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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Sample Questions (Q25-Q30):

NEW QUESTION # 25
Case Study 2 - HipLocal
Company Overview
HipLocal is a community application designed to facilitate communication between people in close proximity. It is used for event planning and organizing sporting events, and for businesses to connect with their local communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement
We are the number one local community app; it's time to take our local community services global. Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept
HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones. They will need to ensure that the application scales smoothly and provides clear uptime data, and that they analyze and respond to any issues that occur.
Existing Technical Environment
HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform. The HipLocal team understands their application well, but has limited experience in global scale applications. Their existing technical environment is as follows:
- Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
- State is stored in a single instance MySQL database in GCP.
- Release cycles include development freezes to allow for QA testing.
- The application has no logging.
- Applications are manually deployed by infrastructure engineers during periods of slow traffic on weekday evenings.
- There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements
HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are:
- Expand availability of the application to new regions.
- Support 10x as many concurrent users.
- Ensure a consistent experience for users when they travel to different regions.
- Obtain user activity metrics to better understand how to monetize their product.
- Ensure compliance with regulations in the new regions (for example, GDPR).
- Reduce infrastructure management time and cost.
- Adopt the Google-recommended practices for cloud computing.
Develop standardized workflows and processes around application lifecycle management.
Define service level indicators (SLIs) and service level objectives (SLOs).
Technical Requirements
- Provide secure communications between the on-premises data center and cloud-hosted applications and infrastructure.
- The application must provide usage metrics and monitoring.
- APIs require authentication and authorization.
- Implement faster and more accurate validation of new features.
- Logging and performance metrics must provide actionable information to be able to provide debugging information and alerts.
- Must scale to meet user demand.
For this question, refer to the HipLocal case study.
How should HipLocal increase their API development speed while continuing to provide the QA team with a stable testing environment that meets feature requirements?

A. Redeploy the APIs to App Engine using Traffic Splitting. Do not move QA traffic to the new versions if errors are found.
B. Include unit tests in their code, and prevent deployments to QA until all tests have a passing status.
C. Include performance tests in their code, and prevent deployments to QA until all tests have a passing status.
D. Create health checks for the QA environment, and redeploy the APIs at a later time if the environment is unhealthy.

Answer: B

Explanation:
A stable environment is one that works. Performance testing does not mean it works fine, unit testing will enable this.

NEW QUESTION # 26
You are developing an application that needs to store files belonging to users in Cloud Storage.
You want each user to have their own subdirectory in Cloud Storage. When a new user is created, the corresponding empty subdirectory should also be created. What should you do?

A. Create an object with the name of the subdirectory that is zero bytes in length. Set the Content- Type metadata to CLOUDSTORAGE_FOLDER.
B. Create an object with the name of the subdirectory ending with a trailing slash ('/') that is zero bytes in length.
C. Create an object with the name of the subdirectory that is zero bytes in length and has WRITER access control list permission.
D. Create an object with the name of the subdirectory, and then immediately delete the object within that subdirectory.

Answer: B

Explanation:
https://cloud.google.com/storage/docs/folders
If you create an empty folder using the Google Cloud console, Cloud Storage creates a zero-byte object as a placeholder. For example, if you create a folder called folder in a bucket called my- bucket, a zero- byte object called gs://my-bucket/folder/ is created. This placeholder is discoverable by other tools when listing the objects in the bucket, for example when using the gsutil ls command.

NEW QUESTION # 27
You have an application deployed in Google Kubernetes Engine (GKE). You need to update the application to make authorized requests to Google Cloud managed services. You want this to be a one-time setup, and you need to follow security best practices of auto-rotating your security keys and storing them in an encrypted store. You already created a service account with appropriate access to the Google Cloud service. What should you do next?

A. Assign the Google Cloud service account to your GKE Pod using Workload Identity.
B. Export the Google Cloud service account, and share it with the Pod as a Kubernetes Secret.
C. Export the Google Cloud service account, and upload it to HashiCorp Vault to generate a dynamic service account for your application.
D. Export the Google Cloud service account, and embed it in the source code of the application.

Answer: A

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/workload-identity Applications running on GKE might need access to Google Cloud APIs such as Compute Engine API, BigQuery Storage API, or Machine Learning APIs.
Workload Identity allows a Kubernetes service account in your GKE cluster to act as an IAM service account. Pods that use the configured Kubernetes service account automatically authenticate as the IAM service account when accessing Google Cloud APIs. Using Workload Identity allows you to assign distinct, fine-grained identities and authorization for each application in your cluster.

NEW QUESTION # 28
You need to deploy a new European version of a website hosted on Google Kubernetes Engine. The current and new websites must be accessed via the same HTTP(S) load balancer's external IP address, but have different domain names. What should you do?

A. Create a new Service of type LoadBalancer specifying the existing IP address as the loadBalancerIP
B. Define a new Ingress resource with a host rule matching the new domain
C. Generate a new Ingress resource and specify the existing IP address as the kubernetes.io/ingress.global-static-ip-name annotation value
D. Modify the existing Ingress resource with a host rule matching the new domain

Answer: D

Explanation:
https://kubernetes.io/docs/concepts/services-networking/ingress/#name-based-virtual-hosting Name-based virtual hosts support routing HTTP traffic to multiple host names at the same IP address.

NEW QUESTION # 29
Your team develops services that run on Google Kubernetes Engine. Your team's code is stored in Cloud Source Repositories. You need to quickly identify bugs in the code before it is deployed to production. You want to invest in automation to improve developer feedback and make the process as efficient as possible.
What should you do?

A. Use Cloud Build to automate building container images from code based on forked versions.
B. Use Spinnaker to automate building container images from code based on Git tags.
C. Use Spinnaker to automate deploying container images to the production environment.
D. Use Cloud Build to automate building container images from code based on Git tags.

Answer: B

Explanation:
Reference: https://spinnaker.io/docs/guides/tutorials/codelabs/kubernetes-v2-source-to-prod/

NEW QUESTION # 30
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