Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?
A.
Create a Cloud Monitoring dashboard based on the BigQuery metric query/scanned_bytes
B.
Create a Cloud Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
C.
Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Cloud Monitoring dashboard based on the custom metric
D.
Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Cloud Monitoring dashboard based on the custom metric
Viewing project and reservation slot usage in Stackdriver Monitoring
Information is available from the "Slots Allocated" metric in Stackdriver Monitoring. This metric information includes a per-reservation and per-job breakdown of slot usage. The information can also be visualized by using the custom charts metric explorer.
https://cloud.google.com/bigquery/docs/reservations-monitoring
https://cloud.google.com/monitoring/api/metrics_gcp
The slots/allocated_for_project metric provides information about the number of slots allocated to each project. It directly reflects the slot usage, making it a relevant and accurate metric for monitoring slot allocation within each project.
Options A, C, and D involve log exports and custom metrics, but they may not be as straightforward or provide the same level of detail as the built-in metric slots/allocated_for_project:
The naming is quite misleading in this case, but it actually seems from the documentation that slots/allocated_for_project indicates the "slots used by project", in which case answer B is correct: https://cloud.google.com/monitoring/api/metrics_gcp#:~:text=slots/allocated_for_project%20GA%0ASlots%20used%20by%20project
B slots/allocated_for_project will give you the total number of slots allocated to each project, but it will not tell you how many slots are actually being used.
The purpose to monitor 'slot usgae' is for billing. 'slot/allocated' means nothing.
Option D is better than B.
And, the question mention 'Each analytics team in organization', so it should be 'organization level'.
If 'usage' = how the slots are being used, D is the corret answer
If 'usage' = how the slots are being allocated, B is the correct answer
I think in this question, usage = how the slots are being used
Answer B,
Why not D, aggregated log export is good but it will generate all the details which is large in size and costly too. you dont need all the information. It can break data privacy. so look for B because this much is asked only. Normally, i make such errors alot.
The correct answer is B. You should create a Cloud Monitoring dashboard based on the BigQuery metric slots/allocated_for_project.
This metric represents the number of BigQuery slots allocated for a project. By creating a Cloud Monitoring dashboard based on this metric, you can monitor the slot usage within each project in your organization. This will allow each team to monitor their own slot usage and ensure that they are not exceeding their allocated quota.
Option A is incorrect because the query/scanned_bytes metric represents the number of bytes scanned by BigQuery queries, not the slot usage.
Option C is incorrect because it involves creating a log export for each project and using a custom metric based on the totalSlotMs field. While this may be a valid way to monitor slot usage, it is more complex than simply using the slots/allocated_for_project metric.
Option D is also incorrect because it involves creating an aggregated log export at the organization level, which is not necessary for monitoring slot usage within individual projects.
B the below is related to the question.
https://cloud.google.com/blog/topics/developers-practitioners/monitoring-bigquery-reservations-and-slot-utilization-information_schema
B. Create a Cloud Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
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