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

Section	Weight	Objectives
Building and implementing CI/CD pipelines	25%	- Optimize and maintain pipelines 1. Handle rollbacks and versioning 2. Monitor pipeline performance 3. Improve speed and reliability - Implement and secure pipelines 1. Enforce security scanning and compliance checks 2. Manage pipeline secrets and credentials 3. Automate build, test, and deployment stages - Design CI/CD pipelines 1. Integrate artifact management 2. Support hybrid/multi-cloud deployment 3. Plan pipelines for apps, infrastructure, ML workloads
Implementing observability and troubleshooting	20%	- Build monitoring and logging systems 1. Use Cloud Monitoring, Cloud Logging, Cloud Trace 2. Collect and analyze metrics, logs, traces 3. Create dashboards and alerts - Troubleshoot complex issues 1. Analyze performance and latency 2. Isolate problems across layers 3. Trace requests end-to-end - Optimize observability strategy 1. Reduce noise and prioritize signals 2. Scale monitoring for large environments 3. Integrate observability into development
Bootstrapping and maintaining a Google Cloud organization	20%	- Manage configuration and deployment 1. Automate resource provisioning 2. Enforce consistency across environments 3. Use Infrastructure as Code tools - Set up governance and compliance 1. Manage resource quotas and limits 2. Implement organization policies 3. Configure audit logging and monitoring - Design resource hierarchy 1. Organize resources by project/folder/application 2. Plan shared networking and connectivity 3. Define IAM policies and access control
Optimizing performance and cost	17%	- Apply FinOps practices 1. Monitor and analyze cloud costs 2. Use spot instances and committed use discounts 3. Right-size resources and eliminate waste - Improve system performance 1. Tune applications and infrastructure 2. Use caching and content delivery 3. Optimize resource allocation - Balance cost, performance, and reliability 1. Make tradeoff decisions based on data 2. Plan capacity and scaling 3. Optimize over time
Applying site reliability engineering practices	18%	- Manage incidents and outages 1. Detect and respond to issues quickly 2. Implement improvements to prevent recurrence 3. Perform postmortems and root cause analysis - Define reliability goals 1. Use error budgets to balance change and stability 2. Align reliability with business needs 3. Establish SLIs, SLOs, SLAs - Design for resilience 1. Test failure scenarios and recovery 2. Plan redundancy and fault tolerance 3. Automate remediation and self-healing

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q31-Q36):

NEW QUESTION # 31
You are running an experiment to see whether your users like a new feature of a web application. Shortly after deploying the feature as a canary release, you receive a spike in the number of 500 errors sent to users, and your monitoring reports show increased latency. You want to quickly minimize the negative impact on users.
What should you do first?

A. Start monitoring latency, traffic, errors, and saturation.
B. Trace the origin of 500 errors and the root cause of increased latency.
C. Roll back the experimental canary release.
D. Record data for the postmortem document of the incident.

Answer: C

NEW QUESTION # 32
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?

A. Create a new service account with the Container Developer role and use it to run Cloud Build.
B. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
C. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
D. Assign the Container Developer role to the Cloud Build service account.

Answer: D

Explanation:
https://cloud.google.com/build/docs/deploying-builds/deploy-gke
https://cloud.google.com/build/docs/securing-builds/configure-user-specified-service-accounts

NEW QUESTION # 33
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead. What should you do?

A. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.
B. Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
C. Configure Cloud Profiler, and initialize the cloud.go@gle.com/go/profiler library in the application.
D. Use Cloud Monitoring to assess the App Engine CPU utilization metric.

Answer: C

NEW QUESTION # 34
You need to deploy a new service to production. The service needs to automatically scale using a Managed Instance Group (MIG) and should be deployed over multiple regions. The service needs a large number of resources for each instance and you need to plan for capacity. What should you do?

A. Deploy the service in one region and use a global load balancer to route traffic to this region.
B. Monitor results of Stackdriver Trace to determine the required amount of resources.
C. Use the n1-highcpu-96 machine type in the configuration of the MIG.
D. Validate that the resource requirements are within the available quota limits of each region.

Answer: A

NEW QUESTION # 35
You have a pool of application servers running on Compute Engine. You need to provide a secure solution that requires the least amount of configuration and allows developers to easily access application logs for troubleshooting. How would you implement the solution on GCP?

A. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Private Logs Viewer role to access Stackdriver and view logs.
B. * Install the gsutil command line tool on your application servers.
* Write a script using gsutil to upload your application log to a Cloud Storage bucket, and then schedule it to run via cron every 5 minutes.
* Give the developers IAM Object Viewer access to view the logs in the specified bucket.
C. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Viewer role to access Stackdriver and view logs.
D. * Deploy the Stackdriver monitoring agent to the application servers.
* Give the developers the IAM Monitoring Viewer role to access Stackdriver and view metrics.

Answer: A

NEW QUESTION # 36
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