AWS Outposts for On-Premises Hadoop and Spark Processing

SAA-C03 By islever Editorial Last updated

Design scalable and loosely coupled architectures.

Short answer

C Migrate the Apache Hadoop and Spark applications to Amazon EMR clusters on AWS Outposts to process data on-premises.

Question

A company’s applications use Apache Hadoop and Apache Spark to process data on premises. The existing infrastructure is not scalable and is complex to manage. A solutions architect must design a scalable solution that reduces operational complexity. The solution must keep the data processing on premises. Which solution will meet these requirements?
  1. Use AWS Site-to-Site VPN to access the on-premises Hadoop Distributed File System (HDFS) data and application. Use an Amazon EMR cluster to process the data.
  2. Use AWS DataSync to connect to the on-premises Hadoop Distributed File System (HDFS) cluster. Create an Amazon EMR cluster to process the data.
  3. Migrate the Apache Hadoop application and the Apache Spark application to Amazon EMR clusters on AWS Outposts. Use the EMR clusters to process the data. Correct Answer
  4. Use an AWS Snowball device to migrate the data to an Amazon S3 bucket. Create an Amazon EMR cluster to process the data.

Key Takeaways

The key constraint is keeping data processing on-premises; AWS Outposts extends AWS services like EMR to customer data centers, satisfying scalability and locality requirements simultaneously.

This question tests designing scalable architectures using AWS Outposts to maintain on-premises data processing. The correct solution leverages Amazon EMR on Outposts to bring managed Hadoop/Spark capabilities to the local environment.

Common mistake: Many learners choose B or D because they assume migrating data to S3 is the standard path for Hadoop workloads, overlooking the explicit requirement that processing must remain on-premises.

Expert Analysis

Why the Answer Is Correct

Option C is the only choice that keeps the data processing physically on-premises while providing a scalable, managed solution. AWS Outposts delivers dedicated AWS infrastructure (including Amazon EMR) within a customer's on-premises data center. This allows the company to use native Apache Hadoop and Spark APIs on EMR without moving the compute workload to the public cloud.

Why the Other Options Are Wrong

Options A, B, and D all involve sending data out of the on-premises environment to AWS services like Amazon S3 or VPC endpoints. Even if Option A attempts to access HDFS remotely, it introduces significant latency and management complexity, failing the 'reduces operational complexity' and 'scalable' criteria compared to a native Outposts deployment. The core failure in A, B, and D is that they move the processing logic off-site or require complex hybrid networking that doesn't solve the management burden.

Community Comment Notes

The community consensus strongly supports Option C, with users noting that it is the 'only solution to keep the processing on-prem.' Comments highlight that the phrase 'keep the data processing on premises' is the critical discriminator that eliminates options involving S3 migration or remote VPN access.

Exam Strategy

Always scan for location constraints like 'on-premises,' 'local,' or 'hybrid.' If the requirement specifies that compute or processing must stay in a specific location, any option that moves the data or compute to the cloud is incorrect, regardless of how scalable the cloud alternative might be.

Frequently Asked Questions

Why can't I just use Site-to-Site VPN to connect to on-prem HDFS?

VPN creates network connectivity but does not solve the management complexity or scalability of the Hadoop cluster itself. You still manage the on-prem Hadoop nodes, which contradicts the goal of reducing operational complexity.

Is Amazon EMR on Outposts different from standard Amazon EMR?

Yes, EMR on Outposts runs on dedicated Outposts hardware within your data center, allowing you to use the same EMR APIs and tools but with data staying on-premises and low-latency access.

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Community Votes

C
100%

100% of anonymous learners picked answer C. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 5 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 5

  1. anikolov 👍 14 Answered C
    C cover requirement: The solution must keep the data processing on premises
  2. Andy_09 👍 9
    I would go for option C, as data processing has to be done on premise.
  3. Hung23 👍 3 Answered B
    Create an Amazon EMR Cluster: With the data now available in Amazon S3, the company can create an Amazon EMR cluster for data processing. EMR provides scalable Hadoop and Spark clusters that can process data stored in S3, enabling the company to leverage cloud-based processing resources while still keeping the data processing on premises.
  4. sandordini 👍 2 Answered C
    Only solution to keep the processing on-prem.
  5. Scheldon 👍 2 Answered C
    Answer C

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