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).

High-quality product

Our Professional-Cloud-Developer exam training vce renews questions according the original questions pool, which closely simulates the real Professional-Cloud-Developer exam questions and reach a high hit rate. Within one year after you purchase our product, we offer free updated Professional-Cloud-Developer renewal questions by email. Statistics indicate that 99% of our clients pass the Professional-Cloud-Developer actual exam successfully, who highly comment our product for its high performance.

Convenience

Our system will send you the Professional-Cloud-Developer vce study material automatically with e-mail after you purchase it (approximately in 10 minutes). As a famous saying goes, time is money. It requires a little time to do practice before taking Professional-Cloud-Developer exam. You just need to click in the link and sign in, and then you are able to use our Professional-Cloud-Developer test prep engine immediately, which enormously save you time and enhance your efficiency.

Multiple guarantees for passing

We have multiple guarantees for passing Professional-Cloud-Developer exam. Firstly, if you are confused about our product's quality, you are able to download Professional-Cloud-Developer free demos before you purchase it. Surely the whole content is more useful than demos. Secondly, Professional-Cloud-Developer valid exam engine is a high hit-rate product, which help 99% of our clients successfully pass the Google Professional-Cloud-Developer actual test. Lastly and most significantly, you would be welcome to get full refund if you unfortunately failed Professional-Cloud-Developer exam. The only thing you need to do is to upload your failed exam result, and we will handle it soon. By the way, we highly recommend that we offer you another dump in free to prepare for the next exam instead of refund, for our confidence of the quality of our products.

Troubled in Professional-Cloud-Developer exam

There are too many key point of Professional-Cloud-Developer latest real test on the book to remember. Some people are too busy to prepare for the Professional-Cloud-Developer exam test due to the realistic reasons. While, when you encountered so many difficulties during the preparation, you have little faith to pass the Google actual test. We know all your troubles. Therefore we are dedicated to develop Professional-Cloud-Developer updated study vce to help you get Google exam certificate easier and sooner.

It's a great pleasure for our product, Professional-Cloud-Developer valid exam engine, to capture your attention. There is no secret for Google exam certificate. We sincerely hope our product can help you pass Google exam.

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.

The Google Professional Cloud Developer certificate is intended to validate the competence of IT professionals tasked with building highly available and scalable applications with the aid of Google endorsed practices and tools. Such individuals will have to demonstrate an understanding of developer tools, cloud-native applications, modern databases, and managed services during the corresponding exam. What’s more, targeted specialists need to have background experience working with at least one programming language and should be proficient in creating useful metrics and logs for debugging and trace coding.

Reference: https://cloud.google.com/certification/cloud-developer

Three different version for successfully pass

What you need to do is focus on our Professional-Cloud-Developer exam training vce, and leaves the rest to us. For one thing, we make deal with Credit Card, which is more convenient and secure. For another, we offer 3 versions of Professional-Cloud-Developer practice exam torrent for download, PDF, software and App. Google Certified Professional - Cloud Developer PDF version is for making notes, where you can tag key points to form an initial impression. Professional-Cloud-Developer online test engine enable you to review anytime anywhere, no matter on bus, in restaurant, or on bed. It support any electronics, IPhone, Android or Windows. You need to load in the first time and then you are able to use it offline. With practices, knowledge is deeply consolidated in your mind. Lastly, you're supposed to do mock exam on computer with our Professional-Cloud-Developer : Google Certified Professional - Cloud Developer software test engine (only support Windows, but account of installation are not limited). With multiple practices, you are tremendously probable to pass Professional-Cloud-Developer exam.

If you have confusions, suggestions or complaints on Google Professional-Cloud-Developer practice engine, please contact us. We supply 24/7 customer service.

After purchase, Instant Download: Upon successful payment, Our systems will automatically send the product you have purchased to your mailbox by email. (If not received within 12 hours, please contact us. Note: don't forget to check your spam.)

