Bigtable High Read Latency — Increase Initial Nodes | Google PCDE Explained
This PCDE practice question tests your understanding of plan and manage database infrastructure. 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.
Refer to the exhibit. After creating this Bigtable instance, the administrator noticed high read latency during peak hours. Which configuration change would most likely help?
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.
The answer is to increase the cluster-num-nodes to at least 5, as this directly addresses Bigtable high read latency by adding more serving capacity to the initial cluster. When an instance starts with too few nodes, like the default three, it cannot handle peak read loads without queuing requests, which spikes latency. Increasing the initial node count raises the baseline throughput, whereas simply raising the max nodes only permits future scaling without fixing the immediate bottleneck. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding that Bigtable’s read performance is tied to the number of nodes serving data, not to replication or storage type—a common trap is confusing autoscaling limits with actual capacity. Remember the memory tip: “Nodes now, not later” — always set initial nodes high enough for peak demand, because max nodes only help after the latency has already occurred.
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
✓
Increase cluster-num-nodes to at least 5
Increasing the number of nodes in the Bigtable cluster (option B) directly improves read throughput by distributing the read load across more tablet servers. High read latency during peak hours typically indicates that the existing nodes are saturated, and adding nodes reduces per-node load, lowering overall latency. This is the most direct and effective configuration change for addressing read latency in a single-cluster setup.
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.
✗
Change cluster-storage-type to HDD
Why it's wrong here
HDD has higher latency than SSD, worsening the problem.
✓
Increase cluster-num-nodes to at least 5
Why this is correct
More nodes increase the read throughput capacity, reducing latency during peak times.
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.
✗
Add more clusters in different zones
Why it's wrong here
Adding clusters provides replication and high availability but does not reduce read latency for the primary cluster.
✗
Increase cluster-autoscaling-max-nodes to 20
Why it's wrong here
Increasing the max nodes allows scaling but does not increase current capacity if autoscaling is not triggered.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google often tests the distinction between autoscaling limits and actual node count, tricking candidates into thinking increasing the maximum will instantly solve performance issues, when in fact the cluster must first scale up to that limit.
Detailed technical explanation
How to think about this question
Bigtable uses a distributed storage system where each node (tablet server) handles a subset of tablets. Read latency increases when nodes exceed their CPU or IOPS capacity; adding nodes reduces the number of tablets per node, allowing more parallel reads. Autoscaling in Bigtable adjusts nodes based on CPU utilization and storage throughput, but it requires a sufficient max-nodes setting and actual demand to trigger scaling, so simply raising the max does not immediately add nodes.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
Plan and manage database infrastructure — This question tests Plan and manage database infrastructure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase cluster-num-nodes to at least 5 — Increasing the number of nodes in the Bigtable cluster (option B) directly improves read throughput by distributing the read load across more tablet servers. High read latency during peak hours typically indicates that the existing nodes are saturated, and adding nodes reduces per-node load, lowering overall latency. This is the most direct and effective configuration change for addressing read latency in a single-cluster setup.
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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