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How to Prepare For Google Professional Cloud Developer Exam
Preparation Guide for Google Professional Cloud Developer Exam
Introduction
Google has designed different Role Based Certifications for the IT professionals to validate their skillset one among them is Google Professional Cloud Developer. This program gives Google cloud professionals a way to demonstrate their skills. The evaluation relies on a meticulous exam using industry standard methodology to validate aspirants proficiency standards to meet Google’s proficiency standards.
According to Google, a Google Certified Professional Cloud Developer facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud developer and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
In this guide, we will cover the Google Professional Cloud Developer Exam, Google Professional Cloud Developer Certified Professionals salary and all aspects of the Google Professional Cloud Developer Certification.
Introduction to Google Professional Cloud Developer Exam
Google Professional Cloud Developer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud Architect in the IT industry.
After passing this exam, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud Developer to their clients and employers.
Topics of Google Professional Cloud Developer Exam
Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our Google Professional Cloud Developer Dumps will include the following topics:
1. Designing highly scalable, available, and reliable cloud-native applications
Designing high-performing applications and APIs
- Microservices
- Scaling velocity characteristics/tradeoffs of IaaS (infrastructure as a service) vs. CaaS (container as a service) vs. PaaS (platform as a service)
- Evaluating different services and technologies
- Geographic distribution of Google Cloud services (e.g., latency, regional services, zonal services)
- Defining a key structure for high-write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL
- User session management
- Caching solutions
- Deploying and securing API services
- Loosely coupled applications using asynchronous Cloud Pub/Sub events
- Graceful shutdown on platform termination
- Google-recommended practices and documentation
Designing secure applications
- Implementing requirements that are relevant for applicable regulations (e.g., data wipeout)
- Security mechanisms that protect services and resources
- Security mechanisms that secure/scan application binaries and manifests
- Storing and rotating application secrets using Cloud KMS
- Authenticating to Google services (e.g., application default credentials, JWT, OAuth 2.0)
- IAM roles for users/groups/service accounts
- Securing service-to-service communications (e.g., service mesh, Kubernetes network policies, and Kubernetes namespaces)
- Set compute/workload identity to least privileged access
- Certificate-based authentication (e.g., SSL, mTLS)
- Google-recommended practices and documentation
Managing application data
- Defining database schemas for Google-managed databases (e.g., Cloud Firestore, Cloud Spanner, Cloud Bigtable, Cloud SQL)
- Choosing data storage options based on use case considerations, such as:
- Cloud Storage-signed URLs for user-uploaded content
- Structured vs. unstructured data
- Strong vs. eventual consistency
- Data volume
- Frequency of data access in Cloud Storage
- Following Google-recommended practices and documentation
Refactoring applications to migrate to Google Cloud
- Using managed services
- Migrating a monolith to microservices
- Google-recommended practices and documentation
2 Building and Testing Applications
Setting up your local development environment
- Emulating Google Cloud services for local application development
- Creating Google Cloud projects
Writing code
- Algorithm design
- Modern application patterns
- Efficiency
- Agile software development
- Unit testing
Testing
- Performance testing
- Integration testing
- Load testing
Building
- Creating a Cloud Source Repository and committing code to it
- Creating container images from code
- Developing a continuous integration pipeline using services (e.g., Cloud Build, Container Registry) that construct deployment artifacts
- Reviewing and improving continuous integration pipeline efficacy
3 Deploying applications
Recommend appropriate deployment strategies for the target compute environment (Compute Engine, Google Kubernetes Engine). Strategies include:
- Blue/green deployments
- Traffic-splitting deployments
- Rolling deployments
- Canary deployments
Deploying applications and services on Compute Engine
- Installing an application into a VM
- Modifying the VM service account
- Manually updating dependencies on a VM
- Exporting application logs and metrics
- Managing Compute Engine VM images and binaries
Deploying applications and services to Google Kubernetes Engine (GKE)
- Deploying a containerized application to GKE
- Managing Kubernetes RBAC and Google Cloud IAM relationship
- Configuring Kubernetes namespaces and access control
- Defining workload specifications (e.g., resource requirements)
- Building a container image using Cloud Build
- Configuring application accessibility to user traffic and other services
- Managing container lifecycle
- Define deployments, services, and pod configurations
Deploying a Cloud Function
- Cloud Functions that are triggered via an event (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)
- Cloud Functions that are invoked via HTTP
- Securing Cloud Functions
Using service accounts
- Creating a service account according to the principle of least privilege
- Downloading and using a service account private key file
4 Integrating Google Cloud Platform Services
Integrating an application with data and storage services
- Read/write data to/from various databases (e.g., SQL, JDBC)
- Connecting to a data store (e.g., Cloud SQL, Cloud Spanner, Cloud Firestore, Cloud Bigtable)
- Writing an application that publishes/consumes data asynchronously (e.g., from Cloud Pub/Sub)
- Storing and retrieving objects from Cloud Storage
- Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
Integrating an application with compute services
- Implementing service discovery in Google Kubernetes Engine and Compute Engine
- Reading instance metadata to obtain application configuration
- Authenticating users by using OAuth2.0 Web Flow and Identity Aware Proxy
- Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
Integrating Google Cloud APIs with applications
- Enabling a Google Cloud API
- Making API calls with a Cloud Client Library, the REST API, or the APIs Explorer, taking into consideration:
- Batching requests
- Restricting return data
- Paginating results
- Caching results
- Error handling (e.g., exponential backoff)
- Using service accounts to make Google API calls
