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

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Exam Professional-Cloud-DevOps-Engineer Objectives Pdf - 100% Useful Questions Pool

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q201-Q206):

NEW QUESTION # 201
You encounter a large number of outages in the production systems you support. You receive alerts for all the outages that wake you up at night. The alerts are due to unhealthy systems that are automatically restarted within a minute. You want to set up a process that would prevent staff burnout while following Site Reliability Engineering practices. What should you do?

A. Eliminate unactionable alerts.
B. Distribute the alerts to engineers in different time zones.
C. Create an incident report for each of the alerts.
D. Redefine the related Service Level Objective so that the error budget is not exhausted.

Answer: A

Explanation:
Eliminate bad monitoring : Unactionable alerts (i.e., spam)https://cloud.google.com/blog/products
/management-tools/meeting-reliability-challenges-with-sre-principles
agree with kyubiblaze about having to remove unactionable items aka spam: "good monitoring alerts on actionable problems" @https://cloud.google.com/blog/products/management-tools/meeting-reliability- challenges-with-sre-principles

NEW QUESTION # 202
You are monitoring a service that uses n2-standard-2 Compute Engine instances that serve large files. Users have reported that downloads are slow. Your Cloud Monitoring dashboard shows that your VMS are running at peak network throughput. You want to improve the network throughput performance. What should you do?

A. Deploy a Cloud NAT gateway and attach the gateway to the subnet of the VMS.
B. Change the machine type for your VMS to n2-standard-8.
C. Add additional network interface controllers (NICs) to your VMS.
D. Deploy the Ops Agent to export additional monitoring metrics.

Answer: B

Explanation:
Explanation
The correct answer is C. Change the machine type for your VMs to n2-standard-8.
According to the Google Cloud documentation, the network throughput performance of a Compute Engine VM depends on its machine type1. The n2-standard-2 machine type has a maximum egress bandwidth of 4 Gbps, which can be a bottleneck for serving large files. By changing the machine type to n2-standard-8, you can increase the maximum egress bandwidth to 16 Gbps, which can improve the network throughput performance and reduce the download time for users. You also need to enable per VM Tier_1 networking performance, which is a feature that allows VMs to achieve higher network performance than the default settings2.
The other options are incorrect because they do not improve the network throughput performance of your VMs. Option A is incorrect because Cloud NAT is a service that allows private IP addresses to access the internet, but it does not increase the network bandwidth or speed3. Option B is incorrect because adding additional network interfaces (NICs) or IP addresses per NIC does not increase ingress or egress bandwidth for a VM1. Option D is incorrect because deploying the Ops Agent can help you monitor and troubleshoot your VMs, but it does not affect the network throughput performance4.

NEW QUESTION # 203
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.
What should you do?

A. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
B. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
C. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
D. Publish various metrics from the application directly to the Stackdriver Monitoring API, and then observe these custom metrics in Stackdriver.

Answer: B

NEW QUESTION # 204
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. Upgrade the GCS buckets to Multi-Regional.
B. Enable high availability on the CloudSQL instances.
C. Move the application from App Engine to Compute Engine.
D. Modify the App Engine configuration to have additional idle instances.

Answer: B

NEW QUESTION # 205
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. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
B. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
C. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
D. Delete the managed instance group and recreate it after updating the instance template

Answer: C

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 # 206
......

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