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| Section | Objectives |
|---|
| Design and plan a Google Cloud network | - Hybrid and multi-cloud architecture design
- 1. Routing strategy design (BGP)
- 2. Interconnect and VPN planning
- VPC design and topology planning
- 1. Regional vs global architecture considerations
- 2. Subnet design and IP address planning
|
| Implement virtual networks | - Load balancing and traffic management
- 1. Cloud DNS configuration
- 2. HTTP(S), TCP/SSL load balancing
- VPC configuration
- 1. Custom mode VPC setup
- 2. Firewall rules configuration
|
| Manage, monitor, and optimize network operations | - Network monitoring and logging
- 1. Cloud Monitoring and Logging usage
- 2. Network Intelligence Center tools
- Security and troubleshooting
- 1. Latency and connectivity diagnostics
- 2. Firewall and security policy troubleshooting
|
| Implement hybrid connectivity | - Dedicated and partner interconnect
- 1. High availability design patterns
- 2. VLAN attachments and configuration
- VPN and peering
- 1. HA VPN setup
- 2. VPC peering and Shared VPC
|
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Google Cloud Certified - Professional Cloud Network Engineer Sample Questions (Q191-Q196):
NEW QUESTION # 191
(You are developing an internet of things (IoT) application that captures sensor data from multiple devices that have already been set up. You need to identify the global data storage product your company should use to store this data. You must ensure that the storage solution you choose meets your requirements of sub- millisecond latency. What should you do?)
- A. Store the IoT data in Bigtable.
- B. Capture IoT data in BigQuery datasets.
- C. Store the IoT data in Cloud Storage. Implement caching by using Cloud CDN.
- D. Store the IoT data in Spanner. Use caches to speed up the process and avoid latencies.
Answer: A
Explanation:
Comprehensive and Detailed In Depth Explanation:
Let's evaluate each option based on the requirement of sub-millisecond latency for globally stored IoT data:
A). Spanner with Caching: While Spanner offers strong consistency and global scalability, the base latency might not consistently be sub-millisecond for all read/write operations globally. Introducing caching adds complexity and doesn't guarantee sub-millisecond latency for all initial reads or cache misses.
B). Bigtable: Bigtable is a highly scalable NoSQL database service designed for low-latency, high-throughput workloads. It excels at storing and retrieving large volumes of time-series data, which is typical for IoT sensor data. Its architecture is optimized for single-key lookups and scans, providing consistent sub-millisecond latency, making it a strong candidate for this use case.
C). BigQuery: BigQuery is a fully managed, serverless data warehouse designed for analytical queries on large datasets. While it's excellent for analyzing IoT data in batch, it's not optimized for the low-latency, high- throughput ingestion and retrieval required for real-time IoT applications with sub-millisecond latency needs.
D). Cloud Storage with Cloud CDN: Cloud Storage is object storage and is not designed for low-latency transactional workloads. Cloud CDN is a content delivery network that caches content closer to users for faster delivery, but it's not suitable for the primary storage of rapidly incoming IoT sensor data requiring sub- millisecond write latency.
Google Cloud Documentation References:
Cloud Bigtable Overview: https://cloud.google.com/bigtable/docs/overview - This document highlights Bigtable's suitability for low-latency and high-throughput applications, including IoT. It mentions its ability to handle massive amounts of data with consistent performance.
Spanner Overview: https://cloud.google.com/spanner/docs/overview - While Spanner offers low latency, Bigtable is generally preferred for extremely high-throughput, low-latency use cases like raw sensor data ingestion due to its optimized architecture for such workloads.
BigQuery Overview: https://cloud.google.com/bigquery/docs/introduction - This emphasizes BigQuery's analytical capabilities rather than low-latency operational workloads.
Cloud Storage Overview: https://cloud.google.com/storage/docs/overview - This describes Cloud Storage as object storage, not ideal for sub-millisecond latency reads and writes required for real-time IoT data.
NEW QUESTION # 192
Your organization is developing a landing zone architecture with the following requirements:
There should be no communication between production and non-production environments.
Communication between applications within an environment may be necessary.
Network administrators should centrally manage all network resources, including subnets, routes, and firewall rules.
Each application should be billed separately.
Developers of an application within a project should have the autonomy to create their compute resources.
Up to 1000 applications are expected per environment.
You need to create a design that accommodates these requirements. What should you do?
