Question 306 of 1,024
Cloud Technology and ServiceseasyMultiple ChoiceObjective-mapped

AWS Glue: Serverless Spark for Big Data Analytics

This CLF-C02 practice question tests your understanding of cloud technology and services. 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.

Which AWS service provides a serverless, fully managed Apache Spark processing engine for big data analytics without managing clusters?

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

AWS Glue (serverless Apache Spark ETL)

AWS Glue provides a fully managed, serverless Apache Spark environment for ETL (extract, transform, load) workloads. It automatically provisions, configures, and scales the Spark cluster behind the scenes, so you don't need to manage any infrastructure. This makes it the correct choice for a serverless Apache Spark processing engine for big data analytics.

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 EMR on EC2

    Why it's wrong here

    EMR on EC2 requires provisioning and managing EC2 cluster nodes — it's not serverless.

  • Amazon Redshift

    Why it's wrong here

    Redshift is a managed data warehouse using columnar SQL — it doesn't run Apache Spark workloads.

  • AWS Glue (serverless Apache Spark ETL)

    Why this is correct

    AWS Glue provides a serverless Apache Spark environment for ETL processing — no cluster provisioning or management, automatic scaling, and pay-per-DPU-second pricing.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Amazon Kinesis Data Analytics

    Why it's wrong here

    Kinesis Data Analytics processes streaming data using SQL or Apache Flink — not batch-oriented Apache Spark ETL.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Amazon EMR (which can run Spark but requires cluster management) with a fully serverless Spark offering, or they mistakenly think Amazon Kinesis Data Analytics supports Apache Spark when it actually supports Apache Flink and SQL for stream processing.

Detailed technical explanation

How to think about this question

Under the hood, AWS Glue uses a dynamic scaling model where the Spark cluster is provisioned on-demand based on the workload's data partitioning and transformation complexity. It integrates with the AWS Glue Data Catalog as a central metadata repository, enabling schema discovery and versioning. In a real-world scenario, a data engineer can run a complex multi-table join and aggregation job on terabytes of data without ever configuring a single EC2 instance or cluster parameter.

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

An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

What to study next

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FAQ

Questions learners often ask

What does this CLF-C02 question test?

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: AWS Glue (serverless Apache Spark ETL) — AWS Glue provides a fully managed, serverless Apache Spark environment for ETL (extract, transform, load) workloads. It automatically provisions, configures, and scales the Spark cluster behind the scenes, so you don't need to manage any infrastructure. This makes it the correct choice for a serverless Apache Spark processing engine for big data analytics.

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.

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Last reviewed: Jun 11, 2026

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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.