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Google Cloud Professional Cloud Developer Practice Exam

Course

GOOGLE CLOUD PROFESSIONAL CLOUD DEVELOPER PRACTICE EXAM

Category

Google Cloud Professional Cloud DeveloperTraining Insitute

Eligibility

Freshers and Career Changers

Mode

Regular Offline and Online Live Training

Batches

Week Days and Week Ends

Duration :

30 to 45 days

Google Cloud Professional Cloud Developer What will you learn?

•Learn to write Google Cloud Professional Cloud Developer Functions.
•How to create delete and view Google Cloud Professional Cloud Developer .
•Learn WebdriverIO Testing with real user scenario examples
•How to write Google Cloud Professional Cloud Developer from scratch (no experience required!)
•Learn How To Create Your Google Cloud Professional Cloud Developer In Easy Steps
•Learn how to write tests for error handling in Google Cloud Professional Cloud Developer .
•Understand and make use the new Features and Concepts in Google Cloud Professional Cloud Developer
•Learn Google Cloud Professional Cloud Developer . Become Developer in Test and Kick-start your Career in IT.
•Learn the essential skills to level-up from beginner to advanced Google Cloud Professional Cloud Developer developer in 2021!

Google Cloud Professional Cloud Developer Practice Exam Training Highlights

•Advanced Topics covered with examples
•Exercises and handouts after every session
•Learn Core concepts from Leading Instructors
•Online Training with 100% placement assistance
•Assignments and test to ensure concept absorption.
•We provide you with your recorded session for further Reference
•Training time :  Week Day / Week End – Any Day Any Time – Students can come and study
•Lifetime access to our 24×7 online support team who will resolve all your technical queries, through ticket based tracking system.

Who are eligible for Google Cloud Professional Cloud Developer

•.Net Developer, SilverLight, MVC3, Entity Framework 4, WCF, SQL/PLSQL, c#, SQL Server 2008, HTML5, .Net
•Embedded Technologies, Semiconductor Technologies, Web Services, Database Services, Cloud Computing, Industrial Automation, Ecommerce, Datbase Architect
•Java, J2EE, Machine Learning, Image Processing, UI Design, UX Developer, C++, Python, Perl
•QT Developer, STB Domain, CAS, UX DESIGNER, UI Developer, HTML5, CSS3, JAVAScript, JQUERY, FIREWORKS, Adobe Photoshop, Illustratot, Embedded C++
•ux, ui, Python Developers, Qa Automation, sales, Ui Development, Ux Design, Software Development, Python, Qa Testing, Automation Testing

