Google Associate Cloud EngineerEnsuring successful operation of a cloud solutionHard
A team is developing a new microservices-based application on Google Cloud. Each microservice is deployed as a container on Google Kubernetes Engine (GKE). They need a way to store and retrieve small amounts of unstructured data (e.g., user preferences, session data) with extremely low latency and high throughput. The data does not require complex querying or transactional integrity across multiple items. Which data storage option is most appropriate?
- ACloud SQL
- BFirestore
- CCloud Storage Standard
- DMemorystore for Redis
Show answer & explanationAnswer & explanation
Correct answer: D. Memorystore for Redis
Memorystore for Redis is a fully managed in-memory data store that provides extremely low latency and high throughput for caching, session management, and real-time analytics, making it ideal for small, frequently accessed, unstructured data in microservices architectures.
Why the other options are wrong
- A. Cloud SQL is a managed relational database, which is overkill for small, unstructured data without complex querying and does not offer the 'extremely low latency' of an in-memory store.
- B. Firestore is a NoSQL document database, suitable for structured and semi-structured data with real-time synchronization and flexible querying, but 'extremely low latency' for cache-like data is typically better served by an in-memory store.
- C. Cloud Storage Standard is object storage, designed for large binary objects and files, not for extremely low-latency retrieval of small, frequently accessed, unstructured data.
Memorystore for Redis
A fully managed in-memory data store service built on open-source Redis, offering extremely high performance for caching and real-time use cases.
- Fully managed in-memory data store
- Extremely low latency, high throughput
- Ideal for caching, session management, real-time data
Memory trick: Redis remembers fast, for microservices that can't wait.