For this question, refer to the Dress4Win case study. Which of the compute services should be migrated as-is and would still be an optimized architecture for performance in the cloud?
A.
Web applications deployed using App Engine standard environment
B.
RabbitMQ deployed using an unmanaged instance group
C.
Hadoop/Spark deployed using Cloud Dataproc Regional in High Availability mode
D.
Jenkins, monitoring, bastion hosts, security scanners services deployed on custom machine types
Question is about compute services to be migrated as ""is and would still be an optimized architecture for performance - Apache Hadoop/Spark servers underline is compute and Hadoop/Spark deployed using Cloud Dataproc seems to be the correct answer.. Hence C seems correct answer to me
Read the previous questions ... they are going to use Managed instance groups with Tomcat &nginx installed on that so app engine is not in picture. Hadoop workloads goes to dataproc as it is.
Google Cloud includes Dataproc, which is a managed Hadoop and Spark environment. You can use Dataproc to run most of your existing jobs with minimal alteration, so you don't need to move away from all of the Hadoop tools you already know.
A. Web applications deployed using App Engine standard environment - there are multiple web apps, seems project limit of 1 - and not clear on the implications of Standard Env, with Nginx (there seems to be discussions) -- no not clear on this.
B. RabbitMQ - is always replaced by Pub/Sub - So No.
C. Hadoop/Spark - This is a well know Use Case
D. Jenkins, Etc, these duplicate GCP products so it can't be the answer.
My bet is C
It's C. hardoop == dataproc. pretty much a cloud version.
D is "Jenkins, monitoring, bastion hosts, security scanners". How can you make them as-is to run in cloud? Monitoring? on-prem to cloud no change? security scanner? no change?
C and D make sense. However, "would still be an optimized architecture". In this case, I chose C because we can move our services as is and we can get significant benefits from GCP
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