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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified - Professional Cloud DevOps Engineer |
| Exam Number: | Professional-Cloud-DevOps-Engineer |
| Available Languages: | Japanese, English, Spanish, Portuguese (Brazil) |
| Passing Score: | Not officially disclosed |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | Approximately 50–60 |
| Exam Price: | $200 USD |
| Related Certifications: | Google Cloud Certified - Professional Cloud Security Engineer Google Cloud Certified - Professional Cloud Network Engineer Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Associate Cloud Engineer |
| Exam Format: | Multiple choice, Multiple select |
| Exam Duration: | 120 minutes |
| Recommended Training: | Google Cloud Skills Boost - DevOps Engineer Path Coursera Google Cloud DevOps Engineering Courses |
| Exam Registration: | Kryterion Webassessor Registration Google Cloud Certification Portal |
| Sample Questions: | Google Professional-Cloud-DevOps-Engineer Sample Questions |
| Exam Way: | Online proctored or test center (Kryterion/Webassessor) |
| Pre Condition: | No formal prerequisites. Recommended: 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud. |
| Official Syllabus URL: | https://cloud.google.com/certification/cloud-devops-engineer |
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Google Professional-Cloud-DevOps-Engineer exam is an essential certification for professionals who want to develop their skills in cloud-based DevOps engineering. Professional-Cloud-DevOps-Engineer exam covers various aspects of infrastructure deployment, automation, monitoring, and optimization, and tests the candidate's ability to design, develop, and manage cloud-based solutions using best practices and industry standards. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is highly valued in the industry and can lead to better career opportunities and higher salaries.
The Google Professional-Cloud-DevOps-Engineer Exam consists of multiple-choice and multiple-select questions, and it is conducted in a timed environment. The duration of the exam is two hours, and candidates are required to score a minimum of 70% to pass the exam. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is valid for two years, and candidates are required to recertify after the expiration of the certification.
NEW QUESTION # 168
You are building an application that runs on Cloud Run The application needs to access a third-party API by using an API key You need to determine a secure way to store and use the API key in your application by following Google-recommended practices What should you do?
Answer: C
Explanation:
The best option for storing and using the API key in your application by following Google-recommended practices is to save the API key in Secret Manager as a secret and reference the secret as an environment variable in the Cloud Run application. Secret Manager is a service that allows you to store and manage sensitive data, such as API keys, passwords, and certificates, in Google Cloud. A secret is a resource that represents a logical secret, such as an API key. You can save the API key in Secret Manager as a secret and use IAM policies to control who can access it. You can also reference the secret as an environment variable in the Cloud Run application by using the ${SECRET_NAME} syntax. This way, you can securely store and use the API key in your application without exposing it in your code or configuration files.
NEW QUESTION # 169
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?
Answer: C
Explanation:
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
NEW QUESTION # 170
Your company follows Site Reliability Engineering practices. You are the person in charge of Communications for a large, ongoing incident affecting your customer-facing applications. There is still no estimated time for a resolution of the outage. You are receiving emails from internal stakeholders who want updates on the outage, as well as emails from customers who want to know what is happening. You want to efficiently provide updates to everyone affected by the outage. What should you do?
Answer: B
NEW QUESTION # 171
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead.
What should you do?
Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
Answer: C
Explanation:
Explanation
The correct answer is C. Configure Cloud Profiler, and initialize the cloud.google.com/go/profiler library in the application.
According to the Google Cloud documentation, Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications1.
Cloud Profiler can help you identify slow paths in your code and optimize the performance of your applications. Cloud Profiler supports applications written in Go that run on App Engine standard environment2. To use Cloud Profiler, you need to configure it in your Google Cloud project and initialize the cloud.google.com/go/profiler library in your application code3. You can then use the Cloud Profiler interface to analyze the profiling data and visualize the results by using flame graphs4. Cloud Profiler has minimal performance impact and management overhead, as it only samples a small fraction of the application activity and does not require any additional infrastructure or agents.
The other options are incorrect because they do not meet the requirements of minimizing performance impact and management overhead. Option A is incorrect because it requires installing a continuous profiling tool into Compute Engine, which is an additional infrastructure that needs to be managed and maintained. Option B is incorrect because it requires periodically running the go tool pprof command against the application instance, which is a manual and disruptive process that can affect the application performance. Option D is incorrect because it only uses Cloud Monitoring to assess the App Engine CPU utilization metric, which is not enough to identify slow paths in the code or optimize the application performance.
NEW QUESTION # 172
You need to reduce the cost of virtual machines (VM| for your organization. After reviewing different options, you decide to leverage preemptible VM instances. Which application is suitable for preemptible VMs?
Answer: A
NEW QUESTION # 173
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