The answer is index write amplification caused by adding an index on a highly selective column. When MySQL must maintain a B-tree index on a column with many unique values, every INSERT or UPDATE operation triggers additional disk writes to update the index structure, multiplying the write overhead per transaction. With 500 writes per second on a 10-million-row table, this index maintenance becomes the bottleneck, overwhelming the 8 vCPUs and 30GB RAM that would otherwise be sufficient. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of the trade-off between read optimization and write performance—a common trap is assuming more indexes always improve performance without considering write workload. The key insight is that highly selective indexes (like UUIDs or timestamps) cause the most write amplification because each new value forces a new leaf node insertion in the B-tree. Memory tip: "Selective indexes speed reads but bleed writes"—the more unique the column, the more work per write.
PCDE Monitor and optimize database performance Practice Question
This PCDE practice question tests your understanding of monitor and optimize database performance. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A Cloud SQL for MySQL instance is configured with 8 vCPUs and 30GB RAM. The Database Advisor suggests adding an index on a table, but after adding, write performance degrades. The table has 10 million rows and receives 500 writes per second. What is the most likely reason?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The index is on a highly selective column causing write amplification.
Option D is correct because adding an index on a highly selective column (e.g., a column with many unique values) forces MySQL to update the B-tree index structure on every write operation. With 500 writes per second and 10 million rows, each INSERT or UPDATE must maintain the index, causing write amplification that degrades write throughput. The 8 vCPUs and 30GB RAM are sufficient for the workload, but the index maintenance overhead becomes the bottleneck.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 needs more CPU.
Why it's wrong here
CPU is already relatively high, but the degradation is due to I/O from index maintenance rather than CPU bottleneck.
✗
The index is too large for memory.
Why it's wrong here
With 30GB RAM, the index likely fits; write degradation is more likely due to write amplification rather than memory pressure.
✗
The index is not used for reads.
Why it's wrong here
Even if unused for reads, the index still must be maintained on writes, causing overhead.
✓
The index is on a highly selective column causing write amplification.
Why this is correct
High selectivity means many unique values, requiring many index page splits and updates, increasing write latency.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that write degradation after adding an index is caused by insufficient resources (CPU or memory), when the real issue is the overhead of index maintenance on a highly selective column, known as write amplification.
Detailed technical explanation
How to think about this question
In MySQL, each secondary index on a table requires a separate B-tree structure. When a row is inserted or updated, every index on that table must be updated atomically, which increases the number of disk I/O operations and locks. For a highly selective column (e.g., UUID or email), the B-tree has many leaf nodes, making each index update more expensive due to random I/O and page splits. In production, this is often observed when adding an index on a column with high cardinality without considering write-heavy workloads.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The index is on a highly selective column causing write amplification. — Option D is correct because adding an index on a highly selective column (e.g., a column with many unique values) forces MySQL to update the B-tree index structure on every write operation. With 500 writes per second and 10 million rows, each INSERT or UPDATE must maintain the index, causing write amplification that degrades write throughput. The 8 vCPUs and 30GB RAM are sufficient for the workload, but the index maintenance overhead becomes the bottleneck.
What should I do if I get this PCDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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