Exam Professional Cloud Architect topic 1 question 160 discussion

answer is definitely D https://cloud.google.com/storage/docs/request-rate#naming-convention "A longer randomized prefix provides more effective auto-scaling when ramping to very high read and write rates. For example, a 1-character prefix using a random hex value provides effective auto-scaling from the initial 5000/1000 reads/writes per second up to roughly 80000/16000 reads/writes per second, because the prefix has 16 potential values. If your use case does not need higher rates than this, a 1-character randomized prefix is just as effective at ramping up request rates as a 2-character or longer randomized prefix." Example: my-bucket/2fa764-2016-05-10-12-00-00/file1 my-bucket/5ca42c-2016-05-10-12-00-00/file2 my-bucket/6e9b84-2016-05-10-12-00-01/file3

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview QUESTION 6 For this question, refer to the Helicopter Racing League (HRL) case study. A recent finance audit of cloud infrastructure noted an exceptionally high number of Compute Engine instances are allocated to do video encoding and transcoding. You suspect that these Virtual Machines are zombie machines that were not deleted after their workloads completed. You need to quickly get a list of which VM instances are idle. What should you do? A. Log into each Compute Engine instance and collect disk, CPU, memory, and network usage statistics for analysis. B. Use the gcloud compute instances list to list the virtual machine instances that have the idle: true label set. C. Use the gcloud recommender command to list the idle virtual machine instances. D. From the Google Console, identify which Compute Engine instances in the managed instance groups are no longer responding to health check probes.

This question is messed up. The formatting, the discussion, everything. I have no idea what to choose here. Chat GPT thinks the answer is C but most think it is D and there's not much difference between the two answers.

The question is how to reduce the data loss, the answer should be something like separation of duty, data lost prevention, but answer D is for reducing latency retrieving data. I'm baffled by this question.

I agree with D, but then, using a random prefix wouldn't it make more difficult the file retrieve?

Why not option B??

I was thinking correct answer was A, because we should have some kind of bucket rotation in order to avoid hiting the max size of a bucket. However it seems there is no size limit for a GCP cloud bucket, so I will have to agree with community and stick to answer D.

D is the correct answer https://cloud.google.com/storage/docs/request-rate#naming-convention

D: https://cloud.google.com/storage/docs/request-rate#naming-convention

D is the correct answer

vote D

Request admin to intervene and delete the hijacking of the question by kopper2019

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview QUESTION 5 For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost- effective approach for storing their race data such as telemetry. They want to keep all historical records, train models using only the previous season's data, and plan for data growth in terms of volume and information collected. You need to propose a data solution. Considering HRL business requirements and the goals expressed by CEO S. Hawke, what should you do? A. Use Firestore for its scalable and flexible document-based database. Use collections to aggregate race data by season and event. B. Use Cloud Spanner for its scalability and ability to version schemas with zero downtime. Split race data using season as a primary key. C. Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on season. D. Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL. Use separate database instances for each season.

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview QUESTION 4 For this question, refer to the Helicopter Racing League (HRL) case study. HRL wants better prediction accuracy from their ML prediction models. They want you to use Google’s AI Platform so HRL can understand and interpret the predictions. What should you do? A. Use Explainable AI. B. Use Vision AI. C. Use Google Cloud’s operations suite. D. Use Jupyter Notebooks.

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview QUESTION 3 For this question, refer to the Helicopter Racing League (HRL) case study. The HRL development team releases a new version of their predictive capability application every Tuesday evening at 3 a.m. UTC to a repository. The security team at HRL has developed an in-house penetration test Cloud Function called Airwolf. The security team wants to run Airwolf against the predictive capability application as soon as it is released every Tuesday. You need to set up Airwolf to run at the recurring weekly cadence. What should you do? A. Set up Cloud Tasks and a Cloud Storage bucket that triggers a Cloud Function. B. Set up a Cloud Logging sink and a Cloud Storage bucket that triggers a Cloud Function. C. Configure the deployment job to notify a Pub/Sub queue that triggers a Cloud Function. D. Set up Identity and Access Management (IAM) and Confidential Computing to trigger a Cloud Function.

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview QUESTION 2 For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional racing league in Cape Town, South Africa. In an effort to give customers in Cape Town a better user experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are a member of the HRL security team and you need to configure the update that will allow only the Fastly IP address ranges through the External HTTP(S) load balancer. Which command should you use?

- New Q, 06/2021 Helicopter Racing League Testlet 1 Company overview Helicopter Racing League (HRL) is a global sports league for competitive helicopter racing. Each year HRL holds the world championship and several regional league competitions where teams compete to earn a spot in the world championship. HRL offers a paid service to stream the races all over the world with live telemetry and predictions throughout each race. Solution concept HRL wants to migrate their existing service to a new platform to expand their use of managed AI and ML services to facilitate race predictions. Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.