Amazon EMR is the correct choice because it is a managed big data platform that natively supports Apache Spark and Hadoop, and it can provision a cluster, install the frameworks, and automatically terminate the cluster after the job completes using transient clusters and step-based lifecycle management. This transient cluster model is the key technical concept: you define a series of processing steps, and EMR spins up the cluster, executes the steps, and then shuts down all resources, ensuring you only pay for compute time during active processing. On the AWS Certified Cloud Practitioner CLF-C02 exam, this question tests your understanding of cost-optimized, managed big data services versus always-on alternatives like running EC2 instances manually. A common trap is confusing EMR with Amazon Redshift or Athena, but remember: EMR is for custom Spark/Hadoop jobs with auto-termination, while Redshift is a data warehouse and Athena is serverless SQL. Memory tip: think “EMR = Ephemeral, Managed, and Ready” for transient clusters that vanish after the job finishes.
CLF-C02 Cloud Technology and Services Practice Question
This CLF-C02 practice question tests your understanding of cloud technology and services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 data engineering team processes petabytes of raw log data using Apache Spark and Hadoop frameworks. They need a managed AWS service that provisions the cluster, installs the big data frameworks, and terminates the cluster after the job completes to minimise cost. Which service should they use?
Why wrong: Redshift is a data warehouse for SQL analytics. It does not run Hadoop or Spark frameworks for big data processing.
B
AWS Glue
Why wrong: Glue is a serverless ETL service that can run Spark jobs. For large, complex Spark workloads with custom configurations, EMR provides more control and flexibility.
C
Amazon EMR
EMR is AWS's managed big data service that provisions and configures Hadoop, Spark, Hive, and other frameworks. It supports transient clusters that terminate after job completion, minimising cost for batch processing workflows.
D
Amazon Athena
Why wrong: Athena is a serverless SQL query service for S3. It does not run Hadoop or Spark big data frameworks.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon EMR
Amazon EMR is the correct choice because it is a managed big data platform that can provision Apache Spark and Hadoop clusters, install the required frameworks, and automatically terminate the cluster upon job completion using features like transient clusters and step-based lifecycle management. This minimizes cost by only paying for compute resources during active processing.
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.
✗
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse for SQL analytics. It does not run Hadoop or Spark frameworks for big data processing.
✗
AWS Glue
Why it's wrong here
Glue is a serverless ETL service that can run Spark jobs. For large, complex Spark workloads with custom configurations, EMR provides more control and flexibility.
✓
Amazon EMR
Why this is correct
EMR is AWS's managed big data service that provisions and configures Hadoop, Spark, Hive, and other frameworks. It supports transient clusters that terminate after job completion, minimising cost for batch processing workflows.
Related concept
Read the scenario before looking for a memorised answer.
✗
Amazon Athena
Why it's wrong here
Athena is a serverless SQL query service for S3. It does not run Hadoop or Spark big data frameworks.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse AWS Glue's use of Apache Spark with the ability to run custom Hadoop/Spark jobs on petabyte-scale data, but Glue is serverless and lacks the cluster management and framework installation capabilities required for this use case.
Detailed technical explanation
How to think about this question
Amazon EMR uses Amazon EC2 instances to form a cluster and can automatically install and configure Apache Spark, Hadoop, Hive, and other frameworks via bootstrap actions. When configured with a transient cluster and step-based execution, EMR automatically terminates the cluster after the final step completes, which is critical for cost optimization in large-scale batch processing jobs that run infrequently.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this CLF-C02 question in full detail.
Cloud Technology and Services — This question tests Cloud Technology and Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon EMR — Amazon EMR is the correct choice because it is a managed big data platform that can provision Apache Spark and Hadoop clusters, install the required frameworks, and automatically terminate the cluster upon job completion using features like transient clusters and step-based lifecycle management. This minimizes cost by only paying for compute resources during active processing.
What should I do if I get this CLF-C02 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This CLF-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CLF-C02 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.