Google Professional-Cloud-Security-Engineer Dumps

Assured Workloads for Google Cloud allows you to deploy regulated workloads with data residency, access, and support requirements. It helps you configure your environment in a manner that aligns with specific compliance frameworks and standards.

roles/logging.privateLogViewer (Private Logs Viewer) includes all the permissions contained by roles/logging.viewer, plus the ability to read Data Access audit logs in the _Default bucket.

With Google Cloud Directory Sync (GCDS), you can synchronize the data in your Google Account with your Microsoft Active Directory or LDAP server. GCDS doesn't migrate any content (such as email messages, calendar events, or files) to your Google Account. You use GCDS to synchronize your Google users, groups, and shared contacts to match the information in your LDAP server.

To ensure user-uploaded comments and product reviews do not include sensitive data before publication, use the Cloud Data Loss Prevention (DLP) API.

Enable DLP API:

Go to the Cloud Console and navigate to APIs & Services > Library.

Search for "Data Loss Prevention API" and enable it.

Configure DLP API:

Create an inspection template specifying the types of sensitive data to detect.

Set up de-identification templates if you want to redact or mask sensitive data.

Implement DLP in Application:

Use the Google Cloud DLP Client Library for the desired programming language.

Send the text data to the DLP API for inspection before saving or publishing.

from google.cloud import dlp_v2 dlp_client = dlp_v2.DlpServiceClient() parent = f"projects/{project_id}" item = {"value": "User comment text here"} inspect_config = {"info_types": [{"name": "PERSON_NAME"}, {"name": "CREDIT_CARD_NUMBER"}]} response = dlp_client.inspect_content(parent=parent, inspect_config=inspect_config, item=item)

Cloud Data Loss Prevention API Documentation

DLP API Client Libraries

The goal is to deploy 2SV with a phased rollout to control the number of individuals affected at once, minimizing disruption, and keeping management simple.

While OU structure can be used, managing policy exceptions based on Configuration Groups is the recommended and less complex way to handle phased rollouts of security settings like 2SV in Google's Admin console.

Extracts:

"When rolling out 2SV, it is highly recommended to use a phased deployment approach to manage the impact on user access and support resources." (Source 2.1)

"You can use configuration groups to select a subset of users within an OU structure and apply specific settings, such as 2SV enforcement, to them. This allows for a gradual, controlled rollout without needing to alter your primary organizational unit structure." (Source 2.2)

Groups allow you to easily add/remove users from the enforcement scope without moving their identity within the OU hierarchy (Option A), which keeps management complexity low. Options C and D do not allow for the necessary phased control of enforcement.

Set the Resource Location Restriction organization policy constraint at the Folder level:

Setting the constraint at the folder level allows for very granular control over data residency requirements.

Each folder can represent a specific geographical location, and projects within those folders will inherit the location constraint, ensuring compliance with regulatory requirements.

This approach provides flexibility to manage data residency across different regions within the same organization.

To meet the requirements of rotating the master key every 45 days, achieving FIPS 140-2 Level 3 validation, and ensuring the master key is stored redundantly in multiple US regions, you should use Customer-managed encryption keys with Cloud HSM. Here’s how:

Set Up Cloud HSM:

Deploy Cloud HSM in your Google Cloud environment. Cloud HSM provides a hardware-based key management solution that meets FIPS 140-2 Level 3 compliance.

Create and Manage Keys:

Create your encryption keys in Cloud HSM. These keys can be managed and rotated per your policy requirements.

Key Rotation:

Set up a key rotation schedule to rotate the master key every 45 days. Cloud HSM allows you to automate this process.

Geographic Redundancy:

Ensure that your Cloud HSM configuration spans multiple regions within the US to achieve redundancy. This will ensure that your keys are available even if a particular region experiences an outage.

Compliance:

Cloud HSM’s FIPS 140-2 Level 3 validation ensures that your encryption keys are managed in a secure and compliant manner.

Benefits:

Security and Compliance: Meets stringent compliance requirements.

Automated Management: Simplifies key management and rotation.

Redundancy: Ensures high availability of keys across multiple regions.

References

Cloud HSM Documentation

Key Management with Cloud KMS and Cloud HSM

Generate Supply Chain Levels for Software Artifacts (SLSA) level 3 assurance by using Cloud Build: SLSA is a framework for ensuring the integrity of software artifacts. By using Cloud Build, you can automate the build process and generate SLSA level 3 compliance, which includes verifiable build steps and provenance.

View the build provenance in the Security insights side panel within the Google Cloud console: The build provenance provides a detailed history of how the software was built, including the source code, build process, and any dependencies. This information is accessible through the Security insights side panel in the Google Cloud console, allowing you to verify the integrity and authenticity of your software artifacts.

References

Supply Chain Levels for Software Artifacts (SLSA) documentation

Cloud Build documentation

Security insights in Google Cloud console

To maintain proper security policies across numerous Google Cloud environments, especially with a large developer base and a small security team, it's crucial to implement automated and scalable security measures.​

Option A: While applying AI-recommended security posture templates can be beneficial, as of now, there isn't a specific predefined template for Gemini in Vertex AI within the Security Command Center.​

Option B: Publishing internal policies and guidelines is essential for promoting secure development practices but may not be sufficient alone to enforce or detect security policies.​

Option C: Implementing the principle of least privilege through Identity and Access Management (IAM) roles minimizes the risk of misconfigurations and unauthorized access by ensuring users have only the permissions necessary for their tasks.​

Option D: Applying organization policy constraints enforces specific configurations and restrictions across projects. Utilizing Security Health Analytics helps in detecting and monitoring deviations from these policies, providing automated insights into potential security issues.​

Option E: Using Cloud Logging to detect misconfigurations and triggering Cloud Run functions for remediation introduces complexity and may require significant maintenance, making it less practical for a small security team.​

Therefore, Options C and D are the most effective strategies. They provide automated enforcement and monitoring of security policies, aligning with the need for scalable solutions given the organization's size and resources.​

The problem requires gaining "detailed visibility into changes to IAM policies, user activity, service account behavior, and access to sensitive projects" due to security inconsistencies.

Cloud Audit Logs: Cloud Audit Logs records administrative activities, data access, and system events across Google Cloud. These logs are the primary source of truth for tracking "who did what, where, and when" in your Google Cloud environment.

Extract Reference: "Cloud Audit Logs maintains the following audit logs for each project, folder, and organization: Admin Activity audit logs, Data Access audit logs, System Event audit logs, Policy Denied audit logs."

Extract Reference: "Admin Activity audit logs contain log entries for API calls or other actions that modify the configuration or metadata of resources. Data Access audit logs record API calls that read the configuration or metadata of resources, as well as user-provided data." (Google Cloud Documentation: "Cloud Audit Logs overview" -

These logs directly capture:Changes to IAM policies: Recorded in Admin Activity logs.

User activity: Recorded in Admin Activity and Data Access logs.

Service account behavior: Actions performed by service accounts are logged in the same way as user actions.

Access to sensitive projects: Data Access logs, especially for sensitive data services, record access events.

Log Export Sinks: To gain "detailed visibility" and enable "correlation with other event sources," these audit logs should be exported to a centralized Security Information and Event Management (SIEM) solution. Log sinks allow you to route logs from Cloud Logging to various destinations, including BigQuery, Cloud Storage, or Pub/Sub (which can then feed into a SIEM).

Extract Reference: "You can use sinks to route some or all of your logs to supported destinations." and "Many security information and event management (SIEM) systems can ingest logs through Cloud Pub/Sub." (Google Cloud Documentation: "Routing and storage overview | Cloud Logging" -

Let's evaluate the other options:

A. OS Config Management agent: This service manages operating system configurations, patching, and inventory on VMs. It is not designed to monitor or log IAM policy changes, user activity, or service account behavior within Google Cloud's IAM system.

B. Metrics Explorer in Cloud Monitoring: While Cloud Monitoring can provide some metrics related to service account authentication, it focuses on time-series data and operational health metrics. It does not provide the detailed, event-level audit records necessary for forensic analysis of IAM policy changes, specific user actions, or granular access events to sensitive data that Cloud Audit Logs offer.

D. Cloud Functions triggered by IAM policy changes + Policy Simulator: This describes a reactive automation pattern for some IAM changes. While useful for immediate alerting on risky modifications, it's a custom solution for a subset of the requirements. It doesn't inherently provide "detailed visibility" into all user activity or comprehensive service account behavior across all projects, nor does it replace the robust logging and correlation capabilities of a SIEM solution ingesting raw audit logs. Cloud Audit Logs are the fundamental data source this approach would rely on.

Therefore, leveraging Cloud Audit Logs and exporting them to a SIEM is the most comprehensive and recommended approach for gaining detailed visibility into IAM-related changes and activities across your Google Cloud organization.

"In order to be able to keep using the existing identity management system, identities need to be synchronized between AD and GCP IAM. To do so google provides a tool called Cloud Directory Sync. This tool will read all identities in AD and replicate those within GCP. Once the identities have been replicated then it's possible to apply IAM permissions on the groups. After that you will configure SAML so google can act as a service provider and either you ADFS or other third party tools like Ping or Okta will act as the identity provider. This way you effectively delegate the authentication from Google to something that is under your control."

To mitigate the risk posed by long-running Google Cloud CLI sessions, it is essential to enforce a reauthentication frequency. This ensures that users must periodically reauthenticate, reducing the window of opportunity for an attacker to exploit an open session. Setting the reauthentication frequency to one hour forces users to reauthenticate after this period, thereby limiting the duration an attacker can use a compromised session.

Access Google Cloud Console: Log in to your Google Cloud Console using your admin credentials.

Navigate to Security Settings: Go to the "Security" section of the Cloud Console.

Set Session Control: Under the session management settings, locate the "Reauthentication frequency" setting. This controls how often users must reauthenticate.

