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PROFESSIONAL-DATA-ENGINEER · Question #339

You are planning to use Cloud Storage as part of your data lake solution. The Cloud Storage bucket will contain objects ingested from external systems. Each object will be ingested once, and the…

The correct answer is A. Create a Cloud Storage bucket with Autoclass enabled. Autoclass is correct because it automatically transitions objects between storage classes (Standard → Nearline → Coldline → Archive) based on each object's actual access activity - no rules to configure, no application changes required, and optimization happens invisibly. Since…

Submitted by carter_n· Mar 30, 2026Designing data processing systems

Question

You are planning to use Cloud Storage as part of your data lake solution. The Cloud Storage bucket will contain objects ingested from external systems. Each object will be ingested once, and the access patterns of individual objects will be random. You want to minimize the cost of storing and retrieving these objects. You want to ensure that any cost optimization efforts are transparent to the users and applications. What should you do?

Options

  • ACreate a Cloud Storage bucket with Autoclass enabled.
  • BCreate a Cloud Storage bucket with an Object Lifecycle Management policy to transition objects from Standard to Coldline storage class if an object age
  • CCreate a Cloud Storage bucket with an Object Lifecycle Management policy to transition objects from Standard to Coldline storage class if an object is not live.
  • DCreate two Cloud Storage buckets. Use the Standard storage class for the first bucket, and use the Coldline storage class for the second bucket. Migrate

How the community answered

(48 responses)
  • A
    83% (40)
  • B
    4% (2)
  • C
    2% (1)
  • D
    10% (5)

Explanation

Autoclass is correct because it automatically transitions objects between storage classes (Standard → Nearline → Coldline → Archive) based on each object's actual access activity - no rules to configure, no application changes required, and optimization happens invisibly. Since access patterns are random and unpredictable, Autoclass dynamically responds to real usage rather than guessing, minimizing both storage and retrieval costs over time.

Option B is wrong because age-based lifecycle policies ignore actual access patterns. An object moved to Coldline due to age but then accessed frequently will incur high retrieval fees, potentially increasing total cost rather than minimizing it.

Option C is wrong because the "not live" condition applies to non-current object versions in versioned buckets - it's not a general access-based policy and doesn't address the random-access cost optimization goal described.

Option D is wrong because it explicitly breaks the transparency requirement: users and applications would need to know which bucket to query, requiring logic changes throughout the system.

Memory tip: Whenever an exam question pairs "unpredictable/random access patterns" with "transparent to users," think Autoclass - it's Google's "set it and forget it" optimizer that requires zero changes to how clients interact with the bucket.

Topics

#Cloud Storage#Autoclass#Cost Optimization#Data Lake Architecture

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