Associate-Cloud-Engineer Exam Dumps - Google Cloud Certified Questions and Answers

https://cloud.google.c om/vpc/docs/vpc#manually_created_subnet_ip_ranges

IAP controls access to your App Engine apps and Compute Engine VMs running on Google Cloud. It leverages user identity and the context of a request to determine if a user should be allowed access. IAP is a building block toward BeyondCorp, an enterprise security model that enables employees to work from untrusted networks without using a VPN.

By default, IAP uses Google identities and IAM. By leveraging Identity Platform instead, you can authenticate users with a wide range of external identity providers, such as:

Email/password

OAuth (Google, Facebook, Twitter, GitHub, Microsoft, etc.)

SAML

OIDC

Phone number

Custom

Anonymous

This is useful if your application is already using an external authentication system, and migrating your users to Google accounts is impractical.

https://cloud.google.com/iap/docs/u sing-tcp-forwarding#grant-permission

Cloud Spanner is a relational database and is highly scalable. Cloud Spanner is a highly scalable, enterprise-grade, globally-distributed, and strongly consistent database service built for the cloud specifically to combine the benefits of relational database structure with a non-relational horizontal scale. This combination delivers high-performance transactions and strong consistency across rows, regions, and continents with an industry-leading 99.999% availability SLA, no planned downtime, and enterprise-grade security

Ref: https://cloud.google.com/sp anner

Graphical user interface, application, Teams Description automatically generated

Let's analyze each option:

A. Using gsutil: While gsutil can transfer data to Cloud Storage, for 150 TB of infrequently accessed data, direct transfer over the network might be slow and consume significant bandwidth, potentially impacting other network operations. It also lacks built-in mechanisms for filtering files based on age.

B. Using Cloud Interconnect and Filestore: Cloud Interconnect provides a dedicated connection, but Filestore is a fully managed NFS service primarily designed for high-performance file sharing for applications running in Google Cloud. Migrating 150 TB of infrequently accessed data to Filestore would be cost-inefficient compared to Cloud Storage and doesn't directly address the requirement of moving older than one year files.

C. Using Transfer Appliance: Transfer Appliance is suitable for very large datasets (petabytes) or when network connectivity is poor or unreliable. While it addresses bandwidth concerns, it involves a physical appliance and might be an overkill for 150 TB of data, especially if network connectivity is reasonable.

D. Using Storage Transfer Service: Storage Transfer Service is specifically designed for moving large amounts of data between online storage systems, including on-premises file systems and Cloud Storage. It offers features like filtering by file age, scheduling transfers, and bandwidth control, directly addressing all the requirements of the question: migrating infrequently accessed files older than one year to Cloud Storage, minimizing costs (by using appropriate Cloud Storage classes for infrequent access), and controlling bandwidth usage.

Google Cloud Documentation References:

Storage Transfer Service Overview: https://cloud.google.com/storage-transfer-service/docs/overview - This page details the capabilities and use cases of Storage Transfer Service, including transferring from on-premises.

Storage Transfer Service for on-premises data: https://cloud.google.com/storage-transfer-service/docs/on-prem-overview - This specifically covers transferring data from on-premises file systems.

Cloud Storage Classes: https://cloud.google.com/storage/docs/storage-classes - Understanding the different storage classes (Standard, Nearline, Coldline, Archive) is crucial for cost optimization of infrequently accessed data. Storage Transfer Service can be configured to move data to a cost-effective class like Nearline or Coldline.

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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. Ifyou consistently hit longer-term quotas, consider workload optimization or requesting a quota increase

https://cloud.google.com/sdk/gcloud/reference/compute/networks/subnets/expand-ip-range

gcloud compute networks subnets expand-ip-range - expand the IP range of a Compute Engine subnetwork gcloud compute networks subnets expand-ip-range NAME --prefix-length=PREFIX_LENGTH [--region=REGION] [GCLOUD_WIDE_FLAG …]

https://cloud.google.com/monitoring/settings/multiple-projects

https://cloud.google.com/monitoring/workspaces

(https://cloud.google.com/resource-manager/docs/project-migration#change_billing_account )

https://cloud.google.com/billing/docs/concepts

https://cloud.google.com/resource-manager/docs/project-migration

"large quantity" : Cloud Storage or BigQuery "files" a file is nothing but an Object