Configure Reauthentication Frequency: Set the reauthentication frequency to "1 hour". This configuration will force users to reauthenticate every hour, thus limiting the duration of each session.

Save Changes: Confirm and save your changes. This setting will now apply to all users, ensuring that open sessions are minimized to a duration of one hour.

When using Google Cloud's Platform-as-a-Service (PaaS) offerings like App Engine, Google manages the infrastructure, including the underlying OS, runtime, and scaling. However, securing the application code itself, such as defending against cross-site scripting (XSS) and SQL injection (SQLi) attacks, remains the responsibility of the user. This involves implementing secure coding practices, validating inputs, and employing appropriate security measures within the application.

"The service evaluates all changes and remote access attempts to detect runtime attacks in near-real time." : This has nothing to do with KNOWN security Vulns in images

To maintain a historical record of what was running in Google Cloud Platform at any point in time, you should use Forseti Security to automate inventory snapshots. Forseti Security is an open-source toolkit that helps to automate security and compliance in GCP by taking inventory snapshots of GCP resources.

Step-by-Step:

Install Forseti Security:

Follow the installation guide to deploy Forseti Security on your GCP environment.

Configure Inventory:

Set up the inventory module in Forseti to capture and store snapshots of GCP resources.

Schedule Snapshots:

Use Forseti’s configuration to schedule regular inventory snapshots.

Access Historical Data:

Review and access historical records through Forseti’s dashboard or by querying the Forseti database.

Compliance and Monitoring: Use Forseti to ensure compliance and monitor changes over time.

Forseti Security Overview

Inventory Module

Firewall Rule Analysis: Analyze the existing VPC firewall rules to identify any rules that might allow traffic between VM instances based on the same service account.

Priority Check: Check the priority of these rules. A rule with a priority lower than 1000 (such as 999) will take precedence over your tag-based rules.

Service Account Configuration: Since your VM instances are deployed without any service account customization, they are likely using the default service account. A firewall rule allowing traffic between instances using this default service account will override the tag-based rules if it has a higher priority.

Testing and Validation: Disable or adjust the priority of the rule with priority 999 to test if the tag-based segmentation works correctly. Validate that the traffic is segmented according to your intended configuration. References:

Google Cloud - VPC Firewall Rules

Google Cloud - Service Accounts

Objective: Reduce the risk of Google Cloud user accounts being compromised.

Solution: Implement strong password policies and post-SSO 2-Step Verification using security keys.

Steps:

Step 1: In Active Directory, configure a domain password policy with strong settings (e.g., complexity, length, expiration).

Step 2: In the Google Admin console, navigate to the Security settings.

Step 3: Enable 2-Step Verification and configure it to use security keys for post-SSO verification.

Step 4: Ensure all users enroll in the 2-Step Verification with security keys.

Using strong password policies in Active Directory along with security keys for 2-Step Verification post-SSO provides enhanced security against account compromises.

The problem requires granting an external partner team access solely to a database, without extending to other network resources, and following Google-recommended practices.

Workforce Identity Federation: This Google Cloud IAM feature is specifically designed for scenarios where an organization needs to grant Google Cloud access to external identities (like partners, contractors, or customers) who are managed by their own identity provider (IdP). It allows these external users to authenticate using their existing credentials and then gain access to specified Google Cloud resources.

Extract Reference: "Workforce Identity Federation lets you use an external identity provider (IdP) to authenticate and authorize a workforce—a group of users, such as employees, partners, and contractors—using IAM, so that the users can access Google Cloud services." (Google Cloud Documentation: "Workforce Identity Federation | IAM Documentation" -

Extract Reference: "Secure access for partners and vendors. Workforce Identity Federation can enable enterprises to selectively federate users from partner or vendor IdPs without requiring IT teams to sync or create a separate identity store to use Google Cloud resources." (Google Cloud Documentation: "Introducing Workforce Identity Federation..." -

Least Privilege and Isolation: With Workforce Identity Federation, you create an identity pool and a provider that trusts the partner's IdP. You then grant IAM roles only to the workforce pool (or specific identities within it) on the specific database resource. This ensures fine-grained access control and prevents access to other resources in your network, directly addressing the least privilege and isolation requirements. The partner's identities are never synced into your internal Cloud Identity directory.

Let's evaluate the other options:

A. Add a public IP address... Securely distribute credentials: Adding a public IP address exposes the database to the internet, which is a major security risk and contradicts "restricted solely to the database and can not extend to any other resources within your company's network" as it allows any external network to potentially reach it. Distributing credentials manually is also not a Google-recommended secure practice.

B. Create accounts for the partner team in your corporate identity provider. Synchronize these accounts with Google Cloud Identity: This means you become responsible for managing the partner's identities within your own corporate IdP and syncing them. This is an unnecessary operational burden and blurs the lines of identity management. It also may inadvertently grant them broader network access if your corporate IdP is connected to your internal network resources.

C. Ask the partner team to set up Cloud Identity accounts within their own corporate environment and identity provider. Grant the partner’s Cloud Identity accounts access: While better than B, this implies the partner managing Cloud Identity accounts themselves and you directly granting IAM roles to their Cloud Identity users. Workforce Identity Federation is a more robust and scalable solution for federating any external IdP with Google Cloud IAM, rather than requiring partners to adopt Cloud Identity directly. Workforce Identity Federation is the explicit pattern for cross-organization access using existing external IdPs.

Therefore, Workforce Identity Federation is the most secure, scalable, and Google-recommended solution for granting restricted access to external partner teams.

To establish a reliable, cloud-native, and scalable process for updating nodes in your GKE clusters, configuring node auto-upgrades within designated maintenance windows is the most effective approach.​

Option A: Migrating to a self-managed Kubernetes environment would increase operational overhead and complexity, as your team would be responsible for managing the entire infrastructure, including patching and updates. This contradicts the goal of adopting a cloud-first strategy and does not inherently provide a more reliable update process.​

Option B: Developing custom scripts for patch management introduces potential risks and maintenance burdens. Ensuring the reliability, security, and scalability of such scripts can be challenging, and this approach may not align with best practices for managing GKE environments.​

Option C: Scheduling daily reboots does not guarantee that nodes will apply the latest patches or updates. Without a mechanism to manage and apply updates, reboots alone are insufficient to maintain node security and compliance.​

Option D: Configuring node auto-upgrades ensures that GKE automatically keeps your nodes up-to-date with the latest stable versions, reducing the risk of missed critical patches. By setting maintenance windows, you can control when these upgrades occur, minimizing disruptions to your workloads. This approach leverages GKE's managed services to maintain security and compliance efficiently.​

Therefore, Option D is the optimal solution, as it aligns with a cloud-first strategy and leverages GKE's native capabilities to automate and schedule node updates effectively.​

The key requirements are maintaining a specific set of controls, including data residency and personnel data access controls, specifically to meet a highly regulated industry's compliance program.

Assured Workloads is the specific Google Cloud service designed to help customers meet these stringent regulatory and compliance requirements (e.g., FINRA, FedRAMP, HIPAA, etc.) by enforcing a specific control bundle.

Extracts:

"Assured Workloads helps organizations run their sensitive workloads securely and in a compliant manner... by providing continuous compliance monitoring for specific compliance programs." (Source 4.1)

"When you create an Assured Workloads folder, the platform automatically enforces compliance controls... including: Data residency and location controls... Personnel access controls... Organizational policies..." (Source 4.2)

This service creates a dedicated, compliant environment in a folder, ensuring the necessary configurations and personnel controls are applied automatically and continuously maintained, which is a more complete solution than the posture management in option B (which focuses only on configuration monitoring) or the singular organizational policy in option C.

For a client concerned about the control of their encryption keys and not wanting to store these keys within the same cloud service provider (CSP) as the data, the following solutions are suitable:

Customer-supplied encryption keys (A):

With customer-supplied encryption keys, clients manage their own encryption keys outside of Google Cloud and supply them to encrypt and decrypt data. This ensures that the keys are not stored in Google Cloud, providing full control over the key management process.

Cloud External Key Manager (D):

Cloud External Key Manager (EKM) allows clients to integrate an external key management system (KMS) with Google Cloud services. This setup enables the client to keep their encryption keys outside Google Cloud while still allowing the data to be encrypted and decrypted within Google Cloud services. This method offers an additional layer of security and control over the encryption keys.

These options provide robust solutions for clients requiring external key management and enhanced control over their encryption processes.

References

Customer-Supplied Encryption Keys

Cloud External Key Manager

The most efficient and recommended way to achieve real-time/near real-time ingestion of logs (including Google Workspace Audit Logs, which feed into Cloud Logging) to a third-party system is by using a Cloud Logging sink to a Pub/Sub topic.

Cloud Logging Sink: Creates a stream of logs filtered by type (e.g., authentication events).

Pub/Sub Topic: A messaging service that acts as a reliable, real-time message queue.

SIEM Subscription: The SIEM system can subscribe directly to the Pub/Sub topic, receiving log events as soon as they are published, meeting the real-time requirement.

Extracts:

"Cloud Logging sinks let you route logs to destinations like Cloud Storage, BigQuery, or Pub/Sub... Routing logs to Pub/Sub enables real-time streaming of log data for consumption by external services or applications, such as a third-party SIEM." (Source 7.1)

Option B (polling) and Option D (Cloud Storage bucket) are batch-oriented methods, which do not meet the real-time/near real-time requirement.

The Organization Policy Service provides a specific constraint called constraints/gcp.restrictServiceUsage. This is the most direct and efficient way to "Allow" or "Deny" specific Google Cloud APIs (services) at any node in the hierarchy (Org, Folder, or Project).

According to Google Cloud Documentation (Restricting Resource Service Usage):

"The Restrict Resource Service Usage constraint allows enterprise administrators to control which Google Cloud services can be used within their Google Cloud resource hierarchy. This constraint can be enforced on an Organization, Folder, or Project. When applied at the folder level, it restricts service usage for all descendant projects within that folder."

