Google Professional-Cloud-Network-Engineer - Google Cloud Certified - Professional Cloud Network Engineer

For private connectivity with at least 1 Gbps bandwidth and without using the public internet, Partner Interconnect is the suitable choice if you do not require the 10 Gbps minimum of Dedicated Interconnect. With Partner Interconnect, you create a VLAN attachment and work with a service provider that facilitates the connection between your on-premises network and Google Cloud. This solution supports connections as low as 50 Mbps and up to 10 Gbps.

https://cloud.google.com/armor/docs/security-policy-concepts#preview_mode

Understanding VPC Flow Logs:

VPC Flow Logs is a feature that captures information about the IP traffic going to and from network interfaces in a VPC. It helps in monitoring and analyzing network traffic, ensuring security, and optimizing network performance.

Current Configuration:

According to the diagram, VPC Flow Logs is already configured for Subnet-1 in the host VPC. This means that traffic information for Subnet-1 is being captured and logged.

Requirement for Subnet-2:

The goal is to monitor flow logs for Subnet-2, which is in the service project VPC.

Correct Configuration for Subnet-2:

To monitor the flow logs for Subnet-2, you need to configure VPC Flow Logs within the service project VPC where Subnet-2 resides. This is because VPC Flow Logs must be configured in the same project and VPC where the subnet is located.

Implementation Steps:

Go to the Google Cloud Console.

Navigate to the service project where Subnet-2 is located.

Select the VPC network containing Subnet-2.

Enable VPC Flow Logs for Subnet-2 by editing the subnet settings and enabling the flow logs option.

Cost and Performance Considerations:

Enabling VPC Flow Logs may incur additional costs based on the volume of data logged. Ensure to review and understand the pricing implications.

Analyze and manage the data collected to avoid unnecessary logging and costs.

For Cloud NGFW in Google Cloud, firewall endpoints are typically created at the regional level, allowing you to associate these with your VPC network for Layer 7 traffic inspection. This regional setup ensures high availability and scales the inspection service across the network.

The Performance Dashboard in the Network Intelligence Center provides a detailed view of network latency and performance metrics. For inter-region latency issues, you can quickly identify round-trip times (RTT) and latency using this tool by selecting the specific regions and network tiers, which allows you to diagnose any anomalies or patterns impacting performance.

The correct answer is D because it meets the following requirements:

Each internal project has its own Google Cloud project, which can be easily created and deleted by Terraform using the google_project resource1.

Each internal project has its own Google Cloud project owner, which can be assigned by Terraform using the google_project_iam_member resource1.

The deployment is simple and the code is reusable with centralized management, because the Shared VPC allows you to connect multiple service projects to a single host project that contains the network resources2. This way, you can use Terraform modules to create and manage the network resources in the host project, and then reference them in the service projects3.

Option A is incorrect because it does not create separate Google Cloud projects for each internal project, which makes it harder to delete the infrastructure and assign project owners. Option B is incorrect because it does not create separate Google Cloud projects for each internal project, and also because it attaches the service projects to a Shared VPC, which is not recommended for short-lived projects2. Option C is incorrect because it does not use a Shared VPC, which means that each internal project has to create and manage its own network resources, which increases complexity and reduces reusability.

Comprehensive and Detailed In Depth Explanation:

Let's analyze each option based on the requirements: PostgreSQL compatibility, significant performance improvement, minimal schema/code changes, handling large data volumes, Google-recommended practices, and cost minimization:

A. Migrate your data to AlloyDB: AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible database service that offers significant performance improvements over standard PostgreSQL due to its architectural optimizations. It is designed to handle large data volumes and minimizes the need for schema and application code changes as it's wire-compatible with PostgreSQL. This aligns well with the requirements for performance improvement, minimal changes, large data, and being a Google-recommended option for PostgreSQL workloads.

B. Migrate your data to Spanner: Spanner is a globally distributed, horizontally scalable database with strong consistency. While it offers excellent scalability and performance, it's not directly PostgreSQL-compatible. Migrating to Spanner would likely require significant schema and application code changes due to differences in data modeling and SQL dialect.

C. Migrate your data to Firebase: Firebase is a suite of mobile and web development tools, with its primary database offering being Firestore (a NoSQL document database) and Realtime Database. These are not PostgreSQL-compatible and would require substantial changes to the data model and application code.

D. Migrate your data to Bigtable: Bigtable is a highly scalable NoSQL wide-column store. It's not compatible with PostgreSQL and requires a completely different data model and application logic.

Therefore, AlloyDB is the most suitable option as it provides PostgreSQL compatibility for minimal migration effort, significant performance improvements, scalability for large data volumes, and is a recommended Google Cloud database service for PostgreSQL workloads.

Google Cloud Documentation References:

AlloyDB for PostgreSQL Overview: https://cloud.google.com/alloydb/docs/overview - This document highlights AlloyDB 's PostgreSQL compatibility, performance benefits, scalability, and suitability for migrating existing PostgreSQL workloads.

Spanner Overview: https://cloud.google.com/spanner/docs/overview - This emphasizes Spanner 's unique features and differences from traditional relational databases like PostgreSQL.

Firebase Documentation: https://firebase.google.com/docs - This outlines the features of Firebase, including Firestore and Realtime Database, highlighting their NoSQL nature and incompatibility with PostgreSQL.

Cloud Bigtable Overview: https://cloud.google.com/bigtable/docs/overview - This describes Bigtable as a NoSQL database, emphasizing its differences from relational databases like PostgreSQL.

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