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Earning the Google Professional-Cloud-DevOps-Engineer Certification can open up new career opportunities for cloud DevOps professionals, as it is recognized as a valuable credential in the industry. It can also help professionals demonstrate their commitment to ongoing learning and development, and provide them with the skills and knowledge they need to succeed in the rapidly evolving field of cloud DevOps engineering.
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The Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam consists of multiple-choice and scenario-based questions that test the candidate's practical experience and knowledge of DevOps practices on the Google Cloud Platform. Professional-Cloud-DevOps-Engineer Exam is available in several languages, including English, Japanese, and Spanish, and is delivered through a secure online platform.
NEW QUESTION # 90
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?
Answer: C
Explanation:
https://cloud.google.com/architecture/continuous-delivery-toolchain-spinnaker-cloud
https://spinnaker.io/guides/user/pipeline/triggers/pubsub/
NEW QUESTION # 91
Your company is developing applications that are deployed on Google Kubernetes Engine (GKE). Each team manages a different application. You need to create the development and production environments for each team, while minimizing costs. Different teams should not be able to access other teams' environments. What should you do?
Answer: B
Explanation:
Explanation
https://cloud.google.com/architecture/prep-kubernetes-engine-for-prod#roles_and_groups
NEW QUESTION # 92
You are deploying an application to Cloud Run. The application requires a password to start. Your organization requires that all passwords are rotated every 24 hours, and your application must have the latest password. You need to deploy the application with no downtime. What should you do?
Answer: C
Explanation:
The correct answer is B, Store the password in Secret Manager and mount the secret as a volume within the application.
Secret Manager is a service that allows you to securely store and manage sensitive data such as passwords, API keys, certificates, and tokens. You can use Secret Manager to rotate your secrets automatically or manually, and access them from your Cloud Run applications1.
There are two ways to use secrets from Secret Manager in Cloud Run:
As environment variables: You can set environment variables that point to secrets in Secret Manager. Cloud Run will resolve the secrets at runtime and inject them into the environment of your application. However, this method has some limitations, such as:
The environment variables are cached for up to 10 minutes, so you may not get the latest version of the secret immediately.
The environment variables are visible in plain text in the Cloud Console and the Cloud SDK, which may expose sensitive information.
The environment variables are limited to 4 KB of data, which may not be enough for some secrets.2 As file system volumes: You can mount secrets from Secret Manager as files in a volume within your application. Cloud Run will create a tmpfs volume and write the secrets as files in it. This method has some advantages, such as:
The files are updated every 30 seconds, so you can get the latest version of the secret faster.
The files are not visible in the Cloud Console or the Cloud SDK, which provides better security.
The files can store up to 64 KB of data, which allows for larger secrets.3 Therefore, for your use case, it is better to use the second method and mount the secret as a file system volume within your application. This way, you can ensure that your application has the latest password, and you can deploy it with no downtime.
To mount a secret as a file system volume in Cloud Run, you can use the following command:
gcloud beta run deploy SERVICE --image IMAGE_URL --update-secrets=/path/to/file=secretName:version where:
SERVICE is the name of your Cloud Run service.
IMAGE_URL is the URL of your container image.
/path/to/file is the path where you want to mount the secret file in your application.
secretName is the name of your secret in Secret Manager.
You can also use the Cloud Console to mount secrets as file system volumes. For more details, see Mounting secrets from Secret Manager.
Reference:
1: Overview | Secret Manager Documentation | Google Cloud
2: Using secrets as environment variables | Cloud Run Documentation | Google Cloud
3: Mounting secrets from Secret Manager | Cloud Run Documentation | Google Cloud
NEW QUESTION # 93
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 # 94
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?
Answer: D
NEW QUESTION # 95
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