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

https://cloud.google.com/storage/docs/audit-logs

https://cloud.google.com/compute/docs/logging/a udit-logging#audited_operations

https://cloud.google.com/compute/docs/disks/local-ssd

Best practices for persistent disk snapshots

You can create persistent disk snapshots at any time, but you can create snapshots more quickly and with greater reliability if you use the following best practices.

Creating frequent snapshots efficiently

Use snapshots to manage your data efficiently.

Create a snapshot of your data on a regular schedule to minimize data loss due to unexpected failure.

Improve performance by eliminating excessive snapshot downloads and by creating an image and reusing it.

Set your snapshot schedule to off-peak hours to reduce snapshot time.

Snapshot frequency limits

Creating snapshots from persistent disks

You can snapshot your disks at most once every 10 minutes. If you want to issue a burst of requests to snapshot your disks, you can issue at most 6 requests in 60 minutes.

If the limit is exceeded, the operation fails and returns the following error:

https://cloud.google.com/compute/docs/disks/snapshot-best-practices

An external HTTP(S) load balancer is a Google-recommended solution for distributing web traffic across multiple regions and zones, and providing high availability, scalability, and security for web applications. It supports both IPv4 and IPv6 addresses, and can handle SSL/TLS termination and encryption. It also integrates with Cloud CDN, Cloud Armor, and Cloud Identity-Aware Proxy for enhanced performance and protection. A managed instance group (MIG) can be used as a backend service for the HTTP(S) load balancer, and can automatically scale the number of VM instances based on the CPU load. A Cloud Storage bucket can also be used as a backend service for the HTTP(S) load balancer, and can serve static content such as images, videos, or HTML files. A URL map can be used to route requests to different backend services based on the path or host of the request. For example, a URL map can send requests for /static/* to the Cloud Storage bucket, and requests for /dynamic/* to the MIG. A managed SSL certificate can be used to secure the connection between the clients and the load balancer, and can be automatically provisioned and renewed by Google.

A is incorrect because an internal HTTP(S) load balancer is only visible within a VPC network, and not to the public internet. It is used for internal applications that need to communicate with other internal services. Identity-Aware Proxy is a service that provides secure access to web applications without using a VPN. It is not a load balancer, and it does not distribute user traffic.

B is incorrect because installing HTTPS certificates on the instance is not necessary, as the HTTP(S) load balancer can handle SSL/TLS termination and encryption. It is also more complex and less secure to manage the certificates on the instance level, as they need to be updated and synchronized across multiple instances.

D is incorrect because an external network load balancer is a TCP/UDP load balancer that operates at the network layer. It is not suitable for web applications that use HTTP(S) protocols, as it does not support SSL/TLS termination and encryption, URL maps, or Cloud Storage backends. It is also less efficient and scalable to forward the requests to the Cloud Storage from the web servers, as it adds an extra hop and latency.

"Google Cloud VPC Network Peering allows internal IP address connectivity across two Virtual Private Cloud (VPC) networks regardless of whether they belong to the same project or the same organization."

https://cloud.google.com/vpc/docs/vpc-peering

while

"Cloud Interconnect provides low latency, high availability connections that enable you to reliably transfer data between your on-premises and Google Cloud Virtual Private Cloud (VPC) networks."

https://cloud.google.com/network-connectivity/docs/interconnect/concepts/overview

and

"HA VPN is a high-availability (HA) Cloud VPN solution that lets you securely connect your on-premises network to your VPC network through an IPsec VPN connection in a single region."

https://cloud.google.com/network-connectivity/docs/vpn/conce pts/overview

"...we recommend that you enable Cloud Billing data export to BigQuery at the same time that you create a Cloud Billing account. "https://cloud.google.com/billing/docs/how-to/export-data-bigquery

https://medium.com/google-cloud/analyzing-google-cloud-billing-data-with-big-query-30bae1c2aae4

Coldline Storage is a very-low-cost, highly durable storage service for storing infrequently accessed data. Coldline Storage is ideal for data you plan to read or modify at most once a quarter. Since we have a requirement to access data once a quarter and want to go with the most cost-efficient option, we should select Coldline Storage.

Ref: https://cloud.google.com/storage/docs/storage-classes#coldline

Comprehensive and Detailed In Depth Explanation:

The core requirements are secure access to a specific BigQuery dataset from a Compute Engine instance, using short-lived credentials, adhering to Google's best practices, and minimizing operational overhead.

A. Project-level IAM role: Granting the BigQuery Data Viewer role at the project level gives the service account broad access to all BigQuery datasets within that project. This violates the principle of least privilege, a fundamental security best practice, as the application should only have access to the designated dataset.

B. Hourly new service account with dataset-level role: While this aims to achieve short-lived credentials, the operational burden of creating, attaching, and managing IAM policies for a new service account every hour is significant and not a Google-recommended practice for routine access. It introduces unnecessary complexity and potential for errors.

C. Custom service account with dataset-level IAM role: This is the recommended and most efficient approach. You create a dedicated Google Cloud service account specifically for this application. You then grant this service account the necessary IAM role (e.g., BigQuery Data Viewer, or a more specific custom role) directly on the target BigQuery dataset. When the Compute Engine instance runs as this service account, the Google Cloud client libraries automatically handle the acquisition and rotation of short-lived OAuth 2.0 access tokens from the instance's metadata server. This eliminates the need to manage long-lived credentials (like service account keys) and ensures the application only has access to the intended dataset. This adheres to the principle of least privilege and minimizes operational costs.

D. Hourly new service account with project-level role: This option combines the high operational overhead of frequently creating new service accounts with the security risk of granting overly permissive project-level access. It is not a recommended practice.

Therefore, the most secure, cost-effective, and operationally efficient solution is to create a custom service account, attach it to the Compute Engine instance, and grant it the appropriate BigQuery IAM role specifically on the target dataset. The platform handles the short-lived credentials automatically.

Google Cloud Documentation References:

Creating and enabling service accounts for instances: https://cloud.google.com/compute/docs/access/create-enable-service-accounts-for-instances - Explains how to create and associate service accounts with Compute Engine VMs.  

Granting, changing, and revoking access to resources: https://cloud.google.com/iam/docs/granting-changing-revoking-access - Details how to manage IAM policies and grant roles to service accounts on specific resources (like BigQuery datasets).  

BigQuery IAM roles: https://cloud.google.com/bigquery/docs/control-access - Provides information on the various IAM roles available for controlling access to BigQuery resources at different levels (project, dataset, table, etc.).

Best practices for using service accounts: https://cloud.google.com/iam/docs/best-practices-for-using-service-accounts - Emphasizes the importance of the principle of least privilege and avoiding the management of long-lived service account keys when possible (relying on the metadata server for short-lived tokens).