Why Option C is the most efficient:

Targeted: By applying it directly to the folder, you don't need to manage complex "exceptions" at the Org level (as in Option B).

Simple: It is a single policy rule that defines an "Allowlist" of services.

IAM vs. Org Policy: IAM (Option A) controls who can do something, but Org Policy controls what can be done. Even if a user is an Editor, the Org Policy will block them from enabling a restricted API.

VPC-SC (Option D): VPC Service Controls is much more complex and is used for data exfiltration prevention, not for simply restricting which APIs can be enabled/used in a project.

nodeSelector is the simplest recommended form of node selection constraint. You can add the nodeSelector field to your Pod specification and specify the node labels you want the target node to have. Kubernetes only schedules the Pod onto nodes that have each of the labels you specify. => Tolerations are applied to pods. Tolerations allow the scheduler to schedule pods with matching taints. Tolerations allow scheduling but don 't guarantee scheduling: the scheduler also evaluates other parameters as part of its function. =>

To manage user accounts and ensure they comply with corporate policies, using Google Cloud Directory Sync (GCDS) allows synchronization between your local identity system and Cloud Identity. The Transfer Tool for Unmanaged Users (TTUU) helps identify and manage conflicting accounts by allowing users to transfer their personal accounts to managed accounts.

Steps:

Synchronize Identities: Use GCDS to sync users from your local identity management system to Cloud Identity, ensuring that all corporate user accounts are managed.

Identify Conflicting Accounts: Use TTUU to find users who have personal Google accounts using corporate email addresses.

Manage Conflicting Accounts: Request users to transfer their personal accounts to managed accounts using TTUU, ensuring all accounts are under corporate control.

Google Cloud Armor provides protection against DDoS attacks and allows you to define security policies to control access to your application. It enables you to block traffic from specific IP addresses or ranges, making it suitable for denying traffic from a list of malicious IP addresses while protecting your application from being directly exposed to the internet.

Steps:

Set Up Cloud Armor: Enable Cloud Armor in your Google Cloud Console.

Create Security Policies: Define security policies that specify the rules for allowing or denying traffic based on IP addresses.

Attach Policies to Backend Services: Apply these security policies to the backend services of your web application.

Use Google Shielded VM including secure boot Virtual Trusted Platform Module (vTPM) and integrity monitoring: Shielded VMs provide verifiable integrity of the VM by ensuring that it was not tampered with or compromised at the boot level. They use features like Secure Boot, vTPM, and integrity monitoring to detect and prevent malicious changes to the VM's operating system and firmware.

Activate Confidential Computing: Confidential Computing provides a secure environment for processing sensitive data. It uses hardware-based enclaves to protect data in use by ensuring it cannot be accessed by the underlying host or any other unauthorized entity. By leveraging Intel SGX or AMD SEV, it ensures that data remains encrypted even when it is being processed.

Enforce these actions by using organization policies: Organization policies can enforce the use of Shielded VMs and Confidential Computing across your organization. This ensures that all VMs comply with these security measures without requiring manual configuration for each VM.

References

Shielded VMs documentation

Confidential Computing documentation

Organization Policies documentation

Objective: Identify the layers of the stack the customer shares responsibility for in a shared security responsibility model for IaaS.

Solution: Understand the shared responsibility model.

Network Security: Customers are responsible for configuring network security, such as setting up firewalls, managing VPCs, and ensuring secure network traffic.

Access Policies: Customers are responsible for managing access policies, including IAM roles and permissions, to ensure only authorized users can access resources.

In IaaS, the cloud provider is typically responsible for the underlying infrastructure, while the customer is responsible for securing their applications and data on the cloud.

o ensure that users can only access the data in a BigQuery table during working hours, you can assign the BigQuery Data Viewer role with an IAM condition that specifies the allowed access times. This method leverages IAM Conditions, which allow you to define and enforce time-based access policies. Here's how to do it:

Identify the BigQuery Table: Determine which BigQuery table(s) require restricted access.

Create an IAM Policy with Conditions: Define an IAM policy that includes a condition for time-based access. You can do this using the Google Cloud Console, gcloud command-line tool, or directly editing the IAM policy JSON.

Specify Working Hours: In the IAM condition, specify the time frame during which access is allowed. For example, you can set access to be allowed from 9 AM to 5 PM on weekdays.

Assign the Role with Conditions: Apply the policy to the users or groups who need access. Ensure that the condition is correctly attached to the BigQuery Data Viewer role.

Example using gcloud:

gcloud projects add-iam-policy-binding [PROJECT_ID] \

--member=user:[USER_EMAIL] \

--role=roles/bigquery.dataViewer \

--condition=expression="(request.time.getFullYear() == 2024) && (request.time.getDayOfWeek() in [1, 2, 3, 4, 5]) && (request.time.getHours() >= 9) && (request.time.getHours() < 17)",title="Working hours condition",description="Access limited to working hours"

References

Google Cloud IAM Conditions

Google Cloud BigQuery IAM Roles

The problem is that the on-premises developers cannot resolve the Artifact Registry hostname, and they have no route to the internet. This is a classic DNS resolution problem in a hybrid network using private API access.

Artifact Registry is a Google-managed service, and its hostname (e.g., us-west1-docker.pkg.dev) resolves to a Google API domain. To access Google services privately from an on-premises network without an internet route, the traffic must be directed to Private Google Access IP ranges.

Issue: The on-premises DNS cannot resolve the Google service domain to the required private IP range.

Solution: The on-premises DNS needs a record (or a forwarding rule) to resolve the Google service domain to the dedicated IP ranges used for Private Google Access, specifically restricted.googleapis.com or private.googleapis.com (which provide the IP addresses for private access).

Extracts (Conceptual Basis):

"To direct traffic privately, you must ensure that your on-premises network's DNS is configured to resolve Google API and service domain names to the IP address range for Private Google Access." (Source 1.1)

"The IP addresses for private.googleapis.com are used for Private Google Access. To enable on-premises hosts to access Google APIs and services using this method, you must configure on-premises DNS to resolve requests for Google API domain names to the IP address range for private.googleapis.com." (Source 1.2)

Option B is incorrect because Private Google Access (PGA) is enabled on the VPC subnet, allowing VMs within the VPC to access Google APIs. However, the problem is with the on-premises developers; the on-premises DNS must be configured to resolve the hostname correctly.

The requirement to ensure the master encryption key material never leaves the on-premises hardware (HSM) and retaining the unilateral ability to revoke access are the defining features of Cloud External Key Manager (Cloud EKM).

Key Residency: Cloud EKM allows you to use encryption keys stored and managed in a supported external key management system, such as an on-premises HSM, for encrypting data in Google Cloud services like BigQuery and Cloud Storage. This ensures the key material remains in your accredited hardware.

Unilateral Control: Since Google Cloud must request the key from the external system for every encryption/decryption operation, revoking access (by disabling the key or revoking Google's access) in the external system immediately renders the data in Google Cloud inaccessible, granting the customer unilateral control.

Extracts:

"Cloud External Key Manager (Cloud EKM) is a cloud service that lets you encrypt data in Google Cloud with keys you manage outside of Google Cloud." (Source 6.1)

"The key material is stored on an external system, such as a Cloud EKM partner or an on-premises HSM, and never leaves that system." (Source 6.1)

"The customer can unilaterally revoke access to the key at the EKM system, making the encrypted data in Google Cloud inaccessible, which is a key requirement for highly regulated industries." (Source 6.2)

To remove personally identifiable information (PII) from files older than 12 months and archive the anonymized files for retention purposes, you can use Google Cloud Data Loss Prevention (DLP).

Create a Cloud DLP Inspection Job:

Go to the Cloud DLP section in the Google Cloud Console.

Create an inspection job that scans files in your Cloud Storage bucket for PII.

Configure the job to only target files that are older than 12 months.

Configure De-identification:

In the inspection job settings, configure de-identification actions to remove or obfuscate PII in the files.

Specify the transformation techniques appropriate for your data, such as masking or tokenization.

Archive Anonymized Files:

Set up the job to move the de-identified files to another Cloud Storage bucket designated for archival.

Ensure this bucket has the appropriate retention policies and access controls in place.

Delete Original Files:

After de-identification and archiving, configure the job to delete the original files from the source bucket.

This approach ensures that PII is effectively removed from old files and that the anonymized data is securely archived, maintaining compliance with data retention and privacy policies.

Cloud Data Loss Prevention Documentation

Setting Up DLP Jobs

Cloud Storage Documentation

Understanding Unmanaged Users:

Unmanaged users are those who have created Google Cloud accounts using their company email addresses outside of the organization's management (e.g., through GCDS).

Challenge:

The goal is to bring these unmanaged accounts under your company's control without disrupting their existing accounts and access.

Using the Transfer Tool:

Google provides a transfer tool specifically designed to migrate unmanaged users to a managed state.

This tool allows administrators to invite unmanaged users to join the organization's Google Cloud Identity or Google Workspace account.

Steps to Use the Transfer Tool:

Step 1: Access the transfer tool from the Google Admin console.

Step 2: Identify the unmanaged users using their email addresses.

Step 3: Send invitations to these users to transfer their accounts.

Step 4: Users accept the invitations, allowing their accounts to be managed under the organization's domain.

Benefits:

This method ensures a smooth transition for users without losing access to their existing data and services.

It aligns with best practices for managing user accounts in a corporate environment.

"To support common use cases like setting a Time to Live (TTL) for objects, retaining noncurrent versions of objects, or "downgrading" storage classes of objects to help manage costs, Cloud Storage offers the Object Lifecycle Management feature. This page describes the feature as well as the options available when using it. To learn how to enable Object Lifecycle Management, and for examples of lifecycle policies, see Managing Lifecycles."

