新版Google Professional-Cloud-Architect題庫上線 - Professional-Cloud-Architect考試指南

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最新的 Google Cloud Certified Professional-Cloud-Architect 免費考試真題 (Q82-Q87):

問題 #82
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?

答案：D

解題說明：
and redeploy your application.
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler Cluster autoscaling
--enable-autoscaling
Enables autoscaling for a node pool.
Enables autoscaling in the node pool specified by --node-pool or the default node pool if --node-pool is not provided.
Where:
--max-nodes=MAX_NODES
Maximum number of nodes in the node pool.
Maximum number of nodes to which the node pool specified by --node-pool (or default node pool if unspecified) can scale.
Incorrect Answers:
C, D: Warning: Do not use Alpha Clusters or alpha features for production workloads.
Note: You can experiment with Kubernetes alpha features by creating an alpha cluster. Alpha clusters are short-lived clusters that run stable Kubernetes releases with all Kubernetes APIs and features enabled. Alpha clusters are designed for advanced users and early adopters to experiment with workloads that take advantage of new features before those features are production-ready. You can use Alpha clusters just like normal Kubernetes Engine clusters.


問題 #83
For this question, refer to the TerramEarth case study.
TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour. How should you design the data ingestion?

答案：D


問題 #84
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?

答案：D

解題說明：
Reference https://cloud.google.com/architecture/setting-up-private-access-to-cloud-apis-through-vpn-tunnels


問題 #85
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
- Increase to a global footprint.
- Improve uptime - downtime is loss of players.
- Increase efficiency of the cloud resources we use.
- Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
- Dynamically scale up or down based on game activity.
- Connect to a transactional database service to manage user profiles and game state.
- Store game activity in a timeseries database service for future analysis.
- As the system scales, ensure that data is not lost due to processing backlogs.
- Run hardened Linux distro.
Requirements for Game Analytics Platform
- Dynamically scale up or down based on game activity
- Process incoming data on the fly directly from the game servers
- Process data that arrives late because of slow mobile networks
- Allow queries to access at least 10 TB of historical data
- Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design a way to test the analytics platform's resilience to changes in mobile network latency.
What should you do?

答案：B

解題說明：
If you're using a service mesh like Istio to manage your app services, you can inject faults at the application layer instead of killing pods or machines, or you can inject corrupting packets at the TCP layer. You can introduce delays to simulate network latency or an overloaded upstream system. You can also introduce aborts, which mimic failures in upstream systems.
https://cloud.google.com/solutions/scalable-and-resilient-apps


問題 #86
Your company creates rendering software which users can download from the company website. Your company has customers all over the world. You want to minimize latency for all your customers. You want to follow Google-recommended practices.
How should you store the files?

答案：C

解題說明：
Reference:
https://cloud.google.com/storage/docs/locations#location-mr


問題 #87
......

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