Your team manages a high-throughput sensor application that stores real-time metrics in a Cloud Bigtable instance. During peak operational hours, read and write latencies spike significantly because average node CPU utilization exceeds 90%. You need to resolve this performance bottleneck during peak traffic while ensuring cost-efficient operations and minimal administrative overhead. Which two actions should you take? (Select TWO answers.)
- Enable autoscaling on the Cloud Bigtable cluster and configure a target CPU utilization threshold.Answer
- Manually increase the node count of the Cloud Bigtable cluster prior to predicted peak traffic windows.Answer
- CMigrate the real-time time-series workload to a Cloud SQL PostgreSQL database instance with storage auto-increase enabled.
- DReconfigure the Cloud Bigtable cluster storage type from SSD to HDD to decrease storage access latency.
Answer
The correct actions are to enable Cloud Bigtable autoscaling with a target CPU threshold and to manually increase the cluster node count to handle peak traffic.
Cloud Bigtable scales performance linearly by adjusting the number of nodes in a cluster. Adding nodes increases compute capacity and reduces CPU load per node, directly resolving latency spikes. Configuring Cloud Bigtable autoscaling automates node management based on CPU utilization targets, while manually scaling nodes allows proactive capacity adjustments.
Step-by-Step Solution
Key Concept
Managing Cloud Bigtable performance and node scaling