"Cloud Identity has a catalog of automated provisioning connectors, which act as a bridge between Cloud Identity and third-party cloud apps."

To securely access Google Cloud APIs from CI/CD pipelines running on Google Kubernetes Engine (GKE), follow these steps:

Create Service Accounts:

Create individual service accounts for each CI/CD pipeline. This ensures isolation and minimal permissions per pipeline.

Use a naming convention that includes an identifier for each pipeline, such as pipeline-a-sa, pipeline-b-sa, etc.

Configure Kubernetes Service Accounts:

Create Kubernetes service accounts for each CI/CD pipeline pod.

Map Kubernetes Service Accounts to Google Service Accounts:

Use Workload Identity to associate Kubernetes service accounts with the corresponding Google service accounts. This allows the pods to authenticate to Google Cloud APIs securely.

Example command to bind the Kubernetes service account to the Google service account:

gcloud iam service-accounts add-iam-policy-binding \ --role roles/iam.workloadIdentityUser \ --member "serviceAccount:.svc.id.goog[/]" \ @.iam.gserviceaccount.com

Deploy CI/CD Pipelines:

Ensure each pipeline runs in dedicated pods that use the specific Kubernetes service accounts configured earlier.

This setup ensures that each pipeline has the necessary permissions to interact with Google Cloud APIs securely, adhering to the principle of least privilege.

References

Using Workload Identity

Managing Service Accounts

To implement a Zero Trust architecture that evaluates device posture (OS version, encryption, etc.) for access to data in Cloud Storage, you must use Context-Aware Access (CAA). CAA relies on Access Context Manager to define "Access Levels" and VPC Service Controls (VPC-SC) to enforce those levels for managed services like Cloud Storage.

According to Google Cloud Documentation (Context-Aware Access with VPC Service Controls):

"VPC Service Controls can use Access Context Manager access levels to restrict access based on a variety of attributes, including user identity, device security status (device policy), and IP address.2 By applying an access level to a service perimeter, you can ensure that only requests meeting those specific contextual requirements can access the resources within that perimeter."

Implementation Steps:

Access Context Manager: Create an access level that checks for device management status, minimum OS version, and other posture requirements (verified by the Chrome Enterprise/Endpoint Verification agent).

VPC Service Controls: Create a service perimeter around the project containing the Cloud Storage buckets.

Policy Binding: Associate the Access Level with the VPC-SC perimeter. Any request that doesn't meet the device policy (e.g., outdated OS) will be blocked at the API layer, even if the user has the correct IAM roles.

Use the TCP/UDP Network Load Balancer:

TCP/UDP Network Load Balancer maintains the client IP address by default when forwarding traffic to backends.

Configure a TCP/UDP Network Load Balancer with appropriate backend services and health checks.

Ensure that the load balancer is using the standard network tier to comply with the requirements.

To ensure compliance with strict regulatory requirements for storing and processing sensitive patient data in the cloud, the following measures should be implemented:​

Assured Workloads: Deploying an Assured Workloads environment in an approved region ensures that data residency requirements are met by restricting data storage and processing to specific geographic locations. Assured Workloads provide predefined controls and configurations tailored to meet regulatory compliance needs.​

Access Approval: Configuring Access Approval ensures that certain administrative actions on patient data require explicit approval from designated compliance officers. This adds a layer of control over sensitive operations, aligning with the need for explicit approvals.​

Cloud Audit Logs and Access Transparency: Enabling Cloud Audit Logs provides a detailed record of actions taken on your data, supporting the requirement for auditability. Access Transparency logs offer visibility into Google's administrative access to your content, enhancing transparency and compliance.​

Therefore, Option C is the most appropriate choice, as it comprehensively addresses data residency, administrative control, and auditability requirements.​

To prepare for migrating Google Cloud projects to a new organization node, it's crucial to ensure that the projects' current configurations and dependencies are appropriately managed. The two necessary preparation steps are:

Identify inherited Identity and Access Management (IAM) roles on projects to be migrated (C):

Projects inherit IAM roles from their parent resources. Identifying these roles is essential to understand the permissions and access levels that users have on the projects. This will help in ensuring that after migration, the appropriate roles and permissions are applied correctly.

Remove the specific migration projects from any VPC Service Controls perimeters and bridges (E):

VPC Service Controls provide security boundaries around your Google Cloud resources to mitigate data exfiltration risks. Before migrating the projects, they need to be removed from any existing VPC Service Controls perimeters and bridges to prevent any disruption in access or network communication. After migration, the projects can be added back to the necessary perimeters.

References

Google Cloud IAM documentation

VPC Service Controls documentation

Unable to grant correct permissions to the destination: Even if the sink was successfully created with the correct service account permissions, this error message displays if the access control model for the Cloud Storage bucket was set to uniform access when the bucket was created. For existing Cloud Storage buckets, you can change the access control model for the first 90 days after bucket creation by using the Permissions tab. For new buckets, select the Fine-grained access control model during bucket creation. For details, see Creating Cloud Storage buckets.

This approach allows you to expose the web interface securely by using Identity-Aware Proxy (IAP), which provides authentication and authorization with Google credentials. The HTTP Load Balancer can distribute traffic to the VMs in the managed group, and the VPC firewall rule ensures that access is allowed from the IAP network range.

To ensure that application teams can only add users from within your organization to their groups, you need to configure the group settings in the Google Workspace Admin console. Here are the steps:

Access Google Workspace Admin Console:

Go to the Google Workspace Admin console.

Navigate to the Groups section.

Configure Group Settings:

Select the relevant groups used by the application teams.

Go to the group settings and set the group to only allow members from your domain.

This prevents external users from being added to these groups.

Apply and Save Changes:

Apply the changes to ensure that only users from within your organization can be added to these groups.

Verify Configuration:

Test the configuration by attempting to add an external user to the group and verifying that it is not allowed.

Benefits:

Security: Prevents unauthorized access by ensuring that only internal users can be added to groups.

Compliance: Helps in adhering to organizational policies regarding user access and management.

References

Google Workspace Admin Help: Groups

This approach allows you to leverage your existing on-premises PKI infrastructure while minimizing its impact and manual processes. By creating a subordinate CA in Google’s Certificate Authority Service, you can automate the process of issuing certificates for your HTTP load balancer frontends. This solution scales well as the number of load balancers increases.

When implementing new security perimeters or access levels, Google Cloud recommends using Dry Run Mode in VPC Service Controls.12 This allows you to see what would have been blocked without actually disrupting traffic.

According to Google Cloud Documentation (Dry Run Mode for Service Perimeters):

"Dry run mode allows you to test the impact of a service perimeter before enforcing it. You can associate an Access Level (which contains Context-Aware attributes like device status and location) with the dry run configuration. Any request that violates the perimeter or the access level will be logged in Cloud Audit Logs as a 'dry run violation,' but the request will still be allowed to proceed."13

Evaluation Process:

Define the Access Level in Access Context Manager (Managed Device + Location).

Configure the VPC-SC Perimeter to include the project.

Apply the Access Level to the Dry Run section of the perimeter.

Monitor the VPC Service Controls Violation Dashboard or Audit Logs for dry run errors to identify legitimate users who would be blocked under the new policy.

Packet Mirroring clones the traffic of specified instances in your Virtual Private Cloud (VPC) network and forwards it for examination. Packet Mirroring captures all traffic and packet data, including payloads and headers.

- First, you create or use an existing key in a supported external key management partner system. This key has a unique URI or key path.

- Next, you grant your Google Cloud project access to use the key, in the external key management partner system.

- In your Google Cloud project, you create a Cloud EKM key, using the URI or key path for the externally-managed key.

The requirements necessitate a private, cross-project service-to-service connection with explicit authorization—a capability perfectly addressed by Private Service Connect (PSC).

Internal Load Balancer: Ensures the service is isolated from the internet (Layer 7 Load Balancer for HTTP/S ML endpoint).

Private Service Connect (PSC): Allows a service (the model endpoint, exposed via the internal load balancer) in one VPC/project (producer) to be securely consumed by other VPCs/projects (consumers) using an internal IP address.

Defined List of Projects: PSC enables Explicit authorization, allowing the producer to define the allowed list of consumers that can establish a connection, directly meeting the granular restriction requirement.

Extracts:

"Private Service Connect provides... Explicit authorization. Private Service Connect provides an authorization model that gives consumers and producers granular control." (Source 2.4)

"Private Service Connect backends let Google Cloud load balancers send traffic through Private Service Connect to reach published services... Placing a load balancer in front of a managed service provides the consumer with more visibility and control..." (Source 2.4)

"Publish services by using Private Service Connect... Select the internal load balancer that hosts the service that you want to publish." (Source 2.3)

To access a user's Google Drive on their behalf without relying on the user's credentials and following Google-recommended practices, you should use a service account with domain-wide delegation.

Create a Service Account:

Go to the Cloud Console, navigate to IAM & Admin > Service Accounts.

Click "Create Service Account" and provide necessary details.

Grant Domain-Wide Delegation:

Edit the service account to enable "G Suite Domain-wide Delegation".

Download the JSON key file.

Configure API Access in G Suite:

Go to the Google Admin Console.

Navigate to Security > API Controls > Domain-wide Delegation.

Add a new API client and use the client ID from the service account.

Authorize the necessary API scopes (e.g.,

Implement in Application:

Use the Google API Client Library for the desired language.

Load the service account credentials and perform user impersonation to access Google Drive.

Domain-wide Delegation of Authority

Using OAuth 2.0 for Server to Server Applications

To provide on-premises hosts with access to Google APIs without using public IP addresses or the public internet, Google Cloud provides Private Google Access for on-premises hosts. This feature allows traffic to stay within the Google network via Cloud Interconnect or Cloud VPN.

