此外，這些KaoGuTi Professional-Cloud-DevOps-Engineer考試題庫的部分內容現在是免費的：https://drive.google.com/open?id=1bCdm0CSUZxtACV-_qcvNFVPayzqolEP5
在如今人才濟濟的社會中，Google專業人士是很受歡迎的，但競爭也很大。所以很多Google專業人士通過一些比較難的權威的Professional-Cloud-DevOps-Engineer認證考試來穩固自己，而我們KaoGuTi是專門為參加Professional-Cloud-DevOps-Engineer認證考試的考生提供便利的。
| Section | Objectives |
|---|---|
| Topic 1: Optimize performance and continuous delivery | - System performance optimization
|
| Topic 2: Implement site reliability engineering (SRE) practices | - Define and manage SLI, SLO, and SLA
|
| Topic 3: Develop and implement CI/CD pipelines | - Build and manage CI/CD pipelines using Google Cloud tools
|
| Topic 4: Implement security and compliance | - Compliance and governance
|
>> Professional-Cloud-DevOps-Engineer題庫最新資訊 <<
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問題 #115
Your company runs applications in Google Kubernetes Engine (GKE) that are deployed following a GitOps methodology.
Application developers frequently create cloud resources to support their applications. You want to give developers the ability to manage infrastructure as code, while ensuring that you follow Google-recommended practices. You need to ensure that infrastructure as code reconciles periodically to avoid configuration drift.
What should you do?
答案：A
解題說明：
Explanation
The best option to give developers the ability to manage infrastructure as code, while ensuring that you follow Google-recommended practices, is to install and configure Config Connector in Google Kubernetes Engine (GKE).
Config Connector is a Kubernetes add-on that allows you to manage Google Cloud resources through Kubernetes. You can use Config Connector to create, update, and delete Google Cloud resources using Kubernetes manifests. Config Connector also reconciles the state of the Google Cloud resources with the desired state defined in the manifests, ensuring that there is no configuration drift1.
Config Connector follows the GitOps methodology, as it allows you to store your infrastructure configuration in a Git repository, and use tools such as Anthos Config Management or Cloud Source Repositories to sync the configuration to your GKE cluster. This way, you can use Git as the source of truth for your infrastructure, and enable reviewable and version-controlled workflows2.
Config Connector can be installed and configured in GKE using either the Google Cloud Console or the gcloud command-line tool. You need to enable the Config Connector add-on for your GKE cluster, and create a Google Cloud service account with the necessary permissions to manage the Google Cloud resources. You also need to create a Kubernetes namespace for each Google Cloud project that you want to manage with Config Connector3.
By using Config Connector in GKE, you can give developers the ability to manage infrastructure as code, while ensuring that you follow Google-recommended practices. You can also benefit from the features and advantages of Kubernetes, such as declarative configuration, observability, and portability4.
References:
1: Overview | Artifact Registry Documentation | Google Cloud
2: Deploy Anthos on GKE with Terraform part 1: GitOps with Config Sync | Google Cloud Blog
3: Installing Config Connector | Config Connector Documentation | Google Cloud
4: Why use Config Connector? | Config Connector Documentation | Google Cloud
問題 #116
You manage your company's primary revenue-generating application. You have an error budget policy in place that freezes production deployments when the application is close to breaching its SLO. A number of issues have recently occurred, and the application has exhausted its error budget. You need to deploy a new release to the application that includes a feature urgently required by your largest customer. You have been told that the release has passed all unit tests. What should you do?
答案：B
解題說明：
Comprehensive and Detailed Explanation From SRE Principles:
This scenario presents a classic SRE conflict: maintaining reliability (as dictated by the exhausted error budget and deployment freeze) versus delivering an urgent business requirement. The error budget policy is there for a reason - to protect users from further instability.
A: Start the deployment of the feature immediately: This directly violates the established error budget policy and the deployment freeze. While the feature is urgent, deploying without caution when the system is already unstable (as indicated by the exhausted error budget) is highly risky and could exacerbate existing problems or introduce new ones, further impacting revenue and customer trust.