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

• User session management
• Evaluating different services and technologies
• Defining a key structure for high-write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL
• Caching solutions
• Google-recommended practices and documentation
• Scaling velocity characteristics/tradeoffs of IaaS (infrastructure as a service) vs. CaaS (container as a service) vs. PaaS (platform as a service)
• Graceful shutdown on platform termination
• Loosely coupled applications using asynchronous Cloud Pub/Sub events
• Deploying and securing API services
• Geographic distribution of Google Cloud services (e.g., latency, regional services, zonal services)
• Microservices

Designing secure applications

• Implementing requirements that are relevant for applicable regulations (e.g., data wipeout)
• Storing and rotating application secrets using Cloud KMS
• Securing service-to-service communications (e.g., service mesh, Kubernetes network policies, and Kubernetes namespaces)
• Security mechanisms that protect services and resources
• Security mechanisms that secure/scan application binaries and manifests
• IAM roles for users/groups/service accounts
• Certificate-based authentication (e.g., SSL, mTLS)
• Google-recommended practices and documentation
• Set compute/workload identity to least privileged access
• Authenticating to Google services (e.g., application default credentials, JWT, OAuth 2.0)

Managing application data

• Cloud Storage-signed URLs for user-uploaded content
• Choosing data storage options based on use case considerations, such as:
• Strong vs. eventual consistency
• Structured vs. unstructured data
• Frequency of data access in Cloud Storage
• Defining database schemas for Google-managed databases (e.g., Cloud Firestore, Cloud Spanner, Cloud Bigtable, Cloud SQL)
• Data volume
• Following Google-recommended practices and documentation

Refactoring applications to migrate to Google Cloud

• Migrating a monolith to microservices
• Using managed services
• 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

• Modern application patterns
• Unit testing
• Algorithm design
• Agile software development
• Efficiency

Testing

• Integration testing
• Performance testing
• Load testing

Building

• Developing a continuous integration pipeline using services (e.g., Cloud Build, Container Registry) that construct deployment artifacts
• Creating container images from code
• Reviewing and improving continuous integration pipeline efficacy
• Creating a Cloud Source Repository and committing code to it

3 Deploying applications

Recommend appropriate deployment strategies for the target compute environment (Compute Engine, Google Kubernetes Engine). Strategies include:

• Traffic-splitting deployments
• Canary deployments
• Rolling deployments
• Blue/green deployments

Deploying applications and services on Compute Engine

• Exporting application logs and metrics
• Manually updating dependencies on a VM
• Managing Compute Engine VM images and binaries
• Modifying the VM service account
• Installing an application into a VM

Deploying applications and services to Google Kubernetes Engine (GKE)

• Defining workload specifications (e.g., resource requirements)
• Configuring application accessibility to user traffic and other services
• Define deployments, services, and pod configurations
• Configuring Kubernetes namespaces and access control
• Managing container lifecycle
• Deploying a containerized application to GKE
• Building a container image using Cloud Build
• Managing Kubernetes RBAC and Google Cloud IAM relationship

Deploying a Cloud Function

• Cloud Functions that are invoked via HTTP
• Securing Cloud Functions
• Cloud Functions that are triggered via an event (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)

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)
• Storing and retrieving objects from Cloud Storage
• Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
• Writing an application that publishes/consumes data asynchronously (e.g., from Cloud Pub/Sub)
• Connecting to a data store (e.g., Cloud SQL, Cloud Spanner, Cloud Firestore, Cloud Bigtable)

Integrating an application with compute services

• Implementing service discovery in Google Kubernetes Engine and Compute Engine
• Reading instance metadata to obtain application configuration
• Using the command-line interface (CLI), Google Cloud Console, and Cloud Shell tools
• Authenticating users by using OAuth2.0 Web Flow and Identity Aware Proxy

Integrating Google Cloud APIs with applications

• Batching requests
• Caching results
• Error handling (e.g., exponential backoff)
• Paginating results
• Using service accounts to make Google API calls
• Making API calls with a Cloud Client Library, the REST API, or the APIs Explorer, taking into consideration:
• Restricting return data
• Enabling a Google Cloud API

5 Managing Application Performance Monitoring

Managing Compute Engine VMs

• Analyzing logs
• Viewing syslogs from a VM
• Sending logs from a VM to Cloud Monitoring
• Inspecting resource utilization over time
• Analyzing a failed Compute Engine VM startup
• Debugging a custom VM image using the serial port

Managing Google Kubernetes Engine workloads

• Analyzing logs
• Configuring workload autoscaling
• Analyzing container lifecycle events (e.g., CrashLoopBackOff, ImagePullErr)
• Using external metrics and corresponding alerts
• Configuring logging and monitoring

Troubleshooting application performance

• Reviewing stack traces for error analysis
• Viewing logs in the Google Cloud Console
• Profiling performance of request-response
• Using documentation, forums, and Google support
• Graphing metrics
• Creating a monitoring dashboard
• Profiling services
• Using Cloud Debugger
• Exporting logs from Google Cloud
• Reviewing application performance (e.g., Cloud Trace, Prometheus, OpenCensus)
• Monitoring and profiling a running application
• Writing custom metrics and creating metrics from logs