According to the official Google Cloud Documentation (Configuring Private Google Access for on-premises hosts):

"Private Google Access for on-premises hosts provides a way for on-premises systems to connect to Google APIs and services by routing traffic through a Cloud VPN tunnel or Cloud Interconnect attachment (VLAN). On-premises hosts don't need public IP addresses; instead, they use internal IP addresses."

Key Implementation Steps:

Network Connectivity: Ensure your on-premises network is connected to your VPC via Cloud Interconnect or VPN.

DNS Configuration: You must configure your on-premises DNS to map API requests (like storage.googleapis.com) to special IP ranges. There are two primary options:

private.googleapis.com: Resolves to 199.36.153.8/30. This range supports most Google APIs but only those that are VPC-Service Control compatible.

restricted.googleapis.com: Resolves to 199.36.153.4/30. This is required specifically when using VPC Service Controls (VPC-SC) to ensure data cannot be exfiltrated to services outside the perimeter.

Routing: You must configure custom static routes in your VPC or use BGP to advertise the 199.36.153.8/30 (or 199.36.153.4/30) range back to your on-premises router.

Why other options are incorrect:

A is incorrect: Shared VPC is used to share a network across multiple Google Cloud projects, not to extend a VPC directly to on-premises hardware.

C is incorrect: While the IP range 199.36.153.8/30 is correct for private.googleapis.com, Cloud NAT is used for outbound internet access from VPC instances without external IPs; it does not facilitate private on-premises-to-API connectivity.

D is incorrect: VPC Peering connects two VPCs within Google Cloud. You cannot "peer" an on-premises data center directly via VPC Peering; you must use Interconnect or VPN.

For scenarios involving multi-party collaboration or highly sensitive data where even the "Workload Operator" should not see the data, Confidential Space is the specific Google Cloud solution. It builds on Confidential Computing but adds a software framework for "Trustless" data processing.

According to Google Cloud Documentation (Confidential Space Overview):

"Confidential Space provides a secure environment for multiple parties to share sensitive data without any party (including the cloud provider or the project administrator) being able to see the data or the code being executed. It uses attestations to verify the integrity of the workload and Workload Identity Federation to release encryption keys or access only to verified, authorized workloads."

Key components of the solution:

Separation of Duties: Confidential Space explicitly defines roles for the Data Collaborator (owns data), Workload Author (writes code), and Workload Operator (runs infrastructure). The operator can manage the VM but cannot access the memory or the data.

Attestation: The system uses hardware-rooted attestation to ensure that the code running in the environment is exactly what was approved.

Output Protection: The processed results can be written to a bucket where only the authorized "Data Scientist" (Data Collaborator role) can retrieve them.

Why other options are incorrect:

A, C, and D are incorrect: While they use Confidential VMs (which encrypt data in RAM), they do not inherently provide the attestation-based trust framework or the rigorous separation of duties required to prevent a VM administrator (operator) from potentially accessing the data via standard VM management tools or during the ingestion phase. Confidential Space is the only one that mandates a signed "attestation" before granting access to data.

Objective: Ensure only front-end Compute Engine instances have public IPs, while others do not.

Solution: Use an organization policy to enforce this requirement.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Organization Policies page.

Step 3: Create a new policy with the constraint constraints/compute.requireOsLogin (or similar constraint to manage public IPs).

Step 4: Define the conditions to allow public IPs only for the front-end instances.

Step 5: Apply the policy to the organization or specific projects as necessary.

By setting up an organization policy with specific conditions, you can control which instances are allowed to have public IPs based on their role or other attributes.

Workload Identity is the Google-recommended method for GKE workloads to access Google Cloud services. It eliminates the need for manual management of service account keys (JSON files), which are a major security risk if leaked.1

According to Google Cloud Documentation (Workload Identity Federation for GKE):

"Workload Identity is the recommended way for your workloads running on GKE to access Google Cloud services in a secure and manageable way. It allows a Kubernetes service account in your GKE cluster to act as a Google IAM service account.2 When you use Workload Identity, you don't need to manage service account keys or store them as Kubernetes secrets."

Why other options are incorrect:

A is incorrect: Service account keys are long-lived and difficult to rotate. Using them increases the risk of credential theft.

C & D are incorrect: Attaching a service account to a Node gives every pod running on that node the same permissions. This violates the Principle of Least Privilege because different workloads on the same node should have different permissions.

To address inconsistencies in your project's Identity and Access Management (IAM) configuration and gain comprehensive visibility into IAM policy changes, user activity, service account behavior, and access to sensitive projects, leveraging Google Cloud's auditing capabilities is essential.​

Option A: While Cloud Monitoring's metrics explorer can track certain metrics, it is not designed to provide detailed logs of IAM policy changes or user activities.​

Option B: Cloud Audit Logs offer detailed records of administrative activities, including IAM policy changes and authentications. By creating log export sinks, you can forward these logs to a Security Information and Event Management (SIEM) solution, enabling correlation with other event sources and comprehensive analysis. This approach provides the necessary visibility into IAM configurations and user activities.​

Option C: Triggering Cloud Functions based on IAM policy changes and analyzing them with a policy simulator is a proactive approach. However, it may not provide the depth of historical data and comprehensive analysis capabilities that a SIEM solution offers.​

Option D: Deploying the OS Config Management agent focuses on VM configuration and patch management, which does not directly address IAM policy monitoring or user activity tracking.​

Therefore, Option B is the most effective solution to gain detailed visibility into IAM-related activities and address the identified inconsistencies.​

The problem states that Google Cloud applications need to access external web services and requires the ability to monitor, control, and log this access.

Monitoring, Controlling, and Logging external web access: This specifically points to a proxy solution, which can intercept, inspect, and log HTTP/S traffic.

Secure Web Proxy (SWP): Google Cloud's Secure Web Proxy is designed for exactly this use case. It acts as an explicit forward proxy for HTTP(S) traffic, allowing organizations to implement granular access controls, inspect traffic for security threats, and log all outbound web requests from their Google Cloud environment.Extract Reference: "Secure Web Proxy is a managed service that lets you deploy and manage an explicit forward proxy to protect your organization's internal resources from web-based threats and to control access to external web applications." and "With Secure Web Proxy, you can: Enforce granular access policies based on different attributes, Log all HTTP(S) requests that are handled by the proxy, and Monitor web traffic for threats." (Google Cloud documentation:

Let's evaluate the other options:

A. Configure VPC firewall rules to allow the services to access the IP addresses of required external web services: VPC firewall rules operate at Layer 4 (TCP/UDP) and Layer 3 (IP). While they can allow or deny traffic to specific IP addresses and ports, they cannot monitor, control, or log HTTP/S requests at the application layer. They don't provide granular control over which web services are accessed or inspect the content of the requests.

C. Configure Google Cloud Armor to monitor and protect your applications by checking incoming traffic patterns for attack patterns: Google Cloud Armor is primarily a Distributed Denial of Service (DDoS) protection and Web Application Firewall (WAF) service. It focuses on protecting applications from incoming threats (ingress traffic), not controlling and logging outgoing access to external web services.

D. Set up a Cloud NAT instance to allow egress traffic from your VPC: Cloud NAT allows instances without external IP addresses to connect to the internet. While it enables egress, it does not provide monitoring, control, or logging capabilities for specific web services at the application layer. It's a network address translation service, not an application-layer proxy.

Therefore, setting up a Secure Web Proxy is the most appropriate solution to meet the requirements of monitoring, controlling, and logging access to external web services from Google Cloud applications.

To enable developer teams to deploy new applications without the extensive overhead of network and security reviews, it’s recommended to mandate the use of infrastructure as code (IaC) and enforce policies through static analysis in CI/CD pipelines. This approach ensures that security and compliance policies are checked automatically during the development process.

Step-by-Step:

Adopt IaC: Use tools like Terraform or Google Cloud Deployment Manager to manage infrastructure as code.

CI/CD Pipeline Integration: Integrate static analysis tools such as TFLint or Checkov in the CI/CD pipeline to enforce security policies.

Policy Definition: Define security policies and best practices that need to be adhered to in the code.

Automated Checks: Configure automated checks in the CI/CD pipeline to review code against these policies before deployment.

Monitor and Audit: Continuously monitor and audit deployed applications to ensure ongoing compliance.

Infrastructure as Code on Google Cloud

Static Analysis for Terraform

Checkov for IaC

Compute Engine doesn't automatically update the OS or the software on your deployed instances. You will need to patch or update your deployed Compute Engine instances when necessary. However, in the cloud it is not recommended that you patch or update individual running instances. Instead it is best to patch the image that was used to launch the instance and then replace each affected instance with a new copy.

The problem requires a publicly accessible Cloud Run service with HTTPS, TLS termination at the edge, threat mitigation, and geo-based access restrictions.

External HTTP(S) Load Balancer: This is the standard Google Cloud component for exposing public-facing web applications, providing a single global IP address, global load balancing, and crucially, TLS termination at the edge of Google's network.

