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| Section | Weight | Objectives |
|---|---|---|
| Managing implementation | 12.5% | - Using Google Cloud tools and APIs programmatically
|
| Analyzing and optimizing technical and business processes | 15% | - Optimizing cost and resource efficiency
|
| Designing for security and compliance | 17.5% | - Implementing identity and access management
|
| Managing and provisioning solution infrastructure | 15% | - Provisioning and managing compute resources
|
| Ensuring solution and operations excellence | 12.5% | - Implementing monitoring, logging, and observability
|
| Designing and planning a cloud solution architecture | 25% | - Planning cloud migration and hybrid/multi-cloud environments
|
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NEW QUESTION # 295
Your organization has 5 TB of private data on premises. You need to migrate the data to Cloud Storage. You want to maximize the data transfer speed. How should you migrate the data?
Answer: C
Explanation:
A is correct because gsutil gives you access to write data to Cloud Storage.
B is not correct because gcloud is the command-line interface for common platform tasks and does not include accessing Cloud Storage.
C is not correct because the data size would require a resumable upload, and that does not meet the requirement of maximizing the data transfer speed.
D is not correct because Storage Transfer Service is for importing online data, not on-premises.
Your data source can be an Amazon Simple Storage Service (Amazon S3) bucket, an HTTP/HTTPS location, or a Cloud Storage bucket.
https://cloud.google.com/storage/docs/gsutil
https://cloud.google.com/sdk/gcloud/
https://cloud.google.com/storage/docs/json_api/v1/how-tos/upload
https://cloud.google.com/storage/docs/uploading-objects
https://cloud.google.com/storage-transfer/docs/overview
NEW QUESTION # 296
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must
meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?
Answer: E
Explanation:
Explanation/Reference:
Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered
by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure
reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the
cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture
streaming metrics, run intensive analytics.
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
References: https://cloud.google.com/solutions/big-data/stream-analytics/
Testlet 1
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.
NEW QUESTION # 297
You need to ensure reliability for your application and operations by supporting reliable task a scheduling for compute on GCP. Leveraging Google best practices, what should you do?
Answer: D
Explanation:
Explanation
https://cloud.google.com/solutions/reliable-task-scheduling-compute-engine
NEW QUESTION # 298
You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud. You are unsure about the optimum CPU and memory options. The application have a consistent usage patterns across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?
Answer: B
Explanation:
Create a Compute engine instance with CPU and Memory options similar to your application's current on-premises virtual machine. Install the cloud monitoring agent, and deploy the third party application. Run a load with normal traffic levels on third party application and follow the Rightsizing Recommendations in the Cloud Console
https://cloud.google.com/migrate/compute-engine/docs/4.9/concepts/planning-a-migration/cloud-instance-rightsizing?hl=en
NEW QUESTION # 299
Your development team has created a mobile game app. You want to test the new mobile app on Android and iOS devices with a variety of configurations. You need to ensure that testing is efficient and cost-effective. What should you do?
Answer: A
Explanation:
Reference:
Topic 8, Helicopter Racing League Case
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 league 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 AI and ML services to facilitate race predictions. Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.
Existing technical environment
HRL is a public cloud-first company; the core of their mission-critical applications runs on their current 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 connectivity and local compute is provided by truck-mounted mobile data centers. Their 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 their predictive capabilities and reduce latency for their viewers in emerging markets. Their requirements are:
Support ability to expose the predictive models to partners.
Increase predictive capabilities during and before races:
* Race results
* Mechanical failures
* Crowd sentiment
Increase telemetry and create additional insights.
Measure fan engagement with new predictions.
Enhance global availability and quality of the broadcasts.
Increase the number of concurrent viewers.
Minimize operational complexity.
Ensure compliance with regulations.
Create a merchandising revenue stream.
Technical requirements
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
Our CEO, 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). Our current platform allows us to predict race outcomes but lacks the facility to support real-time predictions during races and the capacity to process season-long results.
NEW QUESTION # 300
......
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