When encountering a quotaExceeded error in BigQuery, you should follow these steps to diagnose and mitigate the issue:
* Understand the Error:
* The error message indicates that a quota was exceeded (either a short-term rate limit or a longer- term limit).
* The response payload contains information about which quota was reached.
* Quotas can fall into two categories:
* rateLimitExceeded: Short-term limits. Retry the operation after a few seconds using exponential backoff.
* quotaExceeded: Longer-term limits. Wait 10 minutes or longer before retrying the operation.
* Search Errors in Cloud Audit Logs (Option A):
* Cloud Audit Logs provide detailed information about API requests and responses.
* By searching the logs, you can identify the specific API call that triggered the quotaExceeded error.
* This helps you understand which resource or operation exceeded the quota.
* View Errors in Cloud Monitoring (Option C):
* Cloud Monitoring (formerly known as Stackdriver) provides insights into your Google Cloud resources.
* Check the monitoring dashboard for any alerts related to BigQuery quotas.
* You can set up custom monitoring rules to track specific quotas and receive notifications.
* Other Options:
* B. Configure Cloud Trace: Cloud Trace is used for performance analysis and latency tracking. It' s not directly related to quota issues.
* D. Use Information Schema Views: Information schema views provide metadata about your datasets and tables but won't help diagnose quota errors.
* E. Use BigQuery Bl Engine: There is no such tool called "BigQuery Bl Engine." This option is invalid.
Remember that some quotas replenish incrementally over a 24-hour period, so you don't always need to wait a full 24 hours after reaching the limit. If you consistently hit longer-term quotas, consider workload optimization or requesting a quota increase

gcloud compute networks subnets expand-ip-range NAME gcloud compute networks subnets expand-ip-range
- expand the IP range of a Compute Engine subnetworkhttps://cloud.google.com/sdk/gcloud/reference
/compute/networks/subnets/expand-ip-range

Cloud Storage allows world-wide storage and retrieval of any amount of data at any time. We dont need to set up auto-scaling ourselves. Cloud Storage autoscaling is managed by GCP. Cloud Storage is an object store so it is suitable for storing photos. Cloud Storage allows world-wide storage and retrieval so cater well to our worldwide audience. Cloud storage provides us lifecycle rules that can be configured to automatically delete objects older than 30 days. This also fits our requirements. Finally, Google Cloud Storage offers several storage classes such as Nearline Storage ($0.01 per GB per Month) Coldline Storage ($0.007 per GB per Month) and Archive Storage ($0.004 per GB per month) which are significantly cheaper than any of the options above.
Ref: https://cloud.google.com/storage/docs
Ref: https://cloud.google.com/storage/pricing

* Run gcloud builds submit tag gcr.io/img-278322/acme_track_n_trace:v1. is the right answer.
This command correctly tags the image as acme_track_n_trace:v1 and uploads the image to the img-278322 project.
Ref: https://cloud.google.com/sdk/gcloud/reference/builds/submit

"Billing Account Viewer access would usually be granted to finance teams, it provides access to spend information, but does not confer the right to link or unlink projects or otherwise manage the properties of the billing account." https://cloud.google.com/billing/docs/how-to/billing-access