Serverless Network Endpoint Group (NEG): A serverless NEG connects an HTTP(S) Load Balancer to a Cloud Run service (or other serverless backends like Cloud Functions or App Engine), allowing the load balancer to route traffic to the serverless application.Extract Reference: "You can use an external HTTP(S) Load Balancer with a serverless network endpoint group (NEG) to integrate Cloud Run services with advanced load balancing features, such as Cloud CDN, Google Cloud Armor, and Cloud Identity-Aware Proxy." (Google Cloud Documentation: "Connect a Cloud Run service to an HTTP(S) Load Balancer | Cloud Run Documentation" -

Google-Managed Certificate for TLS Termination: Using Google-managed SSL certificates simplifies the management of HTTPS, as Google handles the provisioning, renewal, and deployment of certificates. The external HTTP(S) Load Balancer terminates TLS using these certificates.Extract Reference: "Google-managed SSL certificates let you use Google Cloud's globally distributed infrastructure to automatically provision and renew your certificates." (Google Cloud Documentation: "Google-managed SSL certificates overview | Load Balancing" -

Cloud Armor for Threat Mitigation and Geo-Based Access Control: Cloud Armor is a Web Application Firewall (WAF) service that integrates with HTTP(S) Load Balancers. It provides DDoS protection, allows custom rules for threat mitigation (e.g., SQL injection, XSS), and supports geo-based access control rules to allow or deny traffic based on the source's geographic region.Extract Reference: "Google Cloud Armor helps protect your Google Cloud deployments from various threats, including Distributed Denial of Service (DDoS) attacks and application attacks such as cross-site scripting (XSS) and SQL injection (SQLi)." and "Google Cloud Armor supports geo-based access control, allowing you to filter requests based on geographic region." (Google Cloud Documentation: "Google Cloud Armor overview" -

Let's evaluate the other options:

A. IAP for authentication and IP-based access control + custom SSL certs: IAP is primarily an authentication layer for users/identities, not a WAF for threat mitigation or geo-blocking for a publicly accessible service before any authentication takes place. While it can apply IP-based access, it's typically for post-authentication controls.

B. Assign custom domain, enable HTTPS, allUsers IAM, firewall rules & VPC SC: While Cloud Run supports custom domains and HTTPS, and allUsers makes it public, direct Cloud Run services do not leverage traditional VPC firewall rules for public ingress. VPC Service Controls are for API access and data exfiltration, not for WAF or geo-blocking of public web traffic.

D. Cloud DNS public zone, static IP, VPC firewall rules, threat signatures: Cloud Run services are managed and do not typically expose a static IP address that can be directly associated with VPC firewall rules for public traffic. VPC firewall rules apply to VMs within a VPC, not to the managed global infrastructure of Cloud Run's public endpoints.

Therefore, deploying an external HTTP(S) Load Balancer with a serverless NEG and integrating it with Google-managed certificates and Cloud Armor is the most comprehensive and Google-recommended solution for meeting all the specified security requirements for a publicly accessible Cloud Run application.

To ensure least-privilege access and provide necessary permissions to the DevOps team only during a deployment issue, follow these steps:

Create a Service Account:

In your Google Cloud project, create a new service account specifically for the DevOps team.

Assign Limited Permissions:

Grant the service account permissions with only the necessary list/view roles. For instance, you can create a custom IAM role with compute.instances.list and compute.instances.get permissions.

Grant Service Account User Role:

Assign the Service Account User role to the DevOps team members for the created service account. This allows them to act as the service account and use its permissions.

Access Control During Incidents:

During a deployment issue, the DevOps team can temporarily use the service account to access the resources. This ensures they have the least-privilege access required to investigate and resolve the issue.

Automation and Monitoring:

Implement automation to enable and disable the service account access as needed and monitor the usage to ensure compliance with the least-privilege principle.

Benefits:

Security: Limits access to only what is necessary, reducing the risk of unauthorized changes.

Flexibility: Provides necessary access during incidents without granting permanent elevated permissions.

References

Creating and Managing Service Accounts

Service Account User Role

In the Google Cloud resource hierarchy, Organization Policy is a powerful tool for governance, but its effectiveness depends on strict control over who can modify it. If a policy set at the folder level was "overwritten," it means a principal with the Organization Policy Administrator role (roles/orgpolicy.policyAdmin) at the project level (or folder level) changed the inheritance or defined a more permissive policy.1

According to Google Cloud Documentation (Organization Policy Service - IAM Roles):

"To manage organization policies, a principal must have the Organization Policy Administrator role. This role should be granted only at the Organization level to a limited set of trusted security or compliance administrators to prevent project owners from overriding security guardrails."

Why Option A is the best fix:

By removing the role from everyone except the central security team at the Organization level, you ensure that no one else has the technical permission to "Manage Policy" or click "Override" at any child node (folder or project).

B is insufficient because if a user has the role at the organization level, they can still apply overrides at the folder or project level.

C and D (Security Postures) are detective controls. While the secure_ai_extended template helps monitor drift, it does not prevent the occurrence. The question asks for a solution that "prevents a repeat occurrence," which requires a preventative IAM change.

Objective: Implement an encryption at-rest strategy that balances key management complexity and control for sensitive and non-sensitive data, ensuring FIPS 140-2 L1 compliance.

Solution: Use Google default encryption for non-sensitive data and Cloud Key Management Service (KMS) for sensitive data.

Steps:

Step 1: Store non-sensitive data using Google Cloud’s default encryption, which automatically encrypts data at rest without additional configuration.

Step 2: For sensitive data, use Cloud KMS to create and manage encryption keys.

Step 3: Configure key rotation policies for the keys managed by Cloud KMS to meet compliance requirements.

Step 4: Ensure that all data encryption keys used by Cloud KMS comply with FIPS 140-2 Level 1 standards.

By using Google default encryption for non-sensitive data and Cloud KMS for sensitive data, you can manage encryption efficiently while maintaining control over key residency and rotation for sensitive data.

The problem focuses on securing "super administrator accounts for the organization" when Cloud Identity is synced with Microsoft Entra ID and uses Entra ID for SSO. The key requirements are the principle of least privilege and strong authentication.

Principle of Least Privilege & Dedicated Accounts: Google's best practices strongly recommend creating dedicated, non-federated accounts for super administrators that are distinct from regular user accounts. These accounts should only be used for super administrator tasks and not for daily activities. This segregation ensures that the highest privilege accounts are isolated and adhere to the principle of least privilege by not having combined responsibilities.

Extract Reference: "Designate Organization Administrators... We recommend keeping your super admin account separate from your Organization Administrator group." and "Give super admins a separate account that requires a separate login. For example, user alice@example.com could have a super admin account alice-admin@example.com." and "Use the super admin account only when needed. Delegate administrator tasks to user accounts with limited admin roles. Use the least privilege approach..." (Google Cloud Documentation: "Super administrator account best practices | Resource Manager Documentation" -

Strong Authentication (Google 2-Step Verification): Even when using a third-party identity provider like Microsoft Entra ID for most users, Google recommends enforcing Google's own 2-Step Verification for the critical super administrator accounts. This provides a "break-glass" mechanism that is independent of the external IdP. If the Entra ID integration were to fail or become compromised, the Google-managed super administrator accounts, protected by Google's own 2SV, would still be accessible for emergency recovery.

Extract Reference: "Even when using the legacy SSO profile, super admins can't sign in with SSO in these cases: Admin console. When super administrators try to sign in to an SSO-enabled domain via admin.google.com, they must enter their full Google administrator account email address and associated Google password (not their SSO username and password), and click Sign in to directly access the Admin console. Google doesn't redirect them to the SSO sign-in page." (Google Cloud Identity Help: "Super administrator SSO" - - This highlights that super admin accounts can bypass SSO for direct Admin console access, making Google 's 2SV crucial.

Extract Reference: "It's especially important for super admins to use 2SV because their accounts control access to all business and employee data in the organization. Protect your business with 2-Step Verification. Use security keys for 2-Step Verification." (Cloud Identity Help: "Security best practices for administrator accounts" -

Options C and D are incorrect because combining "organization administrator" (IAM role for GCP resources) and "super administrator" (Google Workspace/Cloud Identity domain-level control) privileges violates the principle of least privilege. Option A is less secure than B because relying solely on Entra ID's 2SV for super administrators means a compromise of Entra ID or an outage would leave the Google Cloud organization vulnerable without an independent break-glass mechanism.

Layer 7 attacks like XSS and SQL injection are application-level threats that require a Web Application Firewall (WAF) for protection. Google Cloud Armor provides this functionality, integrated with the load balancer.

Cloud Armor: Google Cloud's distributed denial-of-service (DDoS) and WAF service.

WAF Rules: Cloud Armor offers pre-configured OWASP Top 10 rules, which directly defend against XSS, SQL injection, and other common application vulnerabilities.

Deployment: Cloud Armor security policies are applied to a backend service that is behind an external HTTP(S) Load Balancer.

Extracts:

"Cloud Armor WAF capabilities help protect web applications from the OWASP Top 10 vulnerabilities... This includes rulesets specifically designed to detect and mitigate SQL injection (SQLi) and cross-site scripting (XSS) attacks." (Source 4.1)

"Cloud Armor security policies are implemented at the edge of the Google Cloud network, applied to the backend services of an external HTTP(S) Load Balancer." (Source 4.2)

Option A is close but incomplete; WAF rules are implemented via a security policy (Option D). Option B relies on Adaptive Protection, which is primarily for volumetric DDoS and advanced attacks, but the direct protection for known XSS/SQLi signatures comes from explicit WAF rules.

To ensure that no personally identifiable information (PII) is published in your yearly website usage analytics reports while preserving data integrity, the Cloud Data Loss Prevention (Cloud DLP) API can be utilized to identify and transform PII within your datasets.​

Option A: Encrypting PII does not remove it from the reports; it merely obscures it, which may not be sufficient for compliance or privacy requirements.​

Option B: Discovering and transforming PII ensures that sensitive information is either masked, tokenized, or otherwise obfuscated, effectively removing PII from the reports while maintaining the overall structure and utility of the data.​

Option C: Detecting and deleting PII could lead to loss of valuable data and may disrupt the integrity of the reports.​

Option D: Quarantining PII data implies isolating it, which doesn't address the need to publish reports without PII.​

Therefore, Option B is the most appropriate approach, as it leverages the Cloud DLP API to identify and transform PII, ensuring that the published reports are free from sensitive information while preserving data integrity.​

Provision a Cloud NAT Instance:

Cloud NAT (Network Address Translation) allows instances without external IP addresses to access the internet securely.

In the Google Cloud Console, navigate to the VPC Network section and select Cloud NAT.

Create a new Cloud NAT configuration, specifying the VPC and region where your Compute Engine VMs are deployed.

