Introductory info

Company overview

Helicopter Racing League (HRL) is a global sports league for competitive helicopter racing. Each year HRL holds the world championship and

several regional leaque competitions where teams compete to earn a spot in the world championship. HRL offers a paid service to stream the

races all over the world with live telemetry and predictions throughout each race.

Solution concept

HRL wants to migrate their existing service to a new platform to expand their use of managed Al and ML services to faciitate race predictions

Additionaly, as new fans engage with the sport, particularly in emerging regions,they want to move the serving of their content, both realtime and

recorded,closer to their users.

Existing technical environment

HRL is a public cloud-frst company, the core of their mision-critical applications runs on their curent public cloud provider. Video recording and

editing is performed at the race tracks, and the content is encoded and transcoded, where needed, in the cloud. Enterprise-grade connectivitly and

local compute is provided by truck-mounted mobile data centers. Thei race prediction services are hosted exclusively on their existing public

cloud provider. Their existing technical environment is as follows:

Existing content is stored in an object storage service on their existing public cloud provider

Video encoding and transcoding is performed on VMs created for each job.

Race predictions are performed using TensorFlow running on VMs in the current public cloud provider.

Business requirements

HRL's owners want to expand thei predictive capabilities and reduce latency for ther viewers in emerging markets. Their requirements are.

Support ability to expose the predictive models to partners.

Increase predictive capabilities during and before races.

A-t Race results

a-t Mechanical failures

A-t Crowd sentiment

Increase telemetry and create additional insights

Measure fan enaagement with new predictions.

Enhance alobal availability and quality of the broadcasts.

Increase the number of concurrent wewers.

Minimize operational complexity.

Ensure compliance with requlations.

Create a merchandising revenue stream.

Technical reauirements

Maintain or increase prediction throughput and accuracy.

Reduce viewer latency.

Increase transcoding performance.

Create real-time analytics of viewer consumption patterns and engagement.

Create a data mart to enable processing of large volumes of race data.

Executive statement

Dur CE0, S. Hawke, wants to bring high-adrenaline racing to fans all around the world. We listen to our fans, and they want enhanced video

streams that include predictions of events within the race (e.g, overtaking). 0ur curent platform allows us to predict race outcomes but lacks the

facility to support real-time predictions during races and the capacity to process season-ong results.

Question

For this question, refer to the Helicopter Racing League (HRl) case study. Your team is in charge of creating a payment card data vault for card

numbers used to bil tens of thousands of viewers, merchandise consumers, and season ticket holders, You need to implement a custom card

tokenization seryice that meets the following requirements:

* It must provide low latency at minimal cost.

∗ It must be able to identify duplicate credit cards and must not store plaintext card numbers.

∗ It should support annual key rotation.

Which storage approach should you adopt for your tokenization service?

For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional racing league in Cape Town, South Africa. In an effort to give customers in Cape Town a better user experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are a member of the HRL security team and you need to configure the update that will allow only the Fastly IP address ranges through the External HTTP(S) load balancer. Which command should you use?

For this question, refer to the Helicopter Racing League (HRL) case study. The HRL development team releases a new version of their predictive capability application every Tuesday evening at 3 am. UTC to a repository. The security team at HRL has developed an in-house penetration test Cloud Function called Airwolf. The security team wants to run Airwolf against the predictive capability application as soon as it is released every Tuesday. You need to set up Airwolf to run at the recurring weekly cadence. What should you do?

For this question, refer to the Helicopter Racing League (HRL) case study. HRL wants better prediction accuracy from their ML prediction models. They want you to use Google's AI Platform so HRL can understand and interpret the predictions. What should you do?

For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost-effective approach for storing their race data such as telemetry. They want to keep all historical records, train models using only the previous season's data, and plan for data growth in terms of volume and information collected. You need to propose a data solution. Considering HRL business requirements and the goals expressed by CEO S. Hawke, what should you do?

For this question, refer to the Helicopter Racing League (HRL) case study. A recent finance audit of cloud infrastructure noted an exceptionally high number of

Compute Engine instances are allocated to do video encoding and transcoding. You suspect that these Virtual Machines are zombie machines that were not deleted after their workloads completed. You need to quickly get a list of which VM instances are idle. What should you do?

You need to upgrade the EHR connection to comply with their requirements. The new connection design must support business-critical needs and meet the same network and security policy requirements. What should you do?

For this question, refer to the EHR Healthcare case study. You need to define the technical architecture for hybrid connectivity between EHR's on-premises systems and Google Cloud. You want to follow Google's recommended practices for production-level applications. Considering the EHR Healthcare business and technical requirements, what should you do?

For this question, refer to the EHR Healthcare case study. You are a developer on the EHR customer portal team. Your team recently migrated the customer portal application to Google Cloud. The load has increased on the application servers, and now the application is logging many timeout errors. You recently incorporated Pub/Sub into the application architecture, and the application is not logging any Pub/Sub publishing errors. You want to improve publishing latency.

What should you do?

For this question, refer to the EHR Healthcare case study. In the past, configuration errors put public IP addresses on backend servers that should not have been accessible from the Internet. You need to ensure that no one can put external IP addresses on backend Compute Engine instances and that external IP addresses can only be configured on frontend Compute Engine instances. What should you do?

For this question, refer to the EHR Healthcare case study. You are responsible for designing the Google Cloud network architecture for Google Kubernetes

Engine. You want to follow Google best practices. Considering the EHR Healthcare business and technical requirements, what should you do to reduce the attack surface?

introductory info

Company Overview

Mountkirk Games makes online, session-based, multiplayer games for the most popular moble platforms. They buld allof 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 MySOL

databases, and analytics tools.

Their curent model is to write game statistics to fles and send them through an ETL tool that loads them into a centraized MySoL database for

reporting

Solution Concept .

Mountkirk Games is bullding 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 NoSOl database.

Business Reguirements

Increase to a global footprint

Improve uptime "" downtime is loss of players

Increase eficiency of the cloud resources we use

Reduce latency to all customers

Technical Regulrements

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 customize Linux distro

Requirements for Game Analyties Platform

1.Dynamically scale up or down based on game activity

2.Process incoming data on the fly directly from the game servers

3. Pracess data that arrives late because of slow mobile networks

4.Allow SOL gueries to access at least 10 TB of historical data

5. Process fles that are regularly uploaded by users' moblle devices

6. Use only fully managed services

CEO Statement -

0ur last sucessful game did not scale wel with our previous cloud provider,resulting in lower user adoption and affecting the game's reputation.

Our investors want more key performance lindicators (KPls) to evaluate the speed and stablty of the game, as well as other metrics that provide

deeper insight into usage patterns so we can adapt the game to target users.

CTO Statement -

Our curent technology stack cannot provide the scale we need, so we want to replace MysOL 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 Kpls, As a result, we do not engage the right users, we are not

conident that our marketing is targeting the right users, and we are not seling enough premium Blast Ups inside the games, which dramaticall

impacts our revenue.

<strong>Question</strong>

Mountkirk Games wants you to design their new testing strategy, How should the test cowerage differ from their existing backends on the other platforms?

✑ 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?

What should you do to isolate development environments from staging and production?

Which combination of Google technologies will meet all of their requirements?