New Year Sale 2026! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Google Professional Cloud Developer Exam - Topic 16 Question 101 Discussion

Actual exam question for Google's Professional Cloud Developer exam
Question #: 101
Topic #: 16
[All Professional Cloud Developer Questions]

Your company is planning to migrate their on-premises Hadoop environment to the cloud. Increasing storage cost and maintenance of data stored in HDFS is a major concern for your company. You also want to make minimal changes to existing data analytics jobs and existing architecture. How should you proceed with the migration?

Show Suggested Answer Hide Answer
Suggested Answer: D

by Jaime at Jan 26, 2025, 04:24 PM

Limited Time Offer

25%

Off

Get Premium Professional Cloud Developer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Lera
3 months ago
Surprised to see so many options, thought it’d be simpler!
upvoted 0 times
...
Tammara
3 months ago
Moving to HDD? That sounds risky for performance.
upvoted 0 times
...
Marjory
3 months ago
Isn't BigQuery better for analytics though?
upvoted 0 times
...
Veda
4 months ago
Totally agree, option D seems the best for minimal changes!
upvoted 0 times
...
Dana
4 months ago
I heard Cloud Dataproc is great for Hadoop migrations.
upvoted 0 times
...
Elly
4 months ago
I'm a bit confused about the cost implications of using HDD versus SSD in Compute Engine. I thought SSDs were generally better for performance, but maybe HDDs are cheaper?
upvoted 0 times
...
Frederic
4 months ago
I practiced a similar question about migrating Hadoop, and I feel like using Cloud Dataproc makes sense since it supports Hadoop jobs directly.
upvoted 0 times
...
Ezekiel
4 months ago
I think migrating to BigQuery could be a good choice, but it might require more changes to the analytics jobs than we want.
upvoted 0 times
...
Leontine
5 months ago
I remember we discussed how Cloud Dataproc can help with minimal changes to existing jobs, but I'm not sure if moving data to Cloud Storage is the best option.
upvoted 0 times
...
Moon
5 months ago
I feel pretty confident about this one. The key is to leverage a managed service like Cloud Dataproc to handle the migration, and then use Cloud Storage for the data to reduce costs. Option D seems like the best approach to me.
upvoted 0 times
...
Lai
5 months ago
Option C looks promising - using Cloud Dataproc to migrate the Hadoop environment while moving the data to larger, cheaper storage. That could be a good balance of cost savings and minimal changes.
upvoted 0 times
...
Malcom
5 months ago
Hmm, I'm a bit confused by the options. Migrating to BigQuery seems like a big change, and I'm not sure if that would really meet the requirement of minimal changes. I'll have to think this through carefully.
upvoted 0 times
...
Thora
5 months ago
This seems like a straightforward migration question. I'd focus on minimizing changes to the existing architecture and jobs, so I'm leaning towards option D.
upvoted 0 times
...
Louvenia
5 months ago
I think I'm leaning towards Option C. Migrating to a Dataproc cluster and using larger HDD disks seems like a good balance of cost savings and minimal changes.
upvoted 0 times
...
Juan
5 months ago
I'm a bit confused by the differences between the Dataproc and BigQuery options. I'll need to research those more to decide.
upvoted 0 times
...
Leonida
5 months ago
Option D sounds promising - migrating the code and using Cloud Storage could help minimize changes while saving on storage costs.
upvoted 0 times
...
Audria
5 months ago
Hmm, the options seem to cover a range of approaches. I'll need to think through the pros and cons of each one.
upvoted 0 times
...
Thurman
5 months ago
This looks like a tricky question. I'll need to carefully consider the requirements around minimal changes and cost savings.
upvoted 0 times
...
Kristofer
10 months ago
Option A looks tempting, but I'm not sure BigQuery is the best fit for our existing Hadoop-based analytics jobs. Rewriting all those jobs seems like a lot of unnecessary work. Option D seems like the perfect balance of cost savings and minimal changes to our architecture.
upvoted 0 times
Rodolfo
8 months ago
Let's proceed with creating a Cloud Dataproc cluster and migrating our Hadoop code objects to the new cluster.
upvoted 0 times
...
Amie
8 months ago
We should definitely consider moving our data to Cloud Storage and leveraging the Cloud Dataproc connector.
upvoted 0 times
...
Rima
9 months ago
Option D does seem like a good balance of cost savings and minimal changes to our architecture.
upvoted 0 times
...
Jacob
9 months ago
I agree, rewriting all those jobs for BigQuery does seem like a lot of unnecessary work.
upvoted 0 times
...
...
Selene
10 months ago
Haha, Option B is a classic 'let's just throw more hardware at the problem' approach. I doubt our management would be too impressed with that strategy. We need a more strategic, cloud-focused solution like what's described in Option D.
upvoted 0 times
...
Vonda
10 months ago
I'm a bit skeptical about Option C. Migrating HDFS data to larger HDD disks doesn't seem like it will address the core issue of high storage costs. We should look for a solution that truly optimizes our storage costs, like Option D.
upvoted 0 times
Mitzie
10 months ago
Yeah, moving our data to Cloud Storage and using the Cloud Dataproc connector sounds like a more efficient solution.
upvoted 0 times
...
Daryl
10 months ago
I agree, Option D seems like a better choice for optimizing storage costs.
upvoted 0 times
...
...
Corinne
11 months ago
I prefer option D. Moving our data to Cloud Storage and using the Cloud Dataproc connector for running jobs seems like a more scalable solution for our company's needs.
upvoted 0 times
...
Cassie
11 months ago
Option D seems like the most straightforward approach. It allows us to keep our existing Hadoop code while migrating the data to the more cost-effective Cloud Storage. The Cloud Dataproc connector will make it easy to run our jobs on the new data location.
upvoted 0 times
Tyisha
9 months ago
Yes, it's important to find a solution that minimizes changes to our existing data analytics jobs and architecture.
upvoted 0 times
...
Kaycee
10 months ago
We should definitely consider moving our data to Cloud Storage to save on storage costs.
upvoted 0 times
...
Darrel
10 months ago
I agree, leveraging the Cloud Dataproc connector will definitely make it easier to run our jobs on the new data location.
upvoted 0 times
...
Dallas
10 months ago
Option D seems like the most straightforward approach. It allows us to keep our existing Hadoop code while migrating the data to the more cost-effective Cloud Storage.
upvoted 0 times
...
...
Solange
11 months ago
I agree with Nathalie. Option C seems like the most efficient way to proceed with the migration while minimizing changes to our existing architecture.
upvoted 0 times
...
Nathalie
11 months ago
I think option C sounds like a good plan. It allows us to migrate our Hadoop environment to Cloud Dataproc and save on storage costs by moving data to larger HDD disks.
upvoted 0 times
...

Save Cancel