The answer is to set parallelism: 10 and completions: 10 in the Job spec. This configuration is correct because the `parallelism` field controls how many Pods run concurrently—here, 10 workers process records in parallel—while the `completions` field defines the total number of successful Pod completions required for the Job to finish. By setting both to 10, you ensure that exactly 10 Pods run simultaneously, each handling a subset of the batch, and the Job is marked complete only after all 10 have succeeded. On the Google Associate Cloud Engineer exam, this tests your understanding of batch workload orchestration in Kubernetes, often appearing as a scenario where you must distinguish between `parallelism` (concurrent Pods) and `completions` (total successes). A common trap is confusing `parallelism` with `completions` or assuming a single value suffices for both. Memory tip: think of “parallelism” as the number of lanes on a highway (cars drive simultaneously) and “completions” as the total number of cars that must reach the destination for the trip to be done.
Google ACE Deploying and implementing a cloud solution Practice Question
This ACE practice question tests your understanding of deploying and implementing a cloud solution. 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 platform engineer is deploying a Kubernetes Job that processes a batch of records. The Job should run 10 parallel workers, each processing a subset of records, and complete when all workers finish successfully. Which Job spec configuration achieves this?
Why wrong: Jobs use `parallelism` and `completions`, not `replicas` — `replicas` is a Deployment field.
B
Set parallelism: 10 and completions: 10 in the Job spec
`parallelism: 10` runs up to 10 Pods simultaneously. `completions: 10` requires 10 successful completions total. Together they create a parallel batch Job.
C
Create 10 separate Job objects — one per worker
Why wrong: Creating 10 separate Jobs is operational overhead that the `parallelism` field handles natively in a single Job object.
D
Set concurrency: 10 in the Job spec
Why wrong: `concurrency` is not a valid Kubernetes Job spec field. Use `parallelism` for controlling simultaneous Pod execution.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set parallelism: 10 and completions: 10 in the Job spec
Option B is correct because in Kubernetes, a Job's `parallelism` field specifies the number of Pods that can run concurrently, and `completions` specifies the total number of successful Pod completions required for the Job to be considered finished. Setting both to 10 ensures exactly 10 Pods run in parallel, each processing a subset of records, and the Job completes only when all 10 have succeeded.
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.
✗
Set replicas: 10 in the Job spec
Why it's wrong here
Jobs use `parallelism` and `completions`, not `replicas` — `replicas` is a Deployment field.
✓
Set parallelism: 10 and completions: 10 in the Job spec
Why this is correct
`parallelism: 10` runs up to 10 Pods simultaneously. `completions: 10` requires 10 successful completions total. Together they create a parallel batch Job.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create 10 separate Job objects — one per worker
Why it's wrong here
Creating 10 separate Jobs is operational overhead that the `parallelism` field handles natively in a single Job object.
✗
Set concurrency: 10 in the Job spec
Why it's wrong here
`concurrency` is not a valid Kubernetes Job spec field. Use `parallelism` for controlling simultaneous Pod execution.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between Deployment fields (like `replicas`) and Job-specific fields (like `parallelism` and `completions`), trapping candidates who confuse the two or assume `replicas` applies to Jobs.
Detailed technical explanation
How to think about this question
Under the hood, the Kubernetes Job controller uses the `parallelism` and `completions` fields to manage a work queue: it creates up to `parallelism` Pods at a time, and each successful Pod completion increments the completion count. If a Pod fails, the controller can restart it (depending on the `backoffLimit`), ensuring the total number of successes reaches `completions`. A real-world scenario is processing a large dataset where each worker handles a shard; setting `parallelism` too high can overwhelm cluster resources, while setting it too low may underutilize capacity.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this ACE question in full detail.
Deploying and implementing a cloud solution — This question tests Deploying and implementing a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set parallelism: 10 and completions: 10 in the Job spec — Option B is correct because in Kubernetes, a Job's `parallelism` field specifies the number of Pods that can run concurrently, and `completions` specifies the total number of successful Pod completions required for the Job to be considered finished. Setting both to 10 ensures exactly 10 Pods run in parallel, each processing a subset of records, and the Job completes only when all 10 have succeeded.
What should I do if I get this ACE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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