Shortest course for Google-PCD exam in our Google-PCD Free Exam PDF

Assuming you are intrigued to confront the Google Professional Cloud Developer test to take the risk to qualify, killexams.com has accurate Google-PCD test inquiries with a reason to ensure you breeze through Google-PCD test effectively by rehearsing Google-PCD test questions. We offer you the legitimate, most recent cutting-edge Google-PCD study guide with a 100 percent unconditional promise.

Containing Latest 2024 Updated Professional Cloud Developer Syllabus Questions
Google-PCD cheatsheet of actual Questions

Practice Tests with actual Google-PCD exam Questions - Updated on Daily Basis
100% Pass Guarantee

Pass4sure Google-PCD Professional Cloud Developer exam Exam dumps
We have legit and sophisticated Google-PCD exam questions that are done up of Google-PCD Exam Braindumps, tested and also Tested through our certified team. killexams.com gives the most particular and most accurate exam real questions which virtually involves most test themes. With the data bank of our Google-PCD exam dumps, you do not have to risk your own chance about memorizing Google-PCD textbooks however surely need 24 hrs to get ready to the real Google-PCD exam.

Online is condensed along with Google-PCD dumps workers nevertheless, almost all all of them are providing outdated along with inaccurate Google-PCD queries. You require in order to do wrestle Legitimate along with 2022 Up-to-date Google-PCD Exam Questions provider on the web. This is significantly much better in the event that a person desire not so as to waste all their period with research, merely trust surrounding the greatest Google-PCD dumps company killexams.com, spending several dollars with incorrect along with out-of-date Google-PCD Exam Questions concerns. Just Acquire totally free Google-PCD Exam Questions inquiries. A person will likely be certainly pleased. Setup a great account in order to download the modern and legitimate Google-PCD PDF Questions made up of Real Google-PCD questions. Acquire Google-PCD VCE practice analyze with regard to nonstop exercise along with training.

Top features of Killexams Google-PCD Exam Questions
-> Fast Google-PCD Exam Questions download Accessibility
-> Comprehensive Google-PCD Questions along with Answers
-> 98% Success Price of Google-PCD exam
-> Certain actual Google-PCD exam questions
-> Google-PCD Concerns Updated with Regular foundation.
-> Valid along with 2022 Up-to-date Google-PCD Quiz Dumps
-> totally Portable Google-PCD exam Data files
-> Full highlighted Google-PCD VCE exam Sim
-> No Limitation on Google-PCD exam Acquire Access
-> Excellent Discount Coupons
-> totally Secured Acquire Account
-> totally Confidentiality Ascertained
-> 100% Achievements certain
-> totally Free PDF Download sample Questions
-> No Undetectable Cost
-> Simply no Monthly Rates
-> No Intelligent Account Repair
-> Google-PCD Quiz Update Excitation by E mail
-> Free Tech support team

Quiz Detail with: https://killexams.com/pass4sure/exam-detail/Google-PCD
Costs Details with: https://killexams.com/exam-price-comparison/Google-PCD
Observe Complete Collection: https://killexams.com/vendors-exam-list

Discount Discount on Complete Google-PCD Exam Questions Exam Questions;
WC2020: 60 per cent Flat Low cost on each exam
PROF17: 10% Further Low cost on Benefit Greater than $69
DEAL17: 15% Further Low cost on Benefit Greater than 99 dollars

A Professional Cloud Developer builds scalable and highly available applications using Google-recommended practices and tools that leverage fully managed services. This individual has experience with cloud-native applications, runtime environments, developer tools, and next-generation databases. A Professional Cloud Developer also has proficiency with at least one general-purpose programming language and is skilled at producing meaningful metrics and logs to debug and trace code.



The Professional Cloud Developer exam assesses your ability to:

Design highly scalable, available, and reliable cloud-native applications

Build and test applications

Deploy applications

Integrate Google Cloud Platform services

Manage application performance monitoring



A Professional Cloud Developer builds scalable and highly available applications using Google-recommended practices and tools that leverage fully managed services. This individual has experience with cloud-native applications, runtime environments, developer tools, and next-generation databases. A Professional Cloud Developer also has proficiency with at least one general-purpose programming language and is skilled at producing meaningful metrics and logs to debug and trace code.



Section 1: Designing highly scalable, available, and reliable cloud-native applications

1.1 Designing high-performing applications and APIs. Considerations include:

- 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



1.2 Designing secure applications. Considerations include:

- 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



1.3 Managing application data. Tasks include:

- 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



1.4 Refactoring applications to migrate to Google Cloud. Tasks include:

- Using managed services

- Migrating a monolith to microservices

- Google-recommended practices and documentation



Section 2: Building and Testing Applications

2.1 Setting up your local development environment. Considerations include:

- Emulating Google Cloud services for local application development

- Creating Google Cloud projects



2.2 Writing code. Considerations include:

- Algorithm design

- Modern application patterns

- Efficiency

- Agile software development

- Unit testing



2.3 Testing. Considerations include:

- Performance testing

- Integration testing

- Load testing



2.4 Building. Considerations include:

- 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



Section 3: Deploying applications

3.1 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



3.2 Deploying applications and services on Compute Engine. Tasks include:

- 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



3.3 Deploying applications and services to Google Kubernetes Engine (GKE). Tasks include:

- 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


3.4 Deploying a Cloud Function. Types include:

- 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



3.5 Using service accounts. Tasks include:

- Creating a service account according to the principle of least privilege

- Downloading and using a service account private key file



Section 4: Integrating Google Cloud Platform Services

4.1 Integrating an application with data and storage services. Tasks include:

- 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



4.2 Integrating an application with compute services. Tasks include:

- Implementing service discovery in Google Kubernetes Engine and Compute Engine

- memorizing 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



4.3 Integrating Google Cloud APIs with applications. Tasks include:

- 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



Section 5: Managing Application Performance Monitoring

5.1 Managing Compute Engine VMs. Tasks include:

- 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



5.2 Managing Google Kubernetes Engine workloads. Tasks include:

- Configuring logging and monitoring

- Analyzing container lifecycle events (e.g., CrashLoopBackOff, ImagePullErr)

- Analyzing logs

- Using external metrics and corresponding alerts

- Configuring workload autoscaling



5.3 Troubleshooting application performance. Tasks include:

- 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 applicationv
- Using documentation, forums, and Google support

Google Dumps