PROFESSIONAL-CLOUD-DATABASE-ENGINEER · Question #42
You work for a financial services company that wants to use fully managed database services. Traffic volume for your consumer services products has increased annually at a constant rate with…
The correct answer is A. Use linear scaling to implement the Autoscaler-based architecture. The Cloud Spanner Autoscaler supports two scaling methods: linear and stepwise. Because the described traffic pattern grows at a constant rate annually (linear growth) with occasional spikes, linear scaling is the appropriate model - it adds capacity proportionally as load…
Question
You work for a financial services company that wants to use fully managed database services. Traffic volume for your consumer services products has increased annually at a constant rate with occasional spikes around holidays. You frequently need to upgrade the capacity of your database. You want to use Cloud Spanner and include an automated method to increase your hardware capacity to support a higher level of concurrency. What should you do?
Options
- AUse linear scaling to implement the Autoscaler-based architecture
- BUse direct scaling to implement the Autoscaler-based architecture.
- CUpgrade the Cloud Spanner instance on a periodic basis during the scheduled maintenance
- DSet up alerts that are triggered when Cloud Spanner utilization metrics breach the threshold, and
How the community answered
(45 responses)- A76% (34)
- B4% (2)
- C13% (6)
- D7% (3)
Explanation
The Cloud Spanner Autoscaler supports two scaling methods: linear and stepwise. Because the described traffic pattern grows at a constant rate annually (linear growth) with occasional spikes, linear scaling is the appropriate model - it adds capacity proportionally as load increases, matching the predictable growth curve while still handling spikes. Manual periodic upgrades (option C) would require human intervention and may cause disruption. Alert-based manual scaling (option D) is reactive and slow. 'Direct scaling' (option B) is not a defined autoscaler method.
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