GOOGLE CLOUD PROFESSIONAL CLOUD DEVELOPER PRACTICE EXAM

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 next generation databases, runtime environments and developer tools. They also have proficiency with at least one general purpose programming language and are skilled with using Stackdriver to produce meaningful metrics and logs to debug and trace code Sample case study Some of the questions on the Professional Cloud Developer certification exam may refer you to a case study that describes a fictitious business and solution concept. This case study is intended to provide additional context to help you choose your answer(s). We recommend that you review the sample case study that may be used in the exam. HipLocal A Professional Google Cloud Developer builds scalable and highly available applications using Google recommended practices and tools that leverage fully managed services. They have hands on experience with next generation databases, runtime environments and developer tools. This individual has proficiency with at least one general purpose programming language to define new APIs and invoke Google APIs and are skilled with using Stackdriver to produce meaningful metrics and logs to debug and trace code. *Note: The exam does not directly assess coding skill. It focuses on your ability to leverage GCP services and recommended practices in order to build, test, deploy, and manage scalable and highly available applications. If you are proficient in at least one general purpose coding language, you should be able to interpret any questions that present code snippets. 1. Designing highly scalable, available, and reliable cloud-native applications 1.1 Designing performant applications and APIs. Considerations include: Infrastructure as a Service vs. Container as a Service vs. Platform as a Service (e.g., autoscaling implications) Portability vs. platform-specific design Evaluating different services and technologies Operating system versions and base runtimes of services Geographic distribution of Google Cloud services Microservices Defining a key structure for high write applications using Cloud Storage, Cloud Bigtable, Cloud Spanner, or Cloud SQL Session management Deploying and securing an API with cloud endpoints Loosely coupled applications using asynchronous Cloud Pub/Sub events Health checks Google-recommended practices and documentation 1.2 Designing secure applications. Considerations include: Applicable regulatory requirements and legislation Security mechanisms that protect services and resources Storing and rotating secrets IAM roles for users/groups/service accounts HTTPs certificates Google-recommended practices and documentation 1.3 Managing application data. Tasks include: Defining database schemas for Google-managed databases (e.g., Cloud Datastore, Cloud Spanner, Cloud Bigtable, BigQuery) Choosing data storage options based on use case considerations, such as: Cloud Storage signed URLs for user-uploaded content Using Cloud Storage to run a static website Structured vs. unstructured data ACID transactions vs. analytics processing Data volume Frequency of data access in Cloud Storage Working with data ingestion systems (e.g., Cloud Pub/Sub, Storage Transfer Service) Following Google-recommended practices and documentation 1.4 Re-architecting applications from local services to Google Cloud Platform. Tasks include: Using managed services Using the strangler pattern for migration Google-recommended practices and documentation 2. Building and Testing Applications 2.1 Setting up your development environment. Considerations include: Emulating GCP services for local application development Creating GCP projects 2.2 Building a continuous integration pipeline. Considerations include: Creating a Cloud Source Repository and committing code to it Creating container images from code Developing unit tests for all code written Developing an integration pipeline using services (e.g., Cloud Build, Container Registry) to deploy the application to the target environment (e.g., development, test, staging) Reviewing test results of continuous integration pipeline 2.3 Testing. Considerations include: Performance testing Integration testing Load testing 2.4 Writing code. Considerations include: Algorithm design Modern application patterns Efficiency Agile methodology 3. Deploying applications 3.1 Implementing appropriate deployment strategies based on the target compute environment (Compute Engine, Google Kubernetes Engine, App Engine). Strategies include: Blue/green deployments Traffic-splitting deployments Rolling deployments Canary deployments 3.2 Deploying applications and services on Compute Engine. Tasks include: Launching a compute instance using GCP Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys) Moving a persistent disk to different VM Creating an autoscaled managed instance group using an instance template Generating/uploading a custom SSH key for instances Configuring a VM for Stackdriver monitoring and logging Creating an instance with a startup script that installs software Creating custom metadata tags Creating a load balancer for Compute Engine instances 3.3 Deploying applications and services on Google Kubernetes Engine. Tasks include: Deploying a GKE cluster Deploying a containerized application to GKE Configuring GKE application monitoring and logging Creating a load balancer for GKE instances Building a container image using Cloud Build 3.4 Deploying an application to App Engine. Considerations include: Scaling configuration Versions Traffic splitting Blue/green deployment 3.5 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 3.6 Creating data storage resources. Tasks include: Creating a Cloud Repository Creating a Cloud SQL instance Creating composite indexes in Cloud Datastore Creating BigQuery datasets Planning and deploying Cloud Spanner Creating a Cloud Storage bucket Creating a Cloud Storage bucket and selecting appropriate storage class Creating a Cloud Pub/Sub topic 3.7 Deploying and implementing networking resources. Tasks include: Creating an auto mode VPC with subnets Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, Tags, Service accounts) Setting up a domain using Cloud DNS 3.8 Automating resource provisioning with Deployment Manager 3.9 Managing Service accounts. Tasks include: Creating a service account with a minimum number of scopes required Downloading and using a service account private key file 4. Integrating Google Cloud Platform Services 4.1 Integrating an application with Data and Storage services. Tasks include: Enabling BigQuery and setting permissions on a dataset Writing an SQL query to retrieve data from relational databases Analyzing data using BigQuery Fetching data from various databases Enabling Cloud SQL and configuring an instance Connecting to a Cloud SQL instance Enabling Cloud Spanner and configuring an instance Creating an application that uses Cloud Spanner Configuring a Cloud Pub/Sub push subscription to call an endpoint Connecting to and running a Cloud SQL query Storing and retrieving objects from Google Storage Publishing and consuming from Data Ingestion sources Reading and updating an entity in a Cloud Datastore transaction from an application Using the CLI tools Provisioning and configuring networks 4.2 Integrating an application with compute services. Tasks include: Implementing service discovery in Google Kubernetes Engine, App Engine, and Compute Engine Writing an application that publishes/consumes from Cloud Pub/Sub Reading instance metadata to obtain application configuration Authenticating users by using Oauth2 Web Flow and Identity Aware Proxy Using the CLI tools Configuring compute services network settings (e.g., subnet, firewall ingress/egress, public/private IPs) 4.3 Integrating Google Cloud APIs with applications. Tasks include: Enabling a GCP API Using pre-trained Google ML APIs Makin

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Python

you’ll learn how to use python for professional programming. You will learn how to create a python application, and how to organize files and folders so that your code is easy to read and understand.

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Data science

 Data science is a broad and ever-evolving field, with opportunities for specialists in many subject areas, as well as generalists who can apply data science techniques and tools to new fields.

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Azure cloud

Cloud computing provides processing power and storage to millions of businesses and consumers. In this blog, we will discuss the importance of the cloud to businesses and consumers.

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Web Designing

Web designing is the process of designing a website by using many different languages, software, and programs. To have an effective website, it should be easy to use, accessible 
 

Frequently Asked Questions

You should check the all out class plan with the goal that you find out about how long you will get for self-study and amendment. A few institutions can’t finish courses even 30 days before the classes, which makes it hard for understudies to change and practice those themes.

To address this inquiry appropriately, you should initially be clear about your own learning destinations. In the event that you don’t have the foggiest idea why you are joining to a program you should pause and respite. In the event that you are going to contribute an extra four to six hours per week on top of an all around occupied proficient and day to day life, wearing exercises and additionally different pastimes, you should initially be extremely clear on what you need from this experience.

A serious online learning provider will not leave you to your own devices. A self-study program that relies on you having an iron will to wade through multiple screens with no feedback or support mechanism is akin to watching paint dry and the chances are that you will not learn much. If, on the other hand, you have a coach who helps you reflect not only on what you have seen and read but, more importantly, on what you have applied, you’re well on the way from knowledge consumption to learning application.

A wretched program prompts inadequately inspired students and a shortage of gold awards. What’s a decent number? IMD’s open online projects have a fruition rate in overabundance of 90%. It’s uncommon that our students don’t finish and it’s considerably more extraordinary that they have not had an important learning experience

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IT Consulting

online training is the No.1 driving preparing foundation in Hyderabad offering end of the week preparation in Java, python, data science, azure cloud, web designing online training.

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We have the best workforce with great Lab Infrastructure alongside nitty gritty course material.

Online Training

We offer the greater part of the course online with virtual homeroom to serve the IT applicants. 

Corporate Training

We have encountered workforce to prepare experts for improving their innovation abilities to everyday necessities.

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Undertaking Training Get Trained from anyplace with an Internet association. Educators instruct understudies in a study hall and you can go to these courses online progressively too

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onlinetrianings.in is no1 Leading preparing Institute in Hyderabad offering study hall preparing on python, data science, azure cloud, web designing.

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