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Google Professional Cloud Developer Practice Test Questions, Google Professional Cloud Developer Exam Practice Test Questions
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The Professional Cloud Developer certificate validates the skills of the interested candidates in building highly available and scalable applications with the use of the tools and practices recommended by Google. The potential applicants for this certification must demonstrate practical experience with developer tools, Cloud-native applications, next-gen databases, and managed services. They also have the expertise in at least one programming language and can develop meaningful logs and metrics to trace and debug code. Those individuals pursuing this option must pass one qualifying exam.
The candidates for this certification are the Cloud developers who have competence in building highly available and scalable apps with the Google-recommended tools and practices. They also have proficiency in a minimum of one general-purpose programming language. It is recommended that the individuals for the Professional Cloud Developer certificate have at least three years of practical experience with Google Cloud solutions and products. They should also possess at least one year of designing and managing solutions with the use of GCP. Please note that you should also understand the content of the prerequisite exam before attempting it.
The Professional Cloud Developer certification exam is a 2-hour test covering the multiple-choice and multiple-select questions. It can be taken in English or Japanese and is available as an online proctored and an on-site proctored exam. The registration process costs $200, and this is for the delivery of a single test. The candidates who do not pass the exam must retake it to obtain the associated certificate. To do this, they must pay a new exam fee for their retake.
This certification exam measures your ability to perform various tasks required for the successful functioning of different processes. The details of its topics are enumerated below:
Designing Highly Available, Reliable, and Scalable Cloud-Native Apps
- Design High Performing APIs and Applications: The considerations for this subject area include Microservices, scaling velocity tradeoffs/characteristics of IaaS vs. CaaS vs. PaaS, Geographic distribution of Google Cloud services, and user session management. It also covers the domains, such as caching solutions, securing & deploying API services, Google-recommended documentation & practices, and refined shutdown on the platform termination. The learners should also be able to explain the key structure of high-write apps with the use of Cloud Storage, Cloud SQL, Cloud Spanner, and Cloud Bigtable.
- Design Secure Applications: This topic covers the details, which include security mechanisms securing and protecting services and resources as well as app manifests & binaries. It also involves the skills in implementing the appropriate prerequisites for applicable applications. You should know about rotating & storing application keys & secrets, validating processes of the Google service, service-to-service communications, and IAM roles for groups/service/user accounts. The subtopic also covers your knowledge of how to run the services that have the least privileged access, data retention prerequisites, and certificate-based validation.
- Manage Application Data: The considerations for this subdomain include data volume, structured versus unstructured data, strong versus eventual consistency, and data access frequency within Cloud Storage.
- Application Modernization: It covers the learners’ skills in using managed services, designing horizontally state-less scalable services, refactoring the monolith to micro-services, and understanding the Google-recommended practices and documentation.
Building & Testing Apps
- Set up a Local Development Environment: This subsection measures your skills in creating different Google Cloud projects, using developing tools and command-line interfaces, Cloud Shell tools, and Google Cloud Console, as well as imitating Google Cloud services for the development of the local application.
- Write Efficient Code: The potential candidates should understand algorithm design, software development methodologies, modern app patterns, and debugging & profiling code.
- Testing: Here, an applicant needs to have the skills in unit testing, performance testing, integration testing, and load testing.
- Building: It covers the skills in managing source control, improving and reviewing continuous efficiency in the integration pipeline, as well as creating different secure container images through code.
- Recommend the Relevant Deployment Strategies with the Relevant Tools for a Target Compute Environment: The consideration for this section includes traffic-splitting deployments, canary deployments, rolling deployments, and green/blue deployments.
- Deploy Applications & Services on the Compute Engine: This area covers bootstrapping of applications, management of service accounts for virtual machines, management of the Compute Engine virtual machine binaries and images, and exporting of application metrics and logs.
- Deploy Applications & Services to GKE: This subtopic includes the evaluation of one’s skills in deploying containerized applications to GCE, configuring Google Cloud IAM and Kubernetes RBAC relationships, identifying workload specifications, and configuring the Kubernetes namespaces, among others.
- Deploy Cloud Functions: The next objective requires having the skills in securing Cloud functions, Cloud functions invoked through HTTP, and Cloud functions triggered through events from Google Cloud services.
- Use a Service Account: This one covers the students’ skills in downloading and utilizing service account private key files as well as constructing service accounts based on the ethics of least privilege.
Incorporating Google Cloud Services
- Incorporate Applications with Data & Storage Services: The considerations for this subsection include connecting to data stores, write/read data from/to different databases and write applications that consume/publish data asynchronously.
- Integrate Applications with Compute Services: This part contains the measurement of the skills in implementing the service discovery in Compute Engine and GKE, authenticating utilizing Identity-Aware Proxy & OAuth2.0 Web Flow, and authenticating with Workload Identity to Cloud APIs.
- Integrate Cloud APIs with Apps: This domain comes with caching results, restricting return data, batching requests, paginating results, and error handling.
Managing Application Performance Monitoring
- Manage Compute Engine Virtual Machines: It covers the applicants’ skills in analyzing & viewing logs; debugging custom VM images with serial ports, sending logs to Cloud Logging from VMs, and inspecting resource usage over time.
- Manage Workloads for the Google Kubernetes Engine: The considerations for this topic include configuring monitoring & logging, viewing & analyzing logs, configuring workload auto-scaling, writing & exporting custom metrics, and analyzing the lifecycle events of a container.
- Troubleshoot Application Performance: This one covers the skills of the test takers in using Cloud Debugger, creating and writing custom and log-based metrics, exporting the logs from GC, and using forums, Google Cloud support, and documentation, among others.
Those individuals who have the Google Professional Cloud Developer certification can take up the job titles, such as Software Engineers, Solutions Architects, Operations Analysts, Web Application Developers, Senior Software Engineers, Information Security Managers, or Data Engineers. The average salary for these positions is $87,000 per annum.
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