ExpertMedium1 markMultiple Choice
Domain 5: Managing Implementation and Ensuring Solution and Operations ReliabilityCloud DataprocCost OptimizationSpot VMs
GCP PCA · Question 48 · Domain 5: Managing Implementation and Ensuring Solution and Operations Reliability
Your company is running a large Hadoop cluster on-premises and wants to migrate to Google Cloud. The workloads consist of ephemeral Spark jobs that run for 2 hours every night to process logs. Cost optimization is a primary concern. Which TWO GCP services/features should you use? (Select TWO)
Your company is running a large Hadoop cluster on-premises and wants to migrate to Google Cloud. The workloads consist of ephemeral Spark jobs that run for 2 hours every night to process logs. Cost optimization is a primary concern. Which TWO GCP services/features should you use? (Select TWO)
Answer options:
A.
Cloud Dataproc
B.
Cloud Dataflow
C.
Spot VMs (Preemptible VMs)
D.
Committed Use Discounts (CUDs)
E.
Compute Engine with custom Hadoop installation
How to approach this question
Identify the managed Hadoop service, and the compute pricing model best suited for short, fault-tolerant batch jobs.
Full Answer
Cloud Dataproc (Option A) is Google's managed Hadoop and Spark service, allowing you to lift-and-shift existing Spark jobs easily. Because the jobs are batch processes running only 2 hours a night, they are highly fault-tolerant. Configuring the Dataproc cluster to use Spot VMs (Option C) for its worker nodes provides massive cost savings compared to on-demand pricing.
Common mistakes
Selecting CUDs (D). CUDs require a 1 or 3-year commitment for resources running 24/7. You would waste money on the 22 hours a day the cluster is off.
Practice the full GCP Professional Cloud Architect Practice Exam 4
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