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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
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 - Building applications and containers 1. Using Cloud Build and Artifact Registry 2. Implementing containerization best practices 3. Configuring build pipelines and provenance - Testing applications 1. Automating testing in CI/CD workflows 2. Writing unit, integration, and end-to-end tests 3. Using AI-assisted development tools
Configuring cloud-native applications for deployment	24%	- Deploying applications to Google Kubernetes Engine 1. Creating and managing workloads and services 2. Configuring scaling, auto-scaling, and updates 3. Managing configurations and secrets - 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. Configuring scaling, networking, and security 3. Deploying from source code or containers
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 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 for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies
Integrating applications with Google Cloud services	21%	- Consuming Google Cloud APIs and services 1. Integrating with AI/ML and generative AI services 2. Using client libraries, REST, and gRPC 3. Enabling and managing APIs - Integrating with data and storage services 1. Using object storage and file storage solutions 2. Implementing messaging and event streaming 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

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Google Certified Professional - Cloud Developer Sample Questions (Q158-Q163):

NEW QUESTION # 158
Your application performs well when tested locally, but it runs significantly slower when you deploy it to App Engine standard environment. You want to diagnose the problem. What should you do?

A. Use Stackdriver Trace to determine which functions within the application have higher latency.
B. File a ticket with Cloud Support indicating that the application performs faster locally.
C. Add logging commands to the application and use Stackdriver Logging to check where the latency problem occurs.
D. Use Stackdriver Debugger Snapshots to look at a point-in-time execution of the application.

Answer: C

Explanation:
Topic 1, HipLocal Case Study
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 10,000 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.
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
* Data is exported to an on-premises Teradata/Vertica data warehouse
* Data analytics is performed in an on-premises Hadoop environment
* The application has no logging
* 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
* Increase the number of concurrent users that can be supported
* 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
Technical Requirements
* The application and backend must provide usage metrics and monitoring
* APIs require strong authentication and authorization
* Logging must be increased, and data should be stored in a cloud analytics platform
* Move to serverless architecture to facilitate elastic scaling
* Provide authorized access to internal apps in a secure manner

NEW QUESTION # 159
You are using Cloud Build build to promote a Docker image to Development, Test, and Production environments. You need to ensure that the same Docker image is deployed to each of these environments.
How should you identify the Docker image in your build?

A. Use the latest Docker image tag.
B. Use a semantic version Docker image tag.
C. Use the digest of the Docker image.
D. Use a unique Docker image name.

Answer: B

Explanation:
Explanation/Reference:

NEW QUESTION # 160
You recently deployed a Go application on Google Kubernetes Engine (GKE). The operations team has noticed that the application's CPU usage is high even when there is low production traffic. The operations team has asked you to optimize your application's CPU resource consumption. You want to determine which Go functions consume the largest amount of CPU.
What should you do?

A. Deploy a Fluent Bit daemonset on the GKE cluster to log data in Cloud Logging. Analyze the logs to get insights into your application code's performance.
B. Modify your Go application to capture profiling data. Analyze the CPU metrics of your application in flame graphs in Profiler.
C. Connect to your GKE nodes using SSH. Run the top command on the shell to extract the CPU utilization of your application.
D. Create a custom dashboard in Cloud Monitoring to evaluate the CPU performance metrics of your application.

Answer: B

Explanation:
https://cloud.google.com/profiler/docs/about-profiler
Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications. It attributes that information to the source code that generated it, helping you identify the parts of your application that are consuming the most resources, and otherwise illuminating your applications performance characteristics.

NEW QUESTION # 161
Your existing application keeps user state information in a single MySQL database. This state information is very user-specific and depends heavily on how long a user has been using an application. The MySQL database is causing challenges to maintain and enhance the schema for various users.
Which storage option should you choose?

A. Cloud Spanner
B. Cloud Storage
C. Cloud SQL
D. Cloud Datastore/Firestore

Answer: C

Explanation:
Explanation/Reference:
Reference: https://cloud.google.com/solutions/migrating-mysql-to-cloudsql-concept

NEW QUESTION # 162
Your application is logging to Stackdriver. You want to get the count of all requests on all
/api/alpha/* endpoints.
What should you do?

A. Add a Stackdriver counter metric for path:/api/alpha/.
B. Export the logs to Cloud Pub/Sub and count lines matching /api/alpha.
C. Add a Stackdriver counter metric for endpoint:/api/alpha/*.
D. Export the logs to Cloud Storage and count lines matching /api/alpha.

Answer: C

Explanation:
Create a filter that collects only the log entries that you want to count in your metric using the logging query language. You can also use regular expressions to create your metric's filters.
https://cloud.google.com/logging/docs/logs-based-metrics/counter-metrics#console

NEW QUESTION # 163
......

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