A financial technology firm is deploying a real-time trading processing engine on Google Cloud consisting of two core workload components. Component 1 is a trading account management database requiring full SQL compliance, multi-table ACID transactions, automated regional failover, and high write performance. Component 2 is an ephemeral risk simulation pipeline performing transient parallel calculations requiring ultra-low sub-millisecond I/O latency, where scratchpad data can be re-generated if an instance terminates. Which TWO storage and database configurations should the solution architect implement to meet these requirements with minimal operational overhead? (Select TWO.)
- Provision a Cloud SQL instance configured with High Availability (regional failover) using SSD Persistent Disk (pd-ssd) for the trading account management database.Cevap
- Attach Local SSD storage to the Compute Engine virtual machines executing the transient risk simulation pipeline.Cevap
- CDeploy a Cloud Bigtable cluster for the trading account management database to ensure relational SQL schema support and multi-table ACID transaction guarantees.
- DMount Coldline Cloud Storage buckets to the simulation nodes to store transient scratchpad data for the risk simulation pipeline.
Cevap
The architect should deploy a High Availability Cloud SQL instance backed by SSD Persistent Disks for the relational account database, and attach Local SSDs to Compute Engine instances for the high-speed scratchpad risk simulation workload.
Cloud SQL configured with High Availability delivers an automated failover solution with full relational SQL and ACID transactional guarantees using SSD Persistent Disk storage. For transient high-performance scratchpad data, Local SSD delivers sub-millisecond latency and high IOPS directly attached to Compute Engine instances.
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Selecting GCP Managed Databases and Storage Types based on Relational/ACID needs, latency, availability, and durability constraints.