B: Delay the deployment of the feature until the error budget is replenished: This strictly adheres to the policy but might not be acceptable given the "urgently required by your largest customer" clause. SRE principles allow for reasoned exceptions and risk management, not just blind adherence if the business context is compelling enough and risks are managed.
C: Re-run the unit tests, and start the deployment of the feature if the tests pass: Unit tests are foundational but insufficient to guarantee a complex application will perform reliably in production, especially when the system is already indicating instability (exhausted error budget). Passing unit tests doesn't negate the risk signaled by the depleted error budget.
D: Deploy the feature to a subset of users, and gradually roll out to all users if there are no errors reported:
This is the most balanced SRE approach in this situation. It acknowledges the urgency while attempting to mitigate risk:Risk Mitigation: A canary release (deploying to a small subset of users) limits the potential negative impact if the new feature introduces new errors or worsens existing instability.
Observation: It allows for careful monitoring of the new release in the production environment with real users.
Data-Driven Decision: The decision to proceed with a wider rollout is based on observed behavior ("if there are no errors reported"), not just assumptions.
Controlled Rollout: A gradual rollout allows for quick rollback if issues arise.
While an exhausted error budget signals a deployment freeze, critical business needs can sometimes necessitate a carefully managed exception. A canary release is a standard SRE technique for deploying changes with reduced risk, making it the most appropriate course of action when faced with such conflicting priorities. The team would also need to communicate clearly about the risks and the rationale for this exception. It's implied that this urgent feature might also fix existing issues or is critical enough to warrant the carefully managed risk.
Reference (Based on SRE principles from Google's SRE books and general practices):
Error Budgets: "The SRE Book" (Site Reliability Engineering: How Google Runs Production Systems) discusses error budgets and deployment freezes. An exhausted error budget typically means no more risky changes until reliability improves.
Canary Releases: This is a fundamental practice for safely deploying new versions. It's about testing in production with a small percentage of traffic.
Managing Risk: SRE is about managing risk, not eliminating it entirely. In situations like this, a calculated risk with strong mitigation (canary, monitoring, rollback plan) can be justified for critical business needs. The decision involves weighing the risk of deploying against the risk of not deploying the urgent feature.
Option D represents a pragmatic SRE approach to navigate this difficult situation by minimizing the blast radius of the change.
問題 #117
You are creating a CI/CD pipeline in Cloud Build to build an application container image The application code is stored in GitHub Your company requires thai production image builds are only run against the main branch and that the change control team approves all pushes to the main branch You want the image build to be as automated as possible What should you do?
Choose 2 answers
答案：C,D
解題說明：
Explanation
The best options for creating a CI/CD pipeline in Cloud Build to build an application container image and ensuring that production image builds are only run against the main branch and that the change control team approves all pushes to the main branch are to create a trigger on the Cloud Build job, set the repository event setting to Push to a branch, and configure a branch protection rule for the main branch on the repository. A trigger is a resource that starts a build when an event occurs, such as a code change. By creating a trigger on the Cloud Build job and setting the repository event setting to Push to a branch, you can ensure that the image build is only run when code is pushed to a specific branch, such as the main branch. A branch protection rule is a rule that enforces certain policies on a branch, such as requiring reviews, status checks, or approvals before merging code. By configuring a branch protection rule for the main branch on the repository, you can ensure that the change control team approves all pushes to the main branch.
問題 #118
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?
答案：A
解題說明：
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter
/README.md
Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload.https://cloud.google.com
/kubernetes-engine/docs/concepts/custom-and-external-metrics
問題 #119
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?
答案：C
解題說明：
Explanation
The correct answer is A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1. An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users. In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices. Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.
問題 #120
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Professional-Cloud-DevOps-Engineer學習資料: https://www.kaoguti.com/Professional-Cloud-DevOps-Engineer_exam-pdf.html
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