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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

Section	Objectives
Optimize performance and continuous delivery	- Monitoring and observability 1. Cloud Monitoring and Logging 2. Performance tuning and feedback loops - System performance optimization 1. Scaling strategies and load handling
Implement site reliability engineering (SRE) practices	- Incident management and postmortems 1. Alerting and on-call practices - Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies
Develop and implement CI/CD pipelines	- Build and manage CI/CD pipelines using Google Cloud tools 1. Artifact repository management 2. Cloud Build pipeline design - Automate build, test, and deployment processes 1. Release management practices 2. Deployment automation strategies
Implement security and compliance	- Secure CI/CD pipelines 1. IAM and least privilege access 2. Secret and credential management - Compliance and governance 1. Audit logging and policy enforcement

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q182-Q187):

NEW QUESTION # 182
Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third partiesare able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible What should you do?

A. * Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that thirdparties can upload batches of data and provide appropriate credentials to the server* Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
B. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data* Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing
C. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket* Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
D. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data* Stop the processing service when there are no batches of data to process

Answer: C

NEW QUESTION # 183
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?

A. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
B. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
C. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
D. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.

Answer: C

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter
/README.md
Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload.https://cloud.google.com
/kubernetes-engine/docs/concepts/custom-and-external-metrics

NEW QUESTION # 184
Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs and you must ensure that the Ops Agent remains up to date. What should you do?

A. Select all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard Then select Install agents
B. Use the gcloud CLI to create an Agent Policy.
C. Use the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory
D. Install the Ops Agent on the Compute Engine image by using a startup script

Answer: B

NEW QUESTION # 185
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. You want to prevent these fields from being written in new log entries as quickly as possible. What should you do?

A. Stage log entries to Cloud Storage, and then trigger a Cloud Function to remove the fields and write the entries to Stackdriver via the Stackdriver Logging API.
B. Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.
C. Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.
D. Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.

Answer: B

NEW QUESTION # 186
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
B. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
D. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.

Answer: C

NEW QUESTION # 187
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