Configure Cloud NAT:

Ensure that the Cloud NAT instance is configured to provide outbound internet connectivity for the VMs in your specified subnet.

This setup allows the VMs to access the internet for package updates and external installations without requiring public IP addresses.

Enable Private Google Access:

Private Google Access allows VMs in a subnet to reach Google APIs and services using internal IP addresses.

In the Google Cloud Console, navigate to the VPC Network section and select Subnets.

Edit the subnet used by your Compute Engine VMs and enable Private Google Access.

Update DevOps Scripts:

Ensure that your DevOps scripts are updated to work with the new network configuration.

Test the build process to confirm that the VMs can access necessary resources and complete the build pipeline successfully.

For managing and rotating encryption keys in a Compute Engine-based cluster using Managed Instance Groups (MIGs), Customer-Managed Encryption Keys (CMEK) with Cloud KMS is the appropriate solution.

Set Up Cloud KMS:

Go to the Cloud Console and navigate to Security > Cryptographic Keys.

Create a keyring and a key.

Create and Use CMEK:

While creating or updating a Compute Engine instance, specify the CMEK key.

Example command:

gcloud compute instances create example-instance \ --image-family=debian-9 \ --image-project=debian-cloud \ --boot-disk-kms-key=projects/[PROJECT_ID]/locations/global/keyRings/[KEY_RING]/cryptoKeys/[KEY]

Rotate Keys:

Rotate keys periodically using Cloud KMS by creating new key versions and updating the instances to use the new key versions.

Customer-Managed Encryption Keys (CMEK)

Using Customer-Managed Encryption Keys

Disable service account key creation You can use the iam.disableServiceAccountKeyCreation boolean constraint to disable the creation of new external service account keys. This allows you to control the use of unmanaged long-term credentials for service accounts. When this constraint is set, user-managed credentials cannot be created for service accounts in projects affected by the constraint.

To manage consumer user accounts created using the corporate domain name, you can use the transfer tool for unmanaged user accounts provided by Google Cloud Identity. Here’s how you can proceed:

Identify Unmanaged Accounts:

Use the Cloud Identity interface to identify consumer (unmanaged) accounts that exist with your corporate domain.

Initiate Transfer Process:

Use the transfer tool for unmanaged user accounts to initiate the transfer. This tool helps in converting unmanaged accounts (consumer accounts) into managed accounts.

User Notification:

Users with unmanaged accounts will receive an email notification prompting them to accept the transfer to the organization’s managed account system.

Accept Transfer:

Users need to follow the instructions in the email to accept the transfer. Once accepted, their accounts will be managed under your organization’s Cloud Identity setup.

Benefits:

Centralized Management: All user accounts under your corporate domain are managed centrally, ensuring compliance and security.

Enhanced Security: Managed accounts provide better control over security policies and access management.

References

Transfer tool for unmanaged users

Cloud Identity Documentation

Understanding Organization Policies:

Organization policies are rules that can be set at different levels of the resource hierarchy in GCP to enforce governance and compliance.

These policies can be set at the organization node, folders, and projects, and they are inherited down the hierarchy unless explicitly overridden.

Hierarchy and Policy Inheritance:

The provided resource hierarchy has an organization node (Example.com), folders (Folder 1 and Folder 2), and a project (Project 2) under Folder 2 with a specific VPC (VPC A).

Each node in the hierarchy can have its own policies, and these policies are inherited by child nodes unless overridden.

Analyzing the Policies in the Hierarchy:

Organization Node Policy:

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "allValues": "DENY" } }

This policy at the organization node denies all load balancer types.

Folder 2 Policy:

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "deniedValues": ["INTERNAL_TCP_UDP", "INTERNAL_HTTP_HTTPS"] } }

This policy at Folder 2 denies the creation of INTERNAL_TCP_UDP and INTERNAL_HTTP_HTTPS load balancers.

Project 2 Policy:

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{ "constraint": "constraints/compute.restrictLoadBalancerCreationForTypes", "listPolicy": { "deniedValues": ["EXTERNAL_TCP_PROXY", "EXTERNAL_SSL_PROXY"] } }

This policy at Project 2 denies the creation of EXTERNAL_TCP_PROXY and EXTERNAL_SSL_PROXY load balancers.

Policy Application to VPC A:

Since policies are inherited, VPC A (which is within Project 2 under Folder 2) will be affected by the policies of both Folder 2 and Project 2.

Combining the denied values from both Folder 2 and Project 2:

From Folder 2: INTERNAL_TCP_UDP, INTERNAL_HTTP_HTTPS

From Project 2: EXTERNAL_TCP_PROXY, EXTERNAL_SSL_PROXY

Conclusion:

VPC A will have the following load balancer types denied: INTERNAL_TCP_UDP, INTERNAL_HTTP_HTTPS, EXTERNAL_TCP_PROXY, EXTERNAL_SSL_PROXY.

When you use a customer-managed encryption key (CMEK) to secure a Cloud Storage bucket, the key and the bucket must be located in the same region. In this case, the key is in europe-west3 and the bucket is in europe-west1, which is why you’re unable to access the key.

To grant an IAM user access to HTTPS resources protected by Identity-Aware Proxy (IAP), you should assign the IAP-Secured Web App User role.

IAP-Secured Web App User (C):

This role grants the necessary permissions for a user to access web applications secured by IAP. It includes permissions to access the IAP-secured resources, ensuring that users can authenticate and gain the appropriate access based on the policies defined in IAP.

Assigning this role ensures that users have the right level of access to protected web resources, aligned with the security controls enforced by IAP.

References

Identity-Aware Proxy Documentation

IAP Roles and Permissions

Packet Mirroring clones the traffic of specified instances in your Virtual Private Cloud (VPC) network and forwards it for examination. Packet Mirroring captures all traffic and packet data, including payloads and headers.

When creating a secure container image, it is essential to follow best practices to minimize vulnerabilities and ensure the container operates as intended. Here are the two key practices:

Package a Single App as a Container: By packaging only a single application within a container, you reduce complexity and potential attack surfaces. This practice aligns with the principle of single responsibility, ensuring each container has a clear and focused purpose.

Remove Any Unnecessary Tools: Any additional tools or software that are not required by the application should be removed from the container image. This minimizes the number of potential vulnerabilities and reduces the attack surface. A minimal container image also leads to smaller image sizes and faster deployment times.

These practices contribute to creating a more secure and efficient container image.

References

Container Security Best Practices

Securing Container Images

Public access prevention protects Cloud Storage buckets and objects from being accidentally exposed to the public. If your bucket is contained within an organization, you can enforce public access prevention by using the organization policy constraint storage.publicAccessPrevention at the project, folder, or organization level.

To grant read access to a third-party disk image stored in an external Google Cloud organization so it can be deployed into a VPC Service Controls perimeter, you need to update the service perimeter to allow egress traffic from your projects to the external project.

Update the Service Perimeter:

Go to the Google Cloud Console, navigate to Security > VPC Service Controls.

Select the appropriate service perimeter that includes your image repository project.

Configure Egress Policy:

Within the perimeter settings, configure the egressTo field to allow traffic to the external project.

Set the identityType to ANY_IDENTITY to permit any principal to access the external project for this specific egress rule.

Specify External Project and Service:

In the egressFrom field, include the external Google Cloud project number as an allowed resource.

Set the serviceName to compute.googleapis.com to specifically allow access to the Compute Engine service in the external project.

This configuration permits your internal projects to read the disk image from the external project while maintaining the security boundaries established by the service perimeter.

VPC Service Controls Documentation

Configuring Service Perimeters

Use the org policy constraint "Google Cloud Platform - Resource Location Restriction" on your Google Cloud organization node: This organizational policy constraint allows you to restrict the locations where your resources can be created. By setting this constraint to allow only Europe regions, you can ensure compliance with GDPR and other regional regulations.

Implementation: To implement this, you need to configure the organization policy with the constraint constraints/gcp.resourceLocations. You can specify allowed regions such as europe-west1 and europe-west4 to ensure resources are only created in these locations.

References

Resource Location Restriction documentation

GDPR compliance on Google Cloud

This PD and bucket data is encrypted using a Google-generated data encryption key (DEK) and key encryption key (KEK). The CMEK feature allows you to create, use, and revoke the key encryption key (KEK). Google still controls the data encryption key (DEK). For more information on Google data encryption keys, see Encryption at Rest.

The requirement is to protect data while in use (meaning data in memory or CPU registers, during processing). This is a concept addressed by Confidential Computing using Trusted Execution Environments (TEEs).

Extracts:

"Confidential VMs are an IaaS solution... Confidential VMs offer: Encryption for 'data in use', including the processor state and the virtual machine's memory." (Source 4.1)

"Confidential computing protects data during processing by isolating workloads inside hardware-based trusted execution environments (TEEs), ensuring even cloud operators cannot access them." (Source 4.3)

"Confidential VMs extend the standard virtual machine concept by adding hardware-enforced confidentiality controls... they ensure data remains encrypted not only at rest and in transit, but also while in use." (Source 4.4)

Options A (CMEK) and B (CSEK) protect data at rest (disk encryption). Option D (Shielded VM) protects integrity and prevents rootkit compromise but does not encrypt memory while the data is actively being processed. Only Confidential VM (or TEE) protects data in use.

To minimize the usage of service account keys and implement Workload Identity Federation (WIF) with your on-premises identity provider, you can use a workload identity pool integrated with your corporate Active Directory Federation Service (ADFS). This setup allows your on-premises Windows-based applications to authenticate to Google Cloud APIs without using long-lived service account keys.

Set Up a Workload Identity Pool:

In the Google Cloud Console, go to IAM & Admin > Workload Identity Federation.

Create a new workload identity pool.

Configure the pool to trust your corporate ADFS by specifying the federation provider details.

Create a Workload Identity Provider:

Within the created pool, set up a new provider for ADFS.

