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
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. 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 has deployed their new backend on Google Cloud Platform (GCP).
You want to create a thorough testing process for new versions of the backend before they are released to the public.
You want the testing environment to scale in an economical way.
How should you design the process?

• A.Create a scalable environment in GCP for simulating production load.
• B.Use the existing infrastructure to test the GCP-based backend at scale.
• C.Build stress tests into each component of your application using resources internal to GCP to simulate load.
• D.Create a set of static environments in GCP to test different levels of load -- for example, high, medium, and low.

Comment: *

Name: *

Email: *

Verification: *

Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform.
Each tier (web, API, and database) scales independently of the others Network traffic should flow through the web to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier. How should you configure the network?

• A.Add each tier to a different subnetwork.
• B.Set up software based firewalls on individual VMs.
• C.Add tags to each tier and set up routes to allow the desired traffic flow.
• D.Add tags to each tier and set up firewall rules to allow the desired traffic flow.

Comment: *

Name: *

Email: *

Verification: *

For this question, refer to the TerramEarth case study. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.
Which two actions should you take?

• A.Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Coldline", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Coldline", and Action: "Set to Nearline".
• B.Create a Cloud Storage lifecycle rule with Age: "90", Storage Class: "Standard", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Nearline", and Action:
  "Set to Coldline".
• C.Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Coldline", and Action:
  "Delete".
• D.Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Nearline", and Action:
  "Delete".

Comment: *

Name: *

Email: *

Verification: *

Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?

• A.Create a tokenizer service and store only tokenized data.
• B.Create separate projects that only process credit card data.
• C.Create separate subnetworks and isolate the components that process credit card data.
• D.Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
• E.Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.

Comment: *

Name: *

Email: *

Verification: *

You have an application deployed on Kubernetes Engine using a Deployment named echo-deployment. The deployment is exposed using a Service called echo-service. You need to perform an update to the application with minimal downtime to the application. What should you do?

• A.Use kubect1 set image deployment/echo-deployment <new-image>
• B.Use the rolling update functionality of the Instance Group behind the Kubernetes cluster
• C.Update the deployment yaml file with the new container image. Use kubect1 delete deployment/ echo-deployment and kubect1 create -f <yaml-file>
• D.Update the service yaml file which the new container image. Use kubect1 delete service/echoservice and kubect1 create -f <yaml-file>

Comment: *

Name: *

Email: *

Verification: *