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| Section | Weight | Objectives |
|---|
| Integrating applications with Google Cloud services | 21% | - 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
- Integrating with data and storage services
- 1. Implementing messaging and event streaming
- 2. Using object storage and file storage solutions
- 3. Working with relational, NoSQL, and in-memory databases
- Implementing application performance monitoring
- 1. Instrumenting code for metrics and traces
- 2. Using operations suite tools
|
| Building and testing applications | 23% | - Setting up development environments
- 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
- 2. Emulating Google Cloud services locally
- Testing applications
- 1. Writing unit, integration, and end-to-end tests
- 2. Using AI-assisted development tools
- 3. Automating testing in CI/CD workflows
- Building applications and containers
- 1. Implementing containerization best practices
- 2. Using Cloud Build and Artifact Registry
- 3. Configuring build pipelines and provenance
|
| Designing highly scalable, secure, and reliable cloud-native applications | 32% | - Designing secure applications
- 1. Applying security best practices and compliance requirements
- 2. Securing data in transit and at rest
- 3. Implementing authentication and authorization mechanisms
- 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 Google Kubernetes Engine
- 1. Managing configurations and secrets
- 2. Creating and managing workloads and services
- 3. Configuring scaling, auto-scaling, and updates
- Deploying to App Engine or Cloud Functions
- 1. Configuring serverless deployments
- 2. Managing versions and traffic splitting
- Deploying applications to Cloud Run
- 1. Integrating with event-driven services
- 2. Deploying from source code or containers
- 3. Configuring scaling, networking, and security
|
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Google Certified Professional - Cloud Developer Sample Questions (Q255-Q260):
NEW QUESTION # 255
You recently developed a new application. You want to deploy the application on Cloud Run without a Dockerfile. Your organization requires that all container images are pushed to a centrally managed container repository. How should you build your container using Google Cloud services? (Choose two.)
- A. Submit a Cloud Build job to push the image.
- B. Push your source code to Artifact Registry.
- C. Include the --platform=kubernetes flag with the gcloud run deploy CLI command.
- D. Use the pack build command with pack CLI.
- E. Include the --source flag with the gcloud run deploy CLI command.
Answer: B,D
Explanation:
https://cloud.google.com/run/docs/deploying#images
https://cloud.google.com/blog/products/containers-kubernetes/google-cloud-now-supports-buildpacks
NEW QUESTION # 256
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.
Which Google Cloud product addresses HipLocal's business requirements for service level indicators and objectives?
- A. Cloud Logging
- B. Cloud Trace
- C. Cloud Profiler
- D. Cloud Monitoring
Answer: D
Explanation:
https://cloud.google.com/stackdriver/docs/solutions/slo-monitoring
NEW QUESTION # 257
Your company has deployed a new API to App Engine Standard environment. During testing, the API is not behaving as expected. You want to monitor the application over time to diagnose the problem within the application code without redeploying the application.
Which tool should you use?
- A. Stackdriver Debug Snapshots
- B. Stackdriver Monitoring
- C. Stackdriver Trace
- D. Stackdriver Debug Logpoints
Answer: B
Explanation:
Reference:
https://rominirani.com/gcp-stackdriver-tutorial-debug-snapshots-traces-logging-and-logpoints-
1ba49e4780e6
NEW QUESTION # 258
Which service should HipLocal use to enable access to internal apps?
- A. Virtual Private Cloud
- B. Cloud VPN
- C. Cloud Armor
- D. Cloud Identity-Aware Proxy
Answer: D
Explanation:
Reference:
https://cloud.google.com/iap/docs/cloud-iap-for-on-prem-apps-overview
NEW QUESTION # 259
Your team detected a spike of errors in an application running on Cloud Run in your production project. The application is configured to read messages from Pub/Sub topic A, process the messages, and write the messages to topic B. You want to conduct tests to identify the cause of the errors. You can use a set of mock messages for testing. What should you do?
- A. Deploy the Pub/Sub emulator on your local machine. Point the production application to your local Pub/Sub topics. Write mock messages to topic A, and then analyze the logs.
- B. Deploy the Pub/Sub and Cloud Run emulators on your local machine. Deploy the application locally, and change the logging level in the application to DEBUG or INFO. Write mock messages to topic A, and then analyze the logs.
- C. Use the Google Cloud console to write mock messages to topic A. Change the logging level in the application to DEBUG or INFO, and then analyze the logs.
- D. Use the gcloud CLI to write mock messages to topic A. Change the logging level in the application to DEBUG or INFO, and then analyze the logs.
Answer: D
NEW QUESTION # 260
......
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