Configure the provider with the necessary details such as the issuer URL and credentials.

Configure Impersonation Rules:

Set up rules to allow principals in the workload identity pool to impersonate specific Google Cloud service accounts.

This is done by specifying the identity provider and the conditions under which the service accounts can be impersonated.

Update Applications:

Modify your on-premises applications to use the configured ADFS authentication to obtain tokens.

These tokens can then be exchanged for Google Cloud access tokens to interact with Google Cloud APIs securely.

By setting up the workload identity pool and configuring impersonation rules, you achieve secure authentication without needing to distribute and manage service account keys.

Workload Identity Federation Documentation

Federating On-Premises Identities to Workload Identity Federation

Enable Dry Run Mode: Start by enabling the dry run mode for your VPC Service Controls perimeter. This mode allows you to test changes without actually enforcing them, thus preventing any disruption to your current setup.

Add Access Level: Add your new access level to the dry run configuration. This way, you can monitor how the new access level would behave and interact with your existing setup without any real impact.

Vetting Process: Carefully vet the new access level by analyzing logs and monitoring the behavior in the dry run mode. Ensure that the new configuration meets your security and operational requirements.

Update Perimeter: Once you are confident that the new access level will not disrupt existing services and meets all requirements, update the actual perimeter configuration with the new access level. This approach minimizes risk by allowing you to test changes before they take effect, ensuring seamless updates with minimal disruption. References:

Google Cloud - Configuring VPC Service Controls

Google Cloud - Using Dry Run Mode

To ensure that data is encrypted while in use by the virtual machines (VMs) and enforce this policy across your organization, you should use Confidential VM instances. Here are the steps:

Enable Confidential VM:

Ensure that Confidential VMs are available in your selected regions and enabled for your project.

Set Organization Policy:

Implement an organization policy to enforce the use of Confidential VM instances for all VMs across your organization.

Use the Google Cloud Console or the gcloud command-line tool to set this policy. Example command:

gcloud resource-manager org-policies set-policy my_policy.yaml

Example my_policy.yaml:

name: organizations/1234567890/policies/compute.requireConfidentialCompute spec: rules: - enforce: true

Verify and Monitor:

Ensure that all newly created VMs across your organization are Confidential VMs.

Regularly monitor compliance through the Google Cloud Console and set up alerts if non-compliant VMs are created.

Benefits:

Data Encryption in Use: Confidential VMs ensure that data is encrypted not just at rest and in transit but also while in use.

Policy Enforcement: Organization policies provide a way to enforce security configurations across all projects under your organization.

References

Confidential Computing Documentation

Creating and Managing Organization Policies

Rewriting the objects in-place within the same bucket, specifying the new CMEK for encryption, allows you to re-encrypt the data without downloading and re-uploading it, thus minimizing costs and time.

The Google Cloud Resource Hierarchy is designed to allow inheritance with the ability to override policies at lower levels (Folders or Projects).2 This is the standard way to handle exceptions for specific business units without weakening the security posture of the entire organization.

According to Google Cloud Documentation (Understanding Hierarchy Evaluation):

"By default, organization policies are inherited by the descendants of the resource on which the policy is enforced. However, you can explicitly override a policy on a child resource (Folder or Project) by setting a new policy that either adds to or replaces the inherited values.3 This allows for granular control and exception handling."

Why this is the correct approach:

Isolation: By moving the workload to a specific folder, you isolate the exception.

Least Privilege: Only the resources within that folder gain the exception; the rest of the organization remains protected by the constraints/compute.vmExternalIpAccess constraint.

No "Bypass" Role: There is no standard IAM role that allows a user to "bypass" an Org Policy (Option A). Policies are enforced at the API level regardless of user roles.

Auditability: Having a specific folder with an override makes it easy for auditors to see exactly where and why an exception exists.

Requirement:

Enforce the use of Customer-Managed Encryption Keys (CMEK) for all new Cloud Storage resources in the organization.

Policy Constraint:

Use the constraints/gcp.restrictNonCmekServices constraint to enforce CMEK usage.

Policy Type and Value:

Set the policy type to allow to specify which services must use CMEK.

In this case, the policy value should be storage.googleapis.com to target Cloud Storage.

Command:

Applying the organization policy with the appropriate binding ensures that all new Cloud Storage resources under the organization will require CMEK.

Steps:

Step 1: Go to the Google Cloud Console.

Step 2: Navigate to the Organization Policies page.

Step 3: Apply the policy constraint constraints/gcp.restrictNonCmekServices with the allow policy type and storage.googleapis.com as the policy value.

If you want to manage the key encryption keys used for your data at rest, instead of having Google manage the keys, use Cloud Key Management Service to manage your keys. This scenario is known as customer-managed encryption keys (CMEK).

”This encryption method is reversible, which helps to maintain referential integrity across your database and has no character-set limitations.”

FPE provides fewer security guarantees compared to other deterministic encryption methods such as AES-SIV. For these reasons, Google strongly recommends using deterministic encryption with AES-SIV instead of FPE for all security sensitive use cases. Other methods like deterministic encryption using AES-SIV provide these stronger security guarantees and are recommended for tokenization use cases unless length and character set preservation are strict requirements—for example, for backward compatibility with a legacy data system.

To identify all principals who can change firewall rules, you need to determine which users or service accounts have permissions that allow them to modify firewall rules in your Google Cloud project. The correct permissions to check for this are compute.firewalls.create and compute.firewalls.delete. These permissions enable a user to create and delete firewall rules, respectively.

The Policy Analyzer tool in Google Cloud allows you to query and analyze IAM policies to identify which principals have specific permissions. By using Policy Analyzer, you can effectively identify all principals with the compute.firewalls.create and compute.firewalls.delete permissions.

Open Policy Analyzer: Go to the Google Cloud Console, navigate to IAM & Admin, and select Policy Analyzer.

Set Up Query: Create a new query specifying the permissions compute.firewalls.create and compute.firewalls.delete.

Run Query: Execute the query to retrieve a list of principals who have these permissions.

Review Results: Analyze the results to identify all users and service accounts with the capability to modify firewall rules.

This method ensures you have a comprehensive list of all principals who can change firewall rules, enhancing your audit and security posture.

Google Cloud Policy Analyzer Documentation

Google Cloud IAM Documentation

An unmanaged Google account is a personal account created by an individual using a corporate email address (e.g., john@company.com), which the organization cannot control. The root cause is that the organization has not claimed the identity for that email address.

Extracts:

"To prevent unmanaged Google account creation, you have two options: Create a user for every person who has an email address in your domain... If there are unmanaged accounts already created, you can use the Transfer Tool for unmanaged users to invite them to become managed users." (Source 5.1)

"If an admin creates a managed Google Account using the same account name as an existing unmanaged user account, this results in a conflicting account." (Source 5.3)

By provisioning an account for every employee (via Google Workspace or Cloud Identity), you effectively claim that domain identity, making it a managed account under IT control and preventing the creation of a new, unmanaged consumer account with the same email address.

Option B describes the foundational, preventative step in identity management: provisioning managed identities for all users in the domain.

- constraints/compute.trustedImageProjects

This list constraint defines the set of projects that can be used for image storage and disk instantiation for Compute Engine. If this constraint is active, only images from trusted projects will be allowed as the source for boot disks for new instances.

Google Cloud Directory Sync (GCDS): Install and configure GCDS to synchronize your on-premises Active Directory with Google Cloud Identity. This tool helps in maintaining consistency between your local directory and Google Cloud.

IAM Groups: Create IAM groups in Google Cloud with permissions that correspond to your Active Directory groups. This mapping ensures that users inherit the appropriate permissions based on their AD group membership.

Synchronization: Set up regular synchronization schedules to keep the user and group information up-to-date between your on-premises AD and Google Cloud.

Access Management: Use these IAM groups to manage access to Google Cloud resources, ensuring that permissions are applied consistently and securely. This approach leverages existing AD infrastructure for identity management, providing a seamless integration with Google Cloud. References:

Google Cloud - Google Cloud Directory Sync

Google Cloud - IAM Groups

Set up a Dedicated Interconnect link between the on-premises environment and Google Cloud:

Dedicated Interconnect provides a direct physical connection between your on-premises network and Google's network, which is ideal for high-throughput, low-latency connections.

Request a Dedicated Interconnect from the Google Cloud Console, specifying the required bandwidth and location.

Once provisioned, set up the connection on your on-premises router and configure the BGP sessions to exchange routes with Google Cloud.

Configure private access using the restricted.googleapis.com domains in on-premises DNS configurations:

Configure your on-premises DNS server to resolve Google APIs to restricted.googleapis.com. This ensures that the traffic stays within the Google network and is not exposed to the public internet.

Update your DNS settings to use restricted.googleapis.com for the necessary API endpoints.

This setup ensures that all Google Cloud API traffic is routed through the private link and subject to VPC Service Controls for additional security and compliance.

Cloud Bigtable is a fully managed NoSQL database service designed to handle large analytical and operational workloads. One of its key features is the ability to replicate data across multiple geographic locations automatically, ensuring high availability and resilience. Here’s a detailed explanation:

Replication: Cloud Bigtable supports multi-cluster routing and replication across different geographic regions. This means that data can be replicated across multiple zones within a region or even across regions, providing geo-redundancy.

Automatic Handling: Once configured, Bigtable automatically manages replication without requiring manual intervention. This is in line with the company's policy for long-term data storage that necessitates automatic replication over at least two geographic places.

Use Case Suitability: Bigtable is ideal for applications that require low-latency access to large amounts of data, which makes it suitable for various use cases including analytical applications, IoT, and financial data processing.

Configuration: Setting up replication involves creating instances in multiple zones and configuring them to replicate data. Google Cloud’s management interface and APIs make this straightforward to configure and monitor.

Google Cloud Bigtable Documentation

Google Cloud Storage Options