- A. Create a design that implements a single Shared VPC. Use VPC firewall rules with secure tags to enforce micro-segmentation between environments.
- B. Create a design that has one host project with a Shared VPC for the production environment, another host project with a Shared VPC for the non-production environment, and a service project that is associated with the corresponding host project for each initiative.
- C. Create a design where each project has its own VPC. Ensure all VPCs are connected by a Network Connectivity Center hub that is centrally managed by the network team.
- D. Create a design that has a Shared VPC for each project. Implement hierarchical firewall policies to apply micro-segmentation between VPCs.
Answer: B
Explanation:
This design allows you to separate production and non-production environments while using Shared VPCs. Each environment has its own Shared VPC, and a service project is associated with each, allowing for separate billing and autonomy for developers. Centralized management of network resources is handled by the host projects.
NEW QUESTION # 193
You have enabled HTTP(S) load balancing for your application, and your application developers have reported that HTTP(S) requests are not being distributed correctly to your Compute Engine Virtual Machine instances. You want to find data about how the request are being distributed.
Which two methods can accomplish this? (Choose two.)
- A. In Stackdriver Error Reporting, look for any unacknowledged errors for the Cloud Load Balancers service.
- B. In Stackdriver Monitoring, create a new dashboard and track the https/backend_request_count metric for the load balancer.
- C. In Stackdriver Monitoring, select Resources > Google Cloud Load Balancers and review the Key Metrics graphs in the dashboard.
- D. In Stackdriver Monitoring, select Resources > Metrics Explorer and search for https
/request_bytes_count metric. - E. On the Load Balancer details page of the GCP Console, click on the Monitoring tab, select your backend service, and look at the graphs.
Answer: B,E
NEW QUESTION # 194
You want to use Cloud Interconnect to connect your on-premises network to a GCP VPC. You cannot meet Google at one of its point-of-presence (POP) locations, and your on-premises router cannot run a Border Gateway Protocol (BGP) configuration.
Which connectivity model should you use?
- A. Partner Interconnect with a layer 3 partner
- B. Partner Interconnect with a layer 2 partner
- C. Direct Peering
- D. Dedicated Interconnect
Answer: A
Explanation:
For Layer 3 connections, your service provider establishes a BGP session between your Cloud Routers and their edge routers for each VLAN attachment. You don't need to configure BGP on your on-premises router. Google and your service provider automatically set the correct configurations.
https://cloud.google.com/network-connectivity/docs/interconnect/concepts/partner-overview
NEW QUESTION # 195
You have several VMs across multiple VPCs in your cloud environment that require access to internet endpoints. These VMs cannot have public IP addresses due to security policies, so you plan to use Cloud NAT to provide outbound internet access. Within your VPCs, you have several subnets in each region. You want to ensure that only specific subnets have access to the internet through Cloud NAT. You want to avoid any unintentional configuration issues caused by other administrators and align to Google-recommended practices. What should you do?
- A. Deploy Cloud NAT in each VPC and configure a custom source range that includes the allowed subnets. Configure Cloud NAT rules to only permit the allowed subnets to egress through Cloud NAT.
- B. Create a firewall rule in each VPC at priority 500 that targets all instances in the network and denies egress to the internet (0.0.0.0/0). Create a firewall rule at priority 300 that targets all instances in the network, has a source filter that maps to the allowed subnets, and allows egress to the internet (0.0.0.0
/0). Deploy Cloud NAT and configure a custom source range that includes the allowed subnets. - C. Create a constraints/compute.restrictCloudNATUsage organizational policy constraint. Attach the constraint to a folder that contains the associated projects. Configure the allowedValues to only contain the subnets that should have internet access. Deploy Cloud NAT and select only the allowed subnets.
- D. Create a firewall rule in each VPC at priority 500 that targets all instances in the network and denies egress to the internet (0.0.0.0/0). Create a firewall rule at priority 300 that targets all instances in the network, has a source filter that maps to the allowed subnets, and allows egress to the internet (0.0.0.0
/0). Deploy Cloud NAT and configure all primary and secondary subnet source ranges.
Answer: C
Explanation:
Explanation: Using an organizational policy with the restrictCloudNATUsage constraint allows you to limit Cloud NAT usage to specific subnets, ensuring that only the necessary subnets can access the internet. This method aligns with Google-recommended practices for controlling Cloud NAT configurations across multiple VPCs and regions.
NEW QUESTION # 196
......
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