Hire GCP Architect

Google Cloud Platform (GCP) is a suite of cloud computing services offered by Google. It provides a range of services including compute, storage, databases, analytics, machine learning, networking, and more. GCP allows businesses to build, deploy, and manage applications and services on the same infrastructure that Google uses for its own products, like Search and YouTube.
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How to hire champion GCP Architect?

Hiring a champion GCP architect requires a thorough understanding of the skills and qualities that are required to be successful in the role. Here are some steps that you can follow to hire a champion GCP architect:
 
  1. Define the job description: Define the job requirements, responsibilities, and qualifications for the role. This includes technical skills, experience with GCP, and soft skills like communication, problem-solving, and collaboration.
  2. Source candidates: Reach out to your professional network, post the job on job boards, and use recruiting tools to find potential candidates. You can also leverage social media and attend industry events to find qualified candidates.
  3. Screen resumes: Review resumes and cover letters to identify candidates who meet the job requirements and have relevant experience with GCP.
  4. Conduct technical interviews: Conduct technical interviews to assess the candidate’s technical skills and experience with GCP. Ask questions related to GCP services, architecture, security, and deployment.
  5. Conduct behavioral interviews: Conduct behavioral interviews to assess the candidate’s soft skills, including communication, problem-solving, and collaboration.
  6. Check references: Contact references to validate the candidate’s skills, experience, and work ethic.
  7. Offer the job: Once you have identified the best candidate, make an offer that includes compensation, benefits, and any other relevant details.
 
It’s important to note that hiring a champion GCP architect can be a challenging process, especially in a competitive market. It’s essential to prioritize skills, experience, and cultural fit to ensure that the candidate will be successful in the role and make a positive impact on your organization. Hire now on TechKluster

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As a GCP programmer, you have the opportunity to register on our platform and enter into the talent pool. This talent pool is a carefully curated list of GCP programmers who have demonstrated exceptional programming skills and expertise in the GCP language.

By being a part of the talent pool, you will have access to top-tier job opportunities from the world’s leading companies and startups. Our team works tirelessly to connect you with the best possible opportunities, giving you the chance to work on exciting projects and develop your skills even further.

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Frequently Asked Questions

All developers on TechKluster are pre-vetted and pre-verified for their skills and background, so you can be sure that the GCP Architect you hire has the qualifications and experience you need.
Yes, you can hire a GCP Architect for a short term (minimum 6 months) and long term on TechKluster. For your custom requirements, you can post requisition on the platform and our team will help you to find the right fit.
No, we currently do not support hiring on an hourly basis.
Monthly compensation for a GCP Architect on TechKluster varies depending on their experience and location.
Payment for hiring a GCP Architect on TechKluster is handled through the platform’s secure payment system. You will receive an invoice for a resource a hired resource. There are payment options to do wire transfer and credit/debit cards.
If you are not satisfied with the work of a GCP Architect you hire on TechKluster, you can discuss the issue with the developer and attempt to resolve it. If you are still not satisfied, you can request a refund through TechKluster’s dispute resolution process.
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Developers Resource Center

TechKluster is committed to help GCP Architect community to achieve their career goals, our developer resource center for GCP provides the useful resources which not only will help you succeed at TechKluster but everywhere in your development career. For suggestions email us at gcp@techkluster.com

Table of Contents

GCP Fundamentals

Google Cloud Platform (GCP) is a suite of cloud computing services offered by Google. It provides a range of services including compute, storage, databases, analytics, machine learning, networking, and more. GCP allows businesses to build, deploy, and manage applications and services on the same infrastructure that Google uses for its own products, like Search and YouTube.

Core Fundamentals:

Compute Engine:

A virtual machine that runs on Google's infrastructure. Compute Engine allows businesses to run workloads in a virtual machine environment.

Cloud Storage:

A scalable, durable, and highly available object storage service. Cloud Storage allows businesses to store and access data from anywhere in the world.

Cloud SQL:

A fully managed relational database service. Cloud SQL allows businesses to easily create and manage databases in the cloud.

Cloud Datastore:

A NoSQL document database service. Cloud Datastore allows businesses to store and access structured data in the cloud.

Cloud Pub/Sub:

A messaging service that allows businesses to send and receive messages between independent applications.

