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

Section	Weight	Objectives
Topic 1: Bootstrapping and maintaining a Google Cloud organization	20%	- Set up governance and compliance 1. Manage resource quotas and limits 2. Configure audit logging and monitoring 3. Implement organization policies - Manage configuration and deployment 1. Use Infrastructure as Code tools 2. Automate resource provisioning 3. Enforce consistency across environments - Design resource hierarchy 1. Plan shared networking and connectivity 2. Define IAM policies and access control 3. Organize resources by project/folder/application
Topic 2: Building and implementing CI/CD pipelines	25%	- Implement and secure pipelines 1. Manage pipeline secrets and credentials 2. Enforce security scanning and compliance checks 3. Automate build, test, and deployment stages - Design CI/CD pipelines 1. Plan pipelines for apps, infrastructure, ML workloads 2. Support hybrid/multi-cloud deployment 3. Integrate artifact management - Optimize and maintain pipelines 1. Handle rollbacks and versioning 2. Improve speed and reliability 3. Monitor pipeline performance
Topic 3: Optimizing performance and cost	17%	- Balance cost, performance, and reliability 1. Make tradeoff decisions based on data 2. Optimize over time 3. Plan capacity and scaling - Apply FinOps practices 1. Use spot instances and committed use discounts 2. Right-size resources and eliminate waste 3. Monitor and analyze cloud costs - Improve system performance 1. Use caching and content delivery 2. Optimize resource allocation 3. Tune applications and infrastructure
Topic 4: 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. Establish SLIs, SLOs, SLAs 2. Use error budgets to balance change and stability 3. Align reliability with business needs - Design for resilience 1. Test failure scenarios and recovery 2. Plan redundancy and fault tolerance 3. Automate remediation and self-healing
Topic 5: Implementing observability and troubleshooting	20%	- Build monitoring and logging systems 1. Collect and analyze metrics, logs, traces 2. Use Cloud Monitoring, Cloud Logging, Cloud Trace 3. Create dashboards and alerts - Troubleshoot complex issues 1. Trace requests end-to-end 2. Isolate problems across layers 3. Analyze performance and latency - Optimize observability strategy 1. Reduce noise and prioritize signals 2. Scale monitoring for large environments 3. Integrate observability into development

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q59-Q64):

NEW QUESTION # 59
You need to enforce several constraint templates across your Google Kubernetes Engine (GKE) clusters. The constraints include policy parameters, such as restricting the Kubernetes API. You must ensure that the policy parameters are stored in a GitHub repository and automatically applied when changes occur. What should you do?

A. Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.
B. Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.
C. Set up a GitHub action to trigger Cloud Build when there is a parameter change. In Cloud Build, run a gcloud CLI command to apply the change.
D. When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.

Answer: A

NEW QUESTION # 60
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

A. Disable the CI pipeline and revert to manually building and pushing the artifacts.
B. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
C. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
D. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.

Answer: B

NEW QUESTION # 61
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. * 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 the IAM Object Viewer access to view the logs in the specified bucket.
B. * 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.
C. * Deploy the Stackdriver monitoring agent to the application servers.
* Give the developers the IAM Monitoring Viewer role to access Stackdriver and view metrics.
D. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Viewer role to access Stackdriver and view logs.

Answer: B

NEW QUESTION # 62
Your company follows Site Reliability Engineering practices. You are the person in charge of Communications for a large, ongoing incident affecting your customer-facing applications. There is still no estimated time for a resolution of the outage. You are receiving emails from internal stakeholders who want updates on the outage, as well as emails from customers who want to know what is happening. You want to efficiently provide updates to everyone affected by the outage. What should you do?

A. Focus on responding to internal stakeholders at least every 30 minutes. Commit to "next update" times.
B. Provide all internal stakeholder emails to the Incident Commander, and allow them to manage internal communications. Focus on providing responses directly to customers.
C. Delegate the responding to internal stakeholder emails to another member of the Incident Response Team. Focus on providing responses directly to customers.
D. Provide periodic updates to all stakeholders in a timely manner. Commit to a "next update" time in all communications.

Answer: D

Explanation:
When disaster strikes, the person who declares the incident typically steps into the IC role and directs the high-level state of the incident. The IC concentrates on the 3Cs and does the following: Commands and coordinates the incident response, delegating roles as needed. By default, the IC assumes all roles that have not been delegated yet. Communicates effectively. Stays in control of the incident response. Works with other responders to resolve the incident. https://sre.google/workbook/incident-response/

NEW QUESTION # 63
As a Site Reliability Engineer, you support an application written in GO that runs on Google Kubernetes Engine (GKE) in production. After releasing a new version Of the application, you notice the application runs for about 15 minutes and then restarts. You decide to add Cloud Profiler to your application and now notice that the heap usage grows constantly until the application restarts. What should you do?

A. Increase the CPU limit in the application deployment.
B. Add high memory compute nodes to the cluster.
C. Increase the memory limit in the application deployment.
D. Add Cloud Trace to the application, and redeploy.

Answer: C

Explanation:
The correct answer is B, Increase the memory limit in the application deployment.
The application is experiencing a memory leak, which means that it is allocating memory that is not freed or reused. This causes the heap usage to grow constantly until it reaches the memory limit of the pod, which triggers a restart by Kubernetes. Increasing the memory limit in the application deployment can help mitigate the problem by allowing the application to run longer before reaching the limit. However, this is not a permanent solution, as the memory leak will still occur and eventually exhaust the available memory. The best solution is to identify and fix the source of the memory leak in the application code, using tools like Cloud Profiler and pprof12.
Reference:
Using Cloud Profiler with Go, Troubleshooting memory leaks. Profiling Go Programs, Heap profiles.

NEW QUESTION # 64
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