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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q180-Q185):

NEW QUESTION # 180
You support an application deployed on Compute Engine. The application connects to a Cloud SQL instance to store and retrieve dat a. After an update to the application, users report errors showing database timeout messages. The number of concurrent active users remained stable. You need to find the most probable cause of the database timeout. What should you do?

A. Use Stackdriver Profiler to visualize the resources utilization throughout the application.
B. Use Cloud Security Scanner to see whether your Cloud SQL is under a Distributed Denial of Service (DDoS) attack.
C. Check the serial port logs of the Compute Engine instance.
D. Determine whether there is an increased number of connections to the Cloud SQL instance.

Answer: D

NEW QUESTION # 181
You are building and running client applications in Cloud Run and Cloud Functions Your client requires that all logs must be available for one year so that the client can import the logs into their logging service You must minimize required code changes What should you do?

A. Update all images in Cloud Run and all functions in Cloud Functions to send logs to both Cloud Logging andthe client's logging service Ensure that all the ports required to send logs are open in the VPC firewall
B. Create a storage bucket and appropriate VPC firewall rules Update all images in Cloud Run and allfunctions in Cloud Functions to send logs to a file within the storage bucket
C. Create a Pub/Sub topic subscription and logging sink Configure the logging sink to send all logs into thetopic Give your client access to the topic to retrieve the logs
D. Create a logs bucket and logging sink. Set the retention on the logs bucket to 365 days Configure thelogging sink to send logs to the bucket Give your client access to the bucket to retrieve the logs

Answer: D

NEW QUESTION # 182
You are running an application in a virtual machine (VM) using a custom Debian image. The image has the Stackdriver Logging agent installed. The VM has the cloud-platform scope. The application is logging information via syslog. You want to use Stackdriver Logging in the Google Cloud Platform Console to visualize the logs. You notice that syslog is not showing up in the "All logs" dropdown list of the Logs Viewer. What is the first thing you should do?

A. Look for the agent's test log entry in the Logs Viewer.
B. Verify the VM service account access scope includes the monitoring.write scope.
C. Install the most recent version of the Stackdriver agent.
D. SSH to the VM and execute the following commands on your VM: ps ax I grep fluentd

Answer: D

NEW QUESTION # 183
You support an application running on App Engine. The application is used globally and accessed from various device types. You want to know the number of connections. You are using Stackdriver Monitoring for App Engine. What metric should you use?

A. tcp_ssl_proxy/new_connections
B. tcp_ssl_proxy/open_connections
C. (lex/jnstance/connections/current
D. flex/connections/current

Answer: D

NEW QUESTION # 184
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. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
B. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.
C. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.
D. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.

Answer: A

Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/tutorials/autoscaling-metrics The Google Cloud HTTP Load Balancer (GCLB) provides metrics on the number of requests and the response latency for each backend service. These metrics can be used as custom metrics for the horizontal pod autoscaler (HPA) to scale the deployment based on the load. This is the correct solution to use an appropriate SLI for scaling.

NEW QUESTION # 185
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