BigQuery:

A fully managed data warehouse that allows businesses to analyze large data sets in real-time.

Services:

Compute:

Compute Engine, Kubernetes Engine, App Engine, Cloud Functions

Storage:

Cloud Storage, Persistent Disk, Cloud Filestore

Databases:

Cloud SQL, Cloud Spanner, Cloud Firestore, Cloud Bigtable

Networking:

Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud CDN

Big Data:

BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Pub/Sub

Machine Learning:

AI Platform, Cloud AutoML, Cloud TPU, Cloud Vision API

Usage:

GCP can be used by businesses of all sizes, from small startups to large enterprises. It is commonly used for developing and deploying web applications, running batch processing and data analysis workloads, and building machine learning models. GCP can be accessed through the Cloud Console, command-line tools, or APIs.

Cost:

GCP offers flexible pricing models, with options for pay-as-you-go, sustained use discounts, and committed use discounts. The cost of using GCP varies depending on the specific services used, the amount of data processed, and the duration of use. GCP also offers a free tier that includes a limited amount of usage for select services, and a 12-month free trial with $300 in credit to use any GCP service. GCP provides cost calculators and monitoring tools to help businesses manage and optimize their usage and costs.

Deploying a Simple Web Application in GCP

Here are the steps to deploy a simple web application in GCP:
 
  1. Create a Project: Create a new project in the GCP console or use an existing one. Select the project you want to use for your web application.
  2. Create a Virtual Machine: Create a virtual machine to host your web application using Compute Engine. Select the operating system, instance size, and disk type.
  3. Install and Configure Web Server: Install and configure a web server like Apache or Nginx on your virtual machine. This will allow you to serve web pages to users.
  4. Upload Your Web Application: Upload your web application files to the virtual machine. This can be done using SSH or other file transfer methods like FTP.
  5. Set up Firewall Rules: Create firewall rules to allow traffic to reach your web application. This can be done using the GCP console or command-line tools.
  6. Configure Domain Name: Configure your domain name to point to the IP address of your virtual machine. This can be done using a domain registrar or DNS provider.
  7. Test Your Application: Test your web application by visiting your domain name in a web browser. You should be able to see your web application running on the virtual machine.
 
Once your web application is deployed, you can monitor and manage it using GCP’s monitoring and logging tools. You can also use GCP’s load balancing and scaling features to handle increased traffic and improve performance.

GCP Learning Resources

Here are some GCP online learning resources and books:

Online Learning Resources:

  1. Google Cloud Platform Fundamentals: This is a free online course provided by Google that covers the fundamentals of GCP. It includes video lectures, hands-on labs, and quizzes.
  2. Coursera: Coursera offers a range of GCP courses, including “Architecting with Google Cloud Platform,” “Data Engineering on Google Cloud Platform,” and “Machine Learning with TensorFlow on Google Cloud Platform.”
  3. Qwiklabs: Qwiklabs provides hands-on labs for GCP that allow users to practice using the platform and its services.
  4. Pluralsight: Pluralsight offers GCP courses for beginners and advanced users. Topics include GCP architecture, data storage, and machine learning.
  5. Udemy: Udemy offers a range of GCP courses, including “Google Cloud Platform Certification – Cloud Architect,” “Google Cloud Platform – GCP – For Techs,” and “Google Cloud Platform Big Data and Machine Learning Fundamentals.”

Books:

  1. “Google Cloud Platform in Action” by JJ Geewax: This book provides an introduction to GCP and covers topics like GCP architecture, storage, and networking.
  2. “Hands-On Cloud Administration in Azure and Google Cloud” by Sander van Vugt: This book covers both GCP and Azure and provides practical examples of how to use the platforms for cloud administration.
  3. “Google Cloud Platform Cookbook” by Juraj Misina: This book provides a collection of recipes for working with GCP services, including compute, storage, and networking.
  4. “Mastering Google Cloud Platform” by V Kishore Ayyadevara: This book covers advanced topics like GCP networking, machine learning, and data analytics.
  5. “Google Cloud Platform for Developers: Build highly scalable cloud solutions with the latest GCP features and techniques” by Ted Hunter: This book provides a developer-focused introduction to GCP and covers topics like GCP APIs, app deployment, and data storage.

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