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Difficulty: HardSelecting and Designing Storage and Database Resources

A enterprise solution architect is selecting Google Cloud storage and database services for four distinct business workloads. Match each workload requirement on the left with the most appropriate managed Google Cloud service on the right.

  • Global online payment transaction ledger requiring multi-region relational ACID compliance, horizontal scale-out for write throughput, and a 99.999% availability SLA.Cloud Spanner
  • High-frequency IoT fleet telemetry ingest requiring single-digit millisecond write latencies, seamless scale-out to petabytes of time-series key-value data, and integration with Apache HBase APIs.Cloud Bigtable
  • Cross-platform mobile gaming application requiring real-time document synchronization, offline client data persistence, and automatic scaling for unstructured JSON document collections.Firestore in Native mode
  • Regulatory financial audit archives requiring Write-Once-Read-Many (WORM) immutability enforcement for compliance, minimum 365-day retention, and lowest storage cost for data accessed less than once per year.Cloud Storage Archive Class with a Locked Retention Policy

Answer

Global payment ledger matches Cloud Spanner; IoT fleet telemetry matches Cloud Bigtable; Mobile gaming app matches Firestore in Native mode; Regulatory financial archives match Cloud Storage Archive Class with a Locked Retention Policy.
Each workload aligns strictly with GCP storage service design parameters: Cloud Spanner handles global multi-region relational ACID writes; Cloud Bigtable handles petabyte-scale time-series telemetry with HBase API compatibility; Firestore Native mode powers mobile document sync with offline caching; and Cloud Storage Archive with Bucket Lock provides compliant WORM object storage.

Step-by-Step Solution

1
Analyze global payment ledger workload requirements
Identified relational schema, global multi-region ACID transactions, horizontal write scaling, and 99.999% SLA.
Cloud Spanner is the only relational Google Cloud database engineered for multi-region horizontal scaling with strong global consistency and five-nines availability.
2
Analyze high-frequency IoT fleet telemetry requirements
Identified high write throughput, time-series access pattern, low millisecond latency, petabyte scale, and HBase API compatibility.
Cloud Bigtable is designed specifically for ultra-low latency key-value/wide-column time-series data at scale and supports HBase API interfaces.
3
Analyze cross-platform mobile gaming application requirements
Identified document store model, client-side offline persistence, and real-time synchronization listeners.
Firestore in Native mode natively supports live data synchronization to client devices, offline caching, and hierarchical JSON document collections.
4
Analyze regulatory financial audit archive requirements
Identified cold data access frequency (<1 access/year), lowest storage cost requirement, and WORM immutability compliance.
Cloud Storage Archive storage class offers the lowest cost for long-term cold object storage, while a Locked Retention Policy guarantees non-rewritable, non-deleterious WORM storage.

Key Concept

Selecting and Designing Storage and Database Resources
Estimated Time:2m 0s
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Selecting and Designing Storage and Database Resources