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

Section	Weight	Objectives
Topic 1: Implementing observability and troubleshooting	20%	- Troubleshoot complex issues 1. Trace requests end-to-end 2. Analyze performance and latency 3. Isolate problems across layers - Optimize observability strategy 1. Integrate observability into development 2. Reduce noise and prioritize signals 3. Scale monitoring for large environments - 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
Topic 2: Building and implementing CI/CD pipelines	25%	- Implement and secure pipelines 1. Enforce security scanning and compliance checks 2. Manage pipeline secrets and credentials 3. Automate build, test, and deployment stages - Optimize and maintain pipelines 1. Improve speed and reliability 2. Monitor pipeline performance 3. Handle rollbacks and versioning - Design CI/CD pipelines 1. Integrate artifact management 2. Plan pipelines for apps, infrastructure, ML workloads 3. Support hybrid/multi-cloud deployment
Topic 3: Optimizing performance and cost	17%	- Improve system performance 1. Optimize resource allocation 2. Use caching and content delivery 3. Tune applications and infrastructure - Apply FinOps practices 1. Monitor and analyze cloud costs 2. Right-size resources and eliminate waste 3. Use spot instances and committed use discounts - Balance cost, performance, and reliability 1. Plan capacity and scaling 2. Optimize over time 3. Make tradeoff decisions based on data
Topic 4: Applying site reliability engineering practices	18%	- Design for resilience 1. Plan redundancy and fault tolerance 2. Test failure scenarios and recovery 3. Automate remediation and self-healing - Define reliability goals 1. Establish SLIs, SLOs, SLAs 2. Align reliability with business needs 3. Use error budgets to balance change and stability - Manage incidents and outages 1. Implement improvements to prevent recurrence 2. Perform postmortems and root cause analysis 3. Detect and respond to issues quickly
Topic 5: Bootstrapping and maintaining a Google Cloud organization	20%	- Manage configuration and deployment 1. Automate resource provisioning 2. Use Infrastructure as Code tools 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 - Set up governance and compliance 1. Manage resource quotas and limits 2. Configure audit logging and monitoring 3. Implement organization policies

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q138-Q143):

NEW QUESTION # 138
You manage an application that is writing logs to Stackdriver Logging. You need to give some team members the ability to export logs. What should you do?

A. Grant the team members the IAM role of logging.configWriter on Cloud IAM.
B. Configure Access Context Manager to allow only these members to export logs.
C. Create an Organizational Policy in Cloud IAM to allow only these members to create log exports.
D. Create and grant a custom IAM role with the permissions logging.sinks.list and logging.sink.get.

Answer: A

Explanation:
Explanation/Reference: https://cloud.google.com/logging/docs/access-control

NEW QUESTION # 139
You support a web application that runs on App Engine and uses CloudSQL and Cloud Storage for data storage. After a short spike in website traffic, you notice a big increase in latency for all user requests, increase in CPU use, and the number of processes running the application. Initial troubleshooting reveals:
After the initial spike in traffic, load levels returned to normal but users still experience high latency.
Requests for content from the CloudSQL database and images from Cloud Storage show the same high latency.
No changes were made to the website around the time the latency increased.
There is no increase in the number of errors to the users.
You expect another spike in website traffic in the coming days and want to make sure users don't experience latency. What should you do?

A. Enable high availability on the CloudSQL instances.
B. Modify the App Engine configuration to have additional idle instances.
C. Move the application from App Engine to Compute Engine.
D. Upgrade the GCS buckets to Multi-Regional.

Answer: A

NEW QUESTION # 140
Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third parties are able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible What should you do?

A. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket
* Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data
* Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing
B. * Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that third parties can upload batches of data and provide appropriate credentials to the server
* Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group
* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
C. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket
* Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group
* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
D. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket
* Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data
* Stop the processing service when there are no batches of data to process

Answer: C

Explanation:
The best option for ensuring that third parties are able to upload their data securely and minimizing costs while ensuring that the data is processed as quickly as possible is to provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (IAM) access to the bucket; create a Cloud Function with a google.storage.object.finalize Cloud Storage trigger; write code so that the function can scale up a Compute Engine autoscaling managed instance group; use an image pre-loaded with the data processing software that terminates the instances when processing completes. A Cloud Storage bucket is a resource that allows you to store and access data in Google Cloud. You can provide a Cloud Storage bucket so that third parties can upload batches of data securely and conveniently. You can also provide appropriate IAM access to the bucket by using roles and policies to control who can read or write data to the bucket. A Cloud Function is a serverless function that executes code in response to an event, such as a change in a Cloud Storage bucket. A google.storage.object.finalize trigger is a type of trigger that fires when a new object is created or an existing object is overwritten in a Cloud Storage bucket. You can create a Cloud Function with a google.storage.object.finalize trigger so that the function runs whenever a new batch of data is uploaded to the bucket. You can write code so that the function can scale up a Compute Engine autoscaling managed instance group, which is a group of VM instances that automatically adjusts its size based on load or custom metrics. You can use an image pre-loaded with the data processing software that terminates the instances when processing completes, which means that the instances only run when there is data to process and stop when they are done. This way, you can minimize costs while ensuring that the data is processed as quickly as possible.

NEW QUESTION # 141
Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs and you must ensure that the Ops Agent remains up to date. What should you do?

A. Use the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory
B. Install the Ops Agent on the Compute Engine image by using a startup script
C. Use the gcloud CLI to create an Agent Policy.
D. Select all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard Then select Install agents

Answer: C

Explanation:
The best option for configuring all current and future Compute Engine instances to collect system logs and ensure that the Ops Agent remains up to date is to use the gcloud CLI to create an Agent Policy. An Agent Policy is a resource that defines how Ops Agents are installed and configured on VM instances that match certain criteria, such as labels or zones. Ops Agents are software agents that collect metrics and logs from VM instances and send them to Cloud Operations products, such as Cloud Monitoring and Cloud Logging. By creating an Agent Policy, you can ensure that all current and future VM instances that match the policy criteria will have the Ops Agent installed and updated automatically. This way, you can collect system logs from all VM instances and use them to generate dashboards in Cloud Operations.

NEW QUESTION # 142
You created a Stackdriver chart for CPU utilization in a dashboard within your workspace project. You want to share the chart with your Site Reliability Engineering (SRE) team only. You want to ensure you follow the principle of least privilege. What should you do?

A. Share the workspace Project ID with the SRE team. Assign the SRE team the Dashboard Viewer IAM role in the workspace project.
B. Share the workspace Project ID with the SRE team. Assign the SRE team the Monitoring Viewer IAM role in the workspace project.
C. Click "Share chart by URL" and provide the URL to the SRE team. Assign the SRE team the Dashboard Viewer IAM role in the workspace project.
D. Click "Share chart by URL" and provide the URL to the SRE team. Assign the SRE team the Monitoring Viewer IAM role in the workspace project.

Answer: B

NEW QUESTION # 143
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