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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q164-Q169):

NEW QUESTION # 164
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?

A. Escalate the situation and request additional error budget.
B. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
C. Look through other metrics related to the product and find SLOs with remaining error budget.
Reallocate the error budgets and allow the feature launch.
D. Notify the team about the lack of error budget and ensure that all their tests are successful so the launch will not further risk the error budget.

Answer: B

Explanation:
The correct answer is A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1.An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users.In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices.Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.
Reference:
Error Budgets, Error Budgets.Service Level Objectives, Service Level Objectives.Error Budget Policies, Error Budget Policies.Error Budget Autonomy, Error Budget Autonomy.

NEW QUESTION # 165
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?

A. In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
B. Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
C. Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.
D. Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.

Answer: D

NEW QUESTION # 166
Your application artifacts are being built and deployed via a CI/CD pipeline. You want the CI/CD pipeline to securely access application secrets. You also want to more easily rotate secrets in case of a security breach.
What should you do?

A. Store secrets in Cloud Storage encrypted with a key from Cloud KMS. Provide the CI/CD pipeline with access to Cloud KMS via IAM.
B. Prompt developers for secrets at build time. Instruct developers to not store secrets at rest.
C. Encrypt the secrets and store them in the source code repository. Store a decryption key in a separate repository and grant your pipeline access to it.
D. Store secrets in a separate configuration file on Git. Provide select developers with access to the configuration file.

Answer: A

NEW QUESTION # 167
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

A. MTTD:5MTTR: 20MTBF: 90Impact: 33%
B. MTTD: 5MTTR: 10MTBF: 90Impact: 33%
C. MTTD:5MTTR: 20MTBF: 90Impact: 50%
D. MTTD:5MTTR: 10MTBF: 90Impact 50%

Answer: A

NEW QUESTION # 168
You are running a web application deployed to a Compute Engine managed instance group Ops Agent is installed on all instances You recently noticed suspicious activity from a specific IP address You need to configure Cloud Monitoring to view the number of requests from that specific IP address with minimal operational overhead. What should you do?

A. Configure the Ops Agent with a metrics receiver
B. Update the application to export the IP address request metrics to the Cloud Monitoring API
C. Configure the Ops Agent with a logging receiver Create a logs-based metric
D. Create a script to scrape the web server log Export the IP address request metrics to the Cloud Monitoring API

Answer: C

NEW QUESTION # 169
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