5 Managing Application Performance Monitoring
Managing Compute Engine VMs
- Debugging a custom VM image using the serial port
- Analyzing a failed Compute Engine VM startup
- Analyzing logs
- Sending logs from a VM to Cloud Monitoring
- Inspecting resource utilization over time
- Viewing syslogs from a VM
Managing Google Kubernetes Engine workloads
- Configuring logging and monitoring
- Analyzing container lifecycle events (e.g., CrashLoopBackOff, ImagePullErr)
- Analyzing logs
- Using external metrics and corresponding alerts
- Configuring workload autoscaling
Troubleshooting application performance
- Creating a monitoring dashboard
- Writing custom metrics and creating metrics from logs
- Graphing metrics
- Using Cloud Debugger
- Reviewing stack traces for error analysis
- Exporting logs from Google Cloud
- Viewing logs in the Google Cloud Console
- Profiling performance of request-response
- Profiling services
- Reviewing application performance (e.g., Cloud Trace, Prometheus, OpenCensus)
- Monitoring and profiling a running application
- Using documentation, forums, and Google support
Who should take the Google Professional Cloud Developer exam
Individuals should pursue the Google Professional Cloud Developer Exam if they want to demonstrate their expertise and ability to design highly scalable, available, and reliable cloud-native applications and deploy applications. It’s perfect for solutions and/or enterprise architects, systems administrators or operations team members or simply any professional who wants in on this specific area of IT and cloud. A Professional Cloud Developer should have skills at producing meaningful metrics and logs to debug and trace code and proficiency with at least one general-purpose programming language.
How to study the Google Professional Cloud Developer Exam
Preparation of certification exams could be covered with two resource types . The first one are the study guides, reference books and study forums that are elaborated and appropriate for building information from ground up. Apart from them video tutorials and lectures are a good option to ease the pain of through study and are relatively make the study process more interesting nonetheless these demand time and concentration from the learner. Smart candidates who wish to create a solid foundation altogether examination topics and connected technologies typically mix video lectures with study guides to reap the advantages of each but practice exams or practice exam engines is one important study tool which goes typically unnoted by most candidates. Practice exams are designed with our experts to make exam prospects test their knowledge on skills attained in course, as well as prospects become comfortable and familiar with the real exam environment.Statistics have indicated exam anxiety plays much bigger role of students failure in exam than the fear of the unknown. Certification-questions expert team recommends preparing some notes on these topics along with it don’t forget to practice Google Professional Cloud Developer Exam dumps which had been written by our expert team, each of these can assist you loads to clear this exam with excellent marks.
Google Professional Cloud Developer Certification Path
The Google Professional Cloud Developer Certification is the highest level of certification mainly focussing to the Google Professional Cloud Developer. There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google Professional Cloud Developer. You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path
How much Google Professional Cloud Developer Exam cost
Google Professional Cloud Developer exam cost is $120 USD(40% discount on retail price of $200 USD).
How to book Google Professional Cloud Developer Exams
The registration for the Google Professional Cloud Developer Exam follows the steps given below.
- Step 1: Visit the Google Cloud Webassessor Website
- Step 2: Sign in or sign up to your Google Cloud Webassessor account
- Step 3: Search for the exam name Google Professional Cloud Developer
- Step 4: Take the date of the exam, choose exam center and make further payment using payment method like credit/debit etc.
What is the duration, language, and format of Google Professional Cloud Developer Exam
- Format: Multiple choices, multiple select
- Length of Examination: 240 minutes
- Number of Questions: 50-60
- Passing score: 80%
- Language: English
- Recommended experience: 3+ years of industry experience including 1+ years designing and managing solutions using GCP.
Google Professional Cloud Developer Certified Professional salary
The average salary of a Google Professional Cloud Developer Certified Expert in
- United State - 181,247 USD
- India - 27,42,327 INR
- Europe - 145,347 EURO
- England - 135,632 POUND
The benefit of obtaining the Google Professional Cloud Developer Exam Certification
- Google Professional Cloud Developer Certification is distinguished among competitors. Google Professional Cloud Developer certification can give them an edge at that time easily when candidates appear for employment interview, employers are very fascinated to note one thing that differentiates the individual from all other candidates.
- Google Professional Cloud Developer certification has more useful and relevant networks that help them in setting career goals for themselves. Google Professional Cloud Developer networks provide them with the correct career guidance than non certified generally are unable to get.
- Google Professional Cloud Developer will be confident and stand different from others as their skills are more trained than non-certified professionals.
- Google Professional Cloud Developer Exam provide proven knowledge to use the tools to complete the task efficiently and cost effectively than the other non-certified professionals lack in doing so.
- Google Professional Cloud Developer Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
- Google Professional Cloud Developer Certifications provide opportunities to get a job easily in which they are interested in instead of wasting years and ending without getting any experience.
Difficulty in writing the Google Professional Cloud Developer Exam
Believe you must have decided to appear for the Google Cloud Developer Certifications, This is one of the most toughest exam conducted by the Google, if you are not from a development background and trying to appear for this exam and then this exam would go very hard for you to crack it down, still if you had done your homework properly and prepared through Google docs, Exam questions practice then definitely you will able to nail down this exam.
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For more info visit:
Security & Identity Fundamentals Kubernetes in the Google Cloud Google Cloud documentation Google Cloud solutions