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Google Professional-Cloud-DevOps-Engineer ist eine Zertifizierungsprüfung, die speziell für die Validierung der Fähigkeiten und Kenntnisse von Fachleuten im Bereich cloud-basierter DevOps-Engineering konzipiert ist. Die Prüfung richtet sich an Personen, die Erfahrung in der Verwaltung und Bereitstellung von Anwendungen auf der Google Cloud Platform (GCP) haben. Die Zertifizierungsprüfung konzentriert sich darauf, die Fähigkeit des Kandidaten zur Gestaltung, Entwicklung und Verwaltung einer robusten cloud-basierten DevOps-Umgebung mithilfe von GCP-Services und -Tools zu bewerten.

Die Google Professional-Cloud-Devops-Engineer-Zertifizierung wird in der Branche hoch geschätzt und als Zeichen der Exzellenz im Bereich Cloud-basierter DevOps anerkannt. Diese Zertifizierung ist ideal für Fachleute, die ihre Karriere in DevOps und Cloud Computing vorantreiben möchten und die an der Zusammenarbeit mit Google Cloud -Technologien interessiert sind. Durch den Erwerb dieser Zertifizierung können Fachleute ihre Fähigkeit demonstrieren, DevOps -Workflows in Google Cloud zu entwerfen, zu implementieren und zu verwalten, und ihre Glaubwürdigkeit bei Arbeitgebern und Kunden gleichermaßen verbessern.

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Die Professional-Cloud-Devops-Engineer-Zertifizierungsprüfung ist eine der Google Cloud-Zertifizierungsprüfungen, die die Fähigkeiten und das Fachwissen einer Person in Google Cloud-Technologien validieren sollen. Die Prüfung deckt eine Reihe von Themen ab, einschließlich kontinuierlicher Integration und Lieferung, Überwachung und Protokollierung, Site -Zuverlässigkeits -Engineering, Sicherheit und Compliance sowie vielem mehr.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Professional-Cloud-DevOps-Engineer Prüfungsfragen mit Lösungen (Q117-Q122):

117. Frage
Your development team has created a new version of their service's API. You need to deploy the new versions of the API with the least disruption to third-party developers and end users of third-party installed applications. What should you do?

Antwort: A


118. Frage
Your company is creating a new cloud-native Google Cloud organization. You expect this Google Cloud organization to first be used by a small number of departments and then expand to be used by a large number of departments. Each department has a large number of applications varying in size. You need to design the VPC network architecture. Your solution must minimize the amount of management required while remaining flexible enough for development teams to quickly adapt to their evolving needs. What should you do?

Antwort: A


119. Frage
You are building the Cl/CD pipeline for an application deployed to Google Kubernetes Engine (GKE) The application is deployed by using a Kubernetes Deployment, Service, and Ingress The application team asked you to deploy the application by using the blue'green deployment methodology You need to implement the rollback actions What should you do?

Antwort: C


120. Frage
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?

Antwort: C

Begründung:
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


121. Frage
Your Cloud Run application writes unstructured logs as text strings to Cloud Logging. You want to convert the unstructured logs to JSON-based structured logs. What should you do?

Antwort: C

Begründung:
The correct answer is D. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPayload field.
Cloud Logging SDKs are libraries that allow you to write structured logs from your Cloud Run application.
You can use the SDKs to create log entries with a jsonPayload field, which contains a JSON object with the properties of your log entry.The jsonPayload field allows you to use advanced features of Cloud Logging, such as filtering, querying, and exporting logs based on the properties of your log entry1.
To use Cloud Logging SDKs, you need to install the SDK for your programming language, and then use the SDK methods to create and send log entries to Cloud Logging.For example, if you are using Node.js, you can use the following code to write a structured log entry with a jsonPayload field2:
// Imports the Google Cloud client library
const {Logging} = require('@google-cloud/logging');
// Creates a client
const logging = new Logging();
// Selects the log to write to
const log = logging.log('my-log');
// The data to write to the log
const text = 'Hello, world!';
const metadata = {
// Set the Cloud Run service name and revision as labels
labels: {
service_name: process.env.K_SERVICE || 'unknown',
revision_name: process.env.K_REVISION || 'unknown',
},
// Set the log entry payload type and value
jsonPayload: {
message: text,
timestamp: new Date(),
},
};
// Prepares a log entry
const entry = log.entry(metadata);
// Writes the log entry
await log.write(entry);
console.log(`Logged: ${text}`);
Using Cloud Logging SDKs is the best way to convert unstructured logs to structured logs, as it provides more flexibility and control over the format and content of your log entries.
Using a Fluent Bit sidecar container is not a good option, as it adds complexity and overhead to your Cloud Run application.Fluent Bit is a lightweight log processor and forwarder that can be used to collect and parse logs from various sources and send them to different destinations3. However, Cloud Run does not support sidecar containers, so you would need to run Fluent Bit as part of your main container image. This would require modifying your Dockerfile and configuring Fluent Bit to read logs from supported locations and parse them as JSON. This is more cumbersome and less reliable than using Cloud Logging SDKs.
Using the log agent in the Cloud Run container image is not possible, as the log agent is not supported on Cloud Run. The log agent is a service that runs on Compute Engine or Google Kubernetes Engine instances and collects logs from various applications and system components. However, Cloud Run does not allow you to install or run any agents on its underlying infrastructure, as it is a fully managed service that abstracts away the details of the underlying platform.
Storing the password directly in the code is not a good practice, as it exposes sensitive information and makes it hard to change or rotate the password. It also requires rebuilding and redeploying the application each time the password changes, which adds unnecessary work and downtime.
References:
1:Writing structured logs | Cloud Run Documentation | Google Cloud
2:Write structured logs | Cloud Run Documentation | Google Cloud
3: Fluent Bit - Fast and Lightweight Log Processor & Forwarder
Logging Best Practices for Serverless Applications - Google Codelabs
About the logging agent | Cloud Logging Documentation | Google Cloud
Cloud Run FAQ | Google Cloud


122. Frage
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