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Planning & Configuring Cloud Solutions

Plan and estimate the GCP product use with Pricing Calculator;
Plan and configure compute resources with specific skills in choosing the relevant compute choices for a specific workload as well as utilizing preemptible virtual machines and custom machine types as relevant;
Plan and configure network resources, which include distinguishing load balancing alternatives, configuring the Cloud DNS, establishing resource locations within a network for its availability.
Plan and configure data storage options with a focus on product choice and selecting storage options;

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Google Associate-Cloud-Engineer Certification Exam is an entry-level certification that can help individuals kick-start their career in cloud computing. Google Associate Cloud Engineer Exam certification is suitable for individuals who have some basic knowledge of cloud computing concepts and have experience working with GCP. Associate-Cloud-Engineer exam is ideal for IT professionals, system administrators, and developers who want to validate their skills and knowledge in using GCP. Google Associate Cloud Engineer Exam certification exam is conducted online and comprises of multiple-choice questions that assess the candidates' understanding of GCP services and their ability to use them in real-world scenarios. Passing the exam leads to the award of the Google Associate Cloud Engineer certification, which is highly valued in the IT industry.

Google Associate-Cloud-Engineer Exam is a valuable certification for individuals who want to demonstrate their skills and knowledge in managing and deploying applications and services on Google Cloud Platform. It provides a solid foundation for candidates who are looking to pursue a career in cloud computing or for those who want to expand their skills and knowledge in this field.

Google Associate Cloud Engineer Exam Sample Questions (Q141-Q146):

NEW QUESTION # 141
You need to set up permissions for a set of Compute Engine instances to enable them to write data into a particular Cloud Storage bucket. You want to follow Google-recommended practices. What should you do?

A. Create a service account with an access scope. Use the access scope 'https://www.googleapis.com/auth/devstorage.write_only'.
B. Create a service account and add it to the IAM role 'storage.objectCreator' for that bucket.
C. Create a service account with an access scope. Use the access scope 'https://www.googleapis.com/auth/cloud-platform'.
D. Create a service account and add it to the IAM role 'storage.objectAdmin' for that bucket.

Answer: C

Explanation:
Reference:
https://towardsdatascience.com/enlightened-datalab-notebooks-35ce8ef374c0

NEW QUESTION # 142
You are performing a monthly security check of your Google Cloud environment and want to know who has access to view data stored in your Google Cloud Project. What should you?

A. Create a Data Loss Prevention job.
B. Review the Identity-Aware Proxy settings for each resource.
C. Review the IAM permissions for any role that allows for data access.
D. Enable Audit Logs for all APIs that are related to data storage.

Answer: C

Explanation:
Explanation/Reference: https://cloud.google.com/compute/docs/access

NEW QUESTION # 143
Your customer has implemented a solution that uses Cloud Spanner and notices some read latency-related performance issues on one table. This table is accessed only by their users using a primary key. The table schema is shown below.

You want to resolve the issue. What should you do?

A. Option A
B. Option C
C. Option D
D. Option B

Answer: B

Explanation:
Explanation
As mentioned in Schema and data model, you should be careful when choosing a primary key to not accidentally create hotspots in your database. One cause of hotspots is having a column whose value monotonically increases as the first key part, because this results in all inserts occurring at the end of your key space. This pattern is undesirable because Cloud Spanner divides data among servers by key ranges, which means all your inserts will be directed at a single server that will end up doing all the work.
https://cloud.google.com/spanner/docs/schema-design#primary-key-prevent-hotspots

NEW QUESTION # 144
Your company stores data from multiple sources that have different data storage requirements.
These data include:
1. Customer data that is structured and read with complex queries
2. Historical log data that is large in volume and accessed
infrequently
3. Real-time sensor data with high-velocity writes, which needs to be
available for analysis but can tolerate some data loss
You need to design the most cost-effective storage solution that fulfills all data storage requirements.
What should you do?

A. Use Cloud SQL for customer data, Cloud Storage (Archive) for historical logs, and Bigtable for sensor data.
B. Use Cloud SQL for customer data, Cloud Storage (Coldline) for historical logs, and BigQuery for sensor data.
C. Use Firestore for customer data, Cloud Storage (Nearline) for historical logs, and Bigtable for sensor data.
D. Use Spanner for all data.

Answer: A

Explanation:
Customer Data: Structured and queried with complexity
Cloud SQL is well suited for structured, relational data and supports complex SQL queries. It is a managed relational database service that provides a familiar SQL interface, which is ideal for customer data with complex querying needs.
Historical Log Data: Large in volume and accessed infrequently
Cloud Storage offers various storage classes optimized for cost based on access frequency. For data that is rarely accessed, the Archive storage class is the most cost-effective option. Although Archive has longer retrieval times compared to other classes, it is appropriate when the data is kept solely for audit or compliance purposes and isn't expected to be read often.
Real-Time Sensor Data: High-velocity writes and available for analysis (with some tolerance for data loss) Bigtable is designed to handle high ingestion rates and large volumes of time-series or sensor data. It provides low-latency reads and writes, making it an excellent choice for real-time analytics of sensor data. Its design also aligns well with scenarios where occasional data loss is acceptable.

NEW QUESTION # 145
For analysis purposes, you need to send all the logs from all of your Compute Engine instances to a BigQuery dataset called platform-logs. You have already installed the Stackdriver Logging agent on all the instances.
You want to minimize cost. What should you do?

A. 1. In Stackdriver Logging, create a logs export with a Cloud Pub/Sub topic called logsas a sink.
2. Create a Cloud Function that is triggered by messages in the logstopic.
3. Configure that Cloud Function to drop logs that are not from Compute Engine and to insert Compute Engine logs in the platform-logsdataset.
B. 1. Create a Cloud Function that has the BigQuery User role on the platform-logsdataset.
2. Configure this Cloud Function to create a BigQuery Job that executes this query:
INSERT INTO dataset.platform-logs (timestamp, log)
SELECT timestamp, log FROM compute.logs
WHERE timestamp > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)
3. Use Cloud Scheduler to trigger this Cloud Function once a day.
C. 1. Give the BigQuery Data Editor role on the platform-logsdataset to the service accounts used by your instances.
2. Update your instances' metadata to add the following value: logs-destination: bq://platform- logs.
D. 1. In Stackdriver Logging, create a filter to view only Compute Engine logs.
2. Click Create Export.
3. Choose BigQuery as Sink Service, and the platform-logsdataset as Sink Destination.

Answer: D

NEW QUESTION # 146
......

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