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

Section	Weight	Objectives
Microservices Architecture	14%	- Container orchestration with GKE 1. Managing pod lifecycle and resource quotas 2. Designing Kubernetes cluster architectures 3. Configuring node pools and auto-scaling 4. Implementing workload deployment and scaling - Service mesh and networking 1. Configuring traffic management and load balancing 2. Implementing Anthos Service Mesh / Istio 3. Implementing service-to-service authentication - API management 1. Implementing API versioning strategies 2. Exposing APIs with Cloud Endpoints / Apigee
CI/CD Pipeline Development	26%	- CI/CD best practices 1. Configuring quality gates and code coverage 2. Managing secrets in CI/CD pipelines 3. Implementing shift-left testing - Containerization and Docker 1. Creating optimized Docker images (multi-stage builds) 2. Managing container registries 3. Implementing container security best practices - Designing and implementing CI/CD pipelines 1. Configuring build triggers and webhooks 2. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.) 3. Setting up artifact management with Artifact Registry 4. Implementing build automation scripts 5. Configuring build caching strategies
Cloud Infrastructure Automation	24%	- Deployment strategies 1. Canary releases and progressive rollouts 2. Rolling updates with Kubernetes 3. Blue-green deployments 4. Feature flags with Firebase Remote Config or LaunchDarkly - Infrastructure as Code (IaC) 1. Managing infrastructure modules and state 2. Implementing with Terraform 3. Implementing immutable infrastructure patterns - Configuration management 1. Using Ansible for configuration management 2. Managing secrets with Secret Manager 3. Implementing configuration drift detection
Reliability and Site Reliability Engineering (SRE)	24%	- Monitoring and observability 1. Implementing distributed tracing with Cloud Trace 2. Creating dashboards for service health visibility 3. Configuring Cloud Monitoring and Logging 4. Setting up alerting policies and incident management - Incident management 1. Configuring automated incident response 2. Post-incident reviews and blameless postmortems 3. Implementing on-call procedures - SLOs, SLIs, and SLAs 1. Error budget policies and management 2. Defining and implementing Service Level Objectives 3. Creating and interpreting Service Level Indicators 4. Setting appropriate Service Level Agreements
Monitoring, Logging, and Debugging	12%	- Debugging and troubleshooting 1. Analyzing performance profiles with Cloud Profiler 2. Using Cloud Debugger and Error Reporting 3. Debugging with Cloud Trace distributed tracing - Log management 1. Configuring log retention policies 2. Implementing log-based metrics 3. Structuring logs for efficient querying - Cloud Operations Suite 1. Configuring Cloud Monitoring metrics 2. Creating uptime checks and alerts 3. Implementing Cloud Logging with log sinks

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q122-Q127):

NEW QUESTION # 122
You need to create a Cloud Monitoring SLO for a service that will be published soon. You want to verify that requests to the service will be addressed in fewer than 300 ms at least 90% Of the time per calendar month.
You need to identify the metric and evaluation method to use. What should you do?

A. Select a latency metric for a window-based method of evaluation.
B. Select an availability metric for a request-based method of evaluation.
C. Select a latency metric for a request-based method of evaluation.
D. Select an availability metric for a window-based method Of evaluation.

Answer: C

Explanation:
Explanation
The correct answer is A. Select a latency metric for a request-based method of evaluation.
A latency metric measures how responsive your service is to users. For example, you can use the cloud.googleapis.com/http/server/response_latencies metric to measure the latency of HTTP requests to your service1. A request-based method of evaluation counts the number of successful requests that meet a certain criterion, such as being below a latency threshold, and compares it to the number of all requests. For example, you can define an SLI as the ratio of requests with latency below 300 ms to all requests2. A request-based method of evaluation is suitable for measuring performance over time, such as per calendar month. You can set an SLO for the SLI to be at least 90%, which means that you expect 90% of the requests to have latency below 300 ms in a month3.

NEW QUESTION # 123
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

A. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.
B. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.
C. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
D. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.

Answer: D

NEW QUESTION # 124
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using a CI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message

You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?

A. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
B. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
C. Delete the managed instance group and recreate it after updating the instance template
D. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template

Answer: B

Explanation:
Explanation
The best option for updating the instance template and minimizing disruption to the application and the number of pipeline runs is to set the create_before_destroy meta-argument to true in the lifecycle block on the instance template. The create_before_destroy meta-argument is a Terraform feature that specifies that a new resource should be created before destroying an existing one during an update. This way, you can avoid downtime and errors when updating a resource that is in use by another resource, such as an instance template that is used by a managed instance group. By setting the create_before_destroy meta-argument to true in the lifecycle block on the instance template, you can ensure that Terraform creates a new instance template with the updated machine type, updates the managed instance group to use the new instance template, and then deletes the old instance template.

NEW QUESTION # 125
Your company runs services on Google Cloud. Each team runs their applications in a dedicated project. New teams and projects are created regularly. Your security team requires that all logs are processed by a security information and event management (SIEM) system. The SIEM ingests logs by using Pub/Sub. You must ensure that all existing and future logs are scanned by the SIEM. What should you do?

A. Create a project-level logging sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs. Repeat for each project.
B. Create a folder-level aggregated sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs. Repeat for each folder.
C. Create an organization-level aggregated sink with a SIEM log bucket as the destination. Set an inclusion filter to include all logs.
D. Create an organization-level aggregated sink with a SIEM Pub/Sub topic as the destination. Set an inclusion filter to include all logs.

Answer: D

NEW QUESTION # 126
You are responsible for creating and modifying the Terraform templates that define your Infrastructure. Because two new engineers will also be working on the same code, you need to define a process and adopt a tool that will prevent you from overwriting each other's code. You also want to ensure that you capture all updates in the latest version. What should you do?

A. * Store your code as text files in Google Drive in a defined folder structure that organizes the files.
* At the end of each day. confirm that all changes have been captured in the files within the folder structure.
* Rename the folder structure with a predefined naming convention that increments the version.
B. * Store your code in a Git-based version control system.
* Establish a process that allows developers to merge their own changes at the end of each day.
* Package and upload code lo a versioned Cloud Storage bucket as the latest master version.
C. * Store your code as text files in Google Drive in a defined folder structure that organizes the files.
* At the end of each day, confirm that all changes have been captured in the files within the folder structure and create a new .zip archive with a predefined naming convention.
* Upload the .zip archive to a versioned Cloud Storage bucket and accept it as the latest version.
D. * Store your code in a Git-based version control system.
* Establish a process that includes code reviews by peers and unit testing to ensure integrity and functionality before integration of code.
* Establish a process where the fully integrated code in the repository becomes the latest master version.

Answer: B

NEW QUESTION # 127
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