- (Exam Topic 5)
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?

1. A. Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
2. B. Enable autoscaling on the GKE cluster and enable horizontal pod autoscaling on your application deployment
3. C. Send curl requests to your application, and validate if the auto scaling works.
4. D. Replicate the application over multiple GKE clusters in every Google Cloud regio
5. E. Configure a global HTTP(S) load balancer to expose the different clusters over a single global IP address.
6. F. Use Cloud Debugger in the development environment to understand the latency between the different microservices.

Correct Answer: B

- (Exam Topic 5)
You are using Cloud SQL as the database backend for a large CRM deployment. You want to scale as usage increases and ensure that you don’t run out of storage, maintain 75% CPU usage cores, and keep replication lag below 60 seconds. What are the correct steps to meet your requirements?

1. A. 1) Enable automatic storage increase for the instance.2) Create a Stackdriver alert when CPU usage exceeds 75%, and change the instance type to reduce CPU usage.3) Create a Stackdriver alert for replication lag, and shard the database to reduce replication time.
2. B. 1) Enable automatic storage increase for the instance.2) Change the instance type to a 32-core machine type to keep CPU usage below 75%.3) Create a Stackdriver alert for replication lag, and shard the database to reduce replication time.
3. C. 1) Create a Stackdriver alert when storage exceeds 75%, and increase the available storage on the instance to create more space.2) Deploy memcached to reduce CPU load.3) Change the instance type to a 32-core machine type to reduce replication lag.
4. D. 1) Create a Stackdriver alert when storage exceeds 75%, and increase the available storage on the instance to create more space.2) Deploy memcached to reduce CPU load.3) Create a Stackdriver alert for replication lag, and change the instance type to a 32-core machine type to reduce replication lag.

Correct Answer: A

- (Exam Topic 2)
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data. What is the most cost-effective way to run this job?

1. A. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
2. B. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
3. C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.
4. D. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the jo

Correct Answer: D
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it’s much better for write-once-read-many scenarios. This means frequently accessed (e.g. “hot” objects) around the world, such as website content, streaming videos, gaming or mobile applications.
References:
https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-performance-5c847ac8f

- (Exam Topic 5)
You need to deploy a stateful workload on Google Cloud. The workload can scale horizontally, but each instance needs to read and write to the same POSIX filesystem. At high load, the stateful workload needs to support up to 100 MB/s of writes. What should you do?

1. A. Use a persistent disk for each instance.
2. B. Use a regional persistent disk for each instance.
3. C. Create a Cloud Filestore instance and mount it in each instance.
4. D. Create a Cloud Storage bucket and mount it in each instance using gcsfuse.

Correct Answer: C
https://cloud.google.com/storage/docs/gcs-fuse#notes
Cloud Filestore: Cloud Filestore is a scalable and highly available shared file service fully managed by
Google. Cloud Filestore provides persistent storage ideal for shared workloads. It is best suited for enterprise applications requiring persistent, durable, shared storage which is accessed by NFS or requires a POSIX compliant file system.
Reference: https://cloud.google.com/storage/docs/gcs-fuse

- (Exam Topic 7)
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

1. A. Replace the existing data warehouse with BigQuer
2. B. Use table partitioning.
3. C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
4. D. Replace the existing data warehouse with BigQuer
5. E. Use federated data sources.
6. F. Replace the existing data warehouse with a Compute Engine instance with 96 CPU
7. G. Add an additional Compute Engine pre-emptible instance with 32 CPUs.

Correct Answer: C
https://cloud.google.com/solutions/bigquery-data-warehouse#external_sources https://cloud.google.com/solutions/bigquery-data-warehouse