PCDOE Optimizing service performance Practice Question
You are designing a globally distributed application using Cloud Spanner. The application has a write-heavy workload. You notice that write latency increases as the number of nodes increases. What is the most likely cause?
⚠ Common exam trap
A common mix-up: candidates assume adding nodes always improves performance, but this scenario tests the counterintuitive behavior where cross-node coordination overhead in distributed databases like Cloud Spanner can degrade write latency with scale.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The workload has many cross-node transactions due to split rows.
In Cloud Spanner, write-heavy workloads with many cross-node transactions cause increased write latency as nodes are added. This occurs because Spanner splits rows across nodes, and transactions that span multiple splits require two-phase commit (2PC) coordination between nodes, which adds network overhead and latency. Adding more nodes increases the likelihood that a transaction touches multiple splits, exacerbating the coordination cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The instance is using a multi-region configuration with too many read-only replicas.
Why it's wrong here
Read-only replicas do not affect write latency.
- ✓
The workload has many cross-node transactions due to split rows.
Why this is correct
Cross-split transactions require coordination, increasing latency.
- ✗
The application is using stale reads for write transactions.
Why it's wrong here
Stale reads are for read-only transactions.
- ✗
The number of splits is too low, causing hotspots.
Why it's wrong here
Low splits cause hotspots but not uniform latency increase.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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