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

Section	Objectives
Topic 1: Implement site reliability engineering (SRE) practices	- Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies - Incident management and postmortems 1. Alerting and on-call practices
Topic 2: Optimize performance and continuous delivery	- System performance optimization 1. Scaling strategies and load handling - Monitoring and observability 1. Cloud Monitoring and Logging 2. Performance tuning and feedback loops
Topic 3: Develop and implement CI/CD pipelines	- Build and manage CI/CD pipelines using Google Cloud tools 1. Cloud Build pipeline design 2. Artifact repository management - Automate build, test, and deployment processes 1. Release management practices 2. Deployment automation strategies
Topic 4: Implement security and compliance	- Compliance and governance 1. Audit logging and policy enforcement - Secure CI/CD pipelines 1. Secret and credential management 2. IAM and least privilege access

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q162-Q167):

NEW QUESTION # 162
Your company has a Google Cloud resource hierarchy with folders for production test and development Your cyber security team needs to review your company's Google Cloud security posture to accelerate security issue identification and resolution You need to centralize the logs generated by Google Cloud services from all projects only inside your production folder to allow for alerting and near-real time analysis. What should you do?

A. Create an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination
B. Enable the Workflows API and route all the logs to Cloud Logging
C. Create a central Cloud Monitoring workspace and attach all related projects
D. Create an aggregated log sink associated with the production folder that uses a Pub Sub topic as the destination

Answer: A

Explanation:
Explanation
The best option for centralizing the logs generated by Google Cloud services from all projects only inside your production folder is to create an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination. An aggregated log sink is a log sink that collects logs from multiple sources, such as projects, folders, or organizations. A Cloud Logging bucket is a storage location for logs that can be used as a destination for log sinks. By creating an aggregated log sink with a Cloud Logging bucket, you can collect and store all the logs from the production folder in one place and allow for alerting and near-real time analysis using Cloud Monitoring and Cloud Operations.

NEW QUESTION # 163
You support a user-facing web application. When analyzing the application's error budget over the previous six months, you notice that the application has never consumed more than 5% of its error budget in any given time window. You hold a Service Level Objective (SLO) review with business stakeholders and confirm that the SLO is set appropriately. You want your application's SLO to more closely reflect its observed reliability.
What steps can you take to further that goal while balancing velocity, reliability, and business needs? (Choose two.)

A. Tighten the SLO match the application's observed reliability.
B. Add more serving capacity to all of your application's zones.
C. Implement and measure additional Service Level Indicators (SLIs) fro the application.
D. Have more frequent or potentially risky application releases.
E. Announce planned downtime to consume more error budget, and ensure that users are not depending on a tighter SLO.

Answer: C,E

Explanation:
https://sre.google/sre-book/service-level-objectives/
You want the application's SLO to more closely reflect it's observed reliability. The key here is error budget never goes over 5%. This means they can have additional downtime and still stay within their budget.

NEW QUESTION # 164
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?

A. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.
B. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
C. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.
D. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.

Answer: C

NEW QUESTION # 165
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to the production environment. A recent security audit alerted your team that the code pushed to production could contain vulnerabilities and that the existing tooling around virtual machine (VM) vulnerabilities no longer applies to the containerized environment. You need to ensure the security and patch level of all code running through the pipeline. What should you do?

A. Implement static code analysis tooling against the Docker files used to create the containers.
B. Reconfigure the existing operating system vulnerability software to exist inside the container.
C. Set up Container Analysis to scan and report Common Vulnerabilities and Exposures.
D. Configure the containers in the build pipeline to always update themselves before release.

Answer: A

NEW QUESTION # 166
Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members.
What should you do?

A. Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.
B. Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member's computer. Organize files with a naming convention that identifies each new version.
C. Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.
D. Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.

Answer: A

Explanation:
https://www.terraform.io/docs/cloud/guides/recommended-practices/part3.3.html

NEW QUESTION # 167
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