-Phase Commit (2PC)
   2. Distributed Transactions with XA
   3. Saga Pattern
   4. Global Locks
   5. Direct Database Replication

4. Granular Access Control

   Which of the following methods is most suitable for implementing fine-grained access control to user profile data, allowing different microservices access to different subsets of the profile information?

   1. OAuth 2.0 scopes with Resource Servers representing different user profile sections.
   2. A single, all-encompassing API key for all microservices.
   3. Publicly exposing all profile data via a GraphQL endpoint.
   4. Hardcoding access rules within each microservice based on its role.
   5. Using a shared secret key passed in HTTP headers for all requests.

5. Data Caching

   Which caching strategy is most effective for reducing the load on the profile service when frequently accessed profile data is required by multiple microservices?

   1. Completely disabling caching to ensure data consistency.
   2. Client-side caching with short expiration times and proper cache invalidation mechanisms (e.g., using message queues to trigger cache invalidation).
   3. Server-side caching only within the profile service itself, without notifying other microservices.
   4. Always fetching data directly from the profile service's database.
   5. Using browser caching with very long expiration times.

6. User Profile Anonymization

   What technique is crucial when sharing user profile data with a microservice responsible for generating aggregate analytics or reporting, while respecting user privacy?

   1. Sharing the raw user profile data without any modifications.
   2. Removing all user data from the analytics service.
   3. Anonymizing or pseudonymizing the user data before sharing it with the analytics service.
   4. Only sharing data for users who have explicitly opted-in.
   5. Sharing data with hash user ID.

7. Database per Microservice

   Which is the primary benefit of using the 'database per microservice' architectural pattern regarding user profile data?

   1. It simplifies data joins across different microservices.
   2. It reduces the overall infrastructure cost.
   3. It increases the coupling between microservices.
   4. It allows each microservice to independently choose the database technology that best suits its needs and data model.
   5. It guarantees immediate data consistency across all microservices.

8. Avoiding Data Duplication

   While the 'database per microservice' pattern is generally recommended, what is a potential drawback related to user profile data in a social networking app?

   1. It eliminates the need for data transformation.
   2. It simplifies the implementation of complex queries involving user profile data across multiple services.
   3. It can lead to data duplication if multiple microservices require copies of certain profile attributes.
   4. It automatically resolves all data consistency issues.
   5. It allows for easier sharing of code libraries.

9. Service Discovery and Communication

   How does service discovery typically contribute to the secure and efficient sharing of user profile information between microservices?

   1. It is not necessary for microservice communication.
   2. It provides a centralized registry that allows microservices to dynamically locate and communicate with each other, enabling secure and efficient data exchange.
   3. It automatically encrypts all data transmitted between microservices.
   4. It eliminates the need for authentication and authorization.
   5. It limits number of microservices in the architecture.

10. Eventual Consistency Strategy

    In the context of eventual consistency, how can you ensure that all microservices eventually receive and process updates to user profile data?

    1. By using two-phase commits (2PC) across all microservices.
    2. By relying solely on synchronous API calls for all data updates.
    3. By implementing a robust message queue system with retry mechanisms and dead-letter queues to handle failed messages.
    4. By avoiding asynchronous communication altogether.
    5. By sharing a single database across all microservices.