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NEW QUESTION 44
Case Study: 1 - Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's 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.
Technical Requirements
Requirements for Game Backend Platform

Dynamically scale up or down based on game activity.
Connect to a managed NoSQL database service.
Run customized Linx 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 SQL queries to access at least 10 TB of historical data.
Process files that are regularly uploaded by users' mobile devices.
Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming 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 gams to target users.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:

Services are deployed redundantly across multiple regions in the US
and Europe.
Only frontend services are exposed on the public internet.
They can provide a single frontend IP for their fleet of services.
Deployment artifacts are immutable.
Which set of products should they use?

A. Google Container Registry, Google Container Engine, Google HTTP(s) Load Balancer
B. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
C. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
D. Google Cloud Storage, Google App Engine, Google Network Load Balancer

Answer: B
Explanation:
Google Cloud Functions is a serverless environment to build and connect cloud services.
Google Cloud Pub/Sub brings the scalability, flexibility, and reliability of enterprise message- oriented middleware to the cloud. By providing many-to-many, asynchronous messaging that decouples senders and receivers, it allows for secure and highly available communication between independently written applications. Google Cloud Pub/Sub delivers low-latency, durable messaging that helps developers quickly integrate systems hosted on the Google Cloud Platform and externally.
Incorrect Answers:
A: Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes.
C: Store your private Docker container images on Cloud Platform for fast, scalable retrieval and deployment. Container Registry is a private Docker repository that works with popular continuous delivery systems. It runs on Cloud Platform to provide consistent uptime on an infrastructure protected by Google's security. You pay only for storage and internet egress you use, there is no per-image fee.
Reference: https://cloud.google.com/load-balancing/
https://cloud.google.com/solutions/ansible-with-spinnaker-tutorial
http://blog.armory.io/what-is-immutable-infrastructure/
https://cloud.google.com/compute/docs/load-balancing/http/

NEW QUESTION 45
Your company is forecasting a sharp increase in the number and size of Apache Spark and Hadoop jobs being run on your local datacenter You want to utilize the cloud to help you scale this upcoming demand with the least amount of operations work and code change. Which product should you use?

A. Google Compute Engine
B. Google Container Engine
C. Google Cloud Dataproc
D. Google Cloud Dataflow

Answer: C

NEW QUESTION 46
You need to optimize batch file transfers into Cloud Storage for Mountkirk Games' new Google Cloud solution.
The batch files contain game statistics that need to be staged in Cloud Storage and be processed by an extract transform load (ETL) tool. What should you do?

A. Use gsutil to extract the files as the first part of ETL.
B. Use gsutil to batch copy the files in parallel.
C. Use gsutil to batch move files in sequence.
D. Use gsutil to load the files as the last part of ETL.

Answer: B

NEW QUESTION 47
Your company has an application deployed on Anthos clusters (formerly Anthos GKE) that is running multiple microservices. The cluster has both Anthos Service Mesh and Anthos Config Management configured. End users inform you that the application is responding very slowly. You want to identify the microservice that is causing the delay. What should you do?

A. Reinstall istio using the default istio profile in order to collect request latency. Evaluate the telemetry between the microservices in the Cloud Console.
B. Use Anthos Config Management to create a namespaceSelector selecting the relevant cluster namespace. On the Google Cloud Console page for Google Kubernetes Engine, visit the workloads and filter on the namespace. Inspect the configurations of the filtered workloads.
C. Use Anthos Config Management to create a ClusterSelector selecting the relevant cluster. On the Google Cloud Console page for Google Kubernetes Engine, view the Workloads and filter on the cluster. Inspect the configurations of the filtered workloads.
D. Use the Service Mesh visualization in the Cloud Console to inspect the telemetry between the microservices.

Answer: D

NEW QUESTION 48
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