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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing high-performing applications and APIs 1. Selecting appropriate compute and deployment platforms 2. Optimizing for latency and throughput 3. Designing for high availability and fault tolerance - Designing for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies - Designing secure applications 1. Securing data in transit and at rest 2. Applying security best practices and compliance requirements 3. Implementing authentication and authorization mechanisms
Configuring cloud-native applications for deployment	24%	- Deploying to App Engine or Cloud Functions 1. Managing versions and traffic splitting 2. Configuring serverless deployments - Deploying applications to Google Kubernetes Engine 1. Managing configurations and secrets 2. Creating and managing workloads and services 3. Configuring scaling, auto-scaling, and updates - Deploying applications to Cloud Run 1. Deploying from source code or containers 2. Integrating with event-driven services 3. Configuring scaling, networking, and security
Integrating applications with Google Cloud services	21%	- Integrating with data and storage services 1. Working with relational, NoSQL, and in-memory databases 2. Implementing messaging and event streaming 3. Using object storage and file storage solutions - Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools - Consuming Google Cloud APIs and services 1. Enabling and managing APIs 2. Using client libraries, REST, and gRPC 3. Integrating with AI/ML and generative AI services
Building and testing applications	23%	- Setting up development environments 1. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations - Testing applications 1. Writing unit, integration, and end-to-end tests 2. Automating testing in CI/CD workflows 3. Using AI-assisted development tools - Building applications and containers 1. Configuring build pipelines and provenance 2. Implementing containerization best practices 3. Using Cloud Build and Artifact Registry

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Google Certified Professional - Cloud Developer Sample Questions (Q363-Q368):

NEW QUESTION # 363
You have an application running in App Engine. Your application is instrumented with Stackdriver Trace. The /product-details request reports details about four known unique products at /sku-details as shown below. You want to reduce the time it takes for the request to complete. What should you do?

A. Store the /sku-details information in a database, and replace the webservice call with a database query.
B. Change /product-details to perform the requests in parallel.
C. Change the Persistent Disk type to SSD.
D. Increase the size of the instance class.

Answer: B

NEW QUESTION # 364
You plan to make a simple HTML application available on the internet. This site keeps information about FAQs for your application. The application is static and contains images, HTML, CSS, and Javascript. You want to make this application available on the internet with as few steps as possible.
What should you do?

A. Upload your application to Cloud Storage.
B. Containerize your application first. Deploy this container to Google Kubernetes Engine (GKE) and assign an external IP address to the GKE pod hosting the application.
C. Create a Compute Engine instance with Apache web server installed. Configure Apache web server to host the application.
D. Upload your application to an App Engine environment.

Answer: A

Explanation:
Explanation/Reference: https://cloud.google.com/storage/docs/hosting-static-website

NEW QUESTION # 365
Your organization has recently begun an initiative to replatform their legacy applications onto Google Kubernetes Engine. You need to decompose a monolithic application into microservices.
Multiple instances have read and write access to a configuration file, which is stored on a shared file system. You want to minimize the effort required to manage this transition, and you want to avoid rewriting the application code. What should you do?

A. Create a new Filestore instance, and mount the volume as an NFS PersistentVolume.
B. Create a new persistent disk, and mount the volume as a shared PersistentVolume.
C. Create a new ConfigMap and volumeMount to store the contents of the configuration file.
D. Create a new Cloud Storage bucket, and mount it via FUSE in the container.

Answer: A

Explanation:
https://kubernetes.io/docs/concepts/storage/volumes/#nfs
An nfs volume allows an existing NFS (Network File System) share to be mounted into a Pod.
Unlike emptyDir, which is erased when a Pod is removed, the contents of an nfs volume are preserved and the volume is merely unmounted. This means that an NFS volume can be pre- populated with data, and that data can be shared between pods. NFS can be mounted by multiple writers simultaneously.

NEW QUESTION # 366
You are deploying your application to a Compute Engine virtual machine instance. Your application is configured to write its log files to disk. You want to view the logs in Stackdriver Logging without changing the application code.
What should you do?

A. Provide the log file folder path in the metadata of the instance to configure it to send the application logs.
B. Use a Stackdriver Logging Library to log directly from the application to Stackdriver Logging.
C. Install the Stackdriver Logging Agent and configure it to send the application logs.
D. Change the application to log to /var/log so that its logs are automatically sent to Stackdriver Logging.

Answer: C

NEW QUESTION # 367
This architectural diagram depicts a system that streams data from thousands of devices. You want to ingest data into a pipeline, store the data, and analyze the data using SQL statements. Which Google Cloud services should you use for steps 1, 2, 3, and 4?

A. 1) App Engine
2) Pub/Sub
3) BigQuery
4) Firestore
B. 1) Pub/Sub
2) Dataflow
3) Firestore
4) BigQuery
C. 1) Pub/Sub
2) Dataflow
3) BigQuery
4) Firestore
D. 1) Dataflow
2) Pub/Sub
3) Firestore
4) BigQuery

Answer: B

NEW QUESTION # 368
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