What is Google Cloud Platform (GCP)? A Comprehensive Guide to Mastering Cloud Services

Cloud computing is turning into an essential key for organizations to handle their increasing data demands. Google Cloud Platform (GCP) is one of the most well-known and reliable cloud providers in the current market. Data storage has been rapidly moving into the cloud. This makes it essential for data analysts to have a firm knowledge of GCP.

In this article, you will get to know the basics of cloud computing, its pros and cons, its pricing model and certifications to solidify your understanding of Google Cloud Platform. Let's get into it.

What is Cloud Computing?

So, what is cloud computing?

It refers to a dispersed set of servers. These servers host IT infrastructure, databases and applications that can be easily accessible over the Internet or any other network. Initially, this term was extracted from old technical diagrams. These diagrams feature a cloud drawing to display networking infrastructure and servers making up the internet.

It demonstrates the on-demand availability of these computing resources for end users and businesses. It also looks after the management of IT infrastructure and servers, while the users can access scalable computing power and data storage on a pay-as-you-go model.

What is Google Cloud Platform?

Now, what is Google Cloud Platform?

It is Google’s suite of public cloud computing services and tools. These include relevant data analytics services, such as Looker Studio and Google BigQuery. Google’s global network of data center’s powers Google Cloud Platform. It runs on the same infrastructure as Google Docs, Google Drive and Gmail.

As mentioned before, It's quite beneficial for consultants and analysts to learn about GCP. It puts great emphasis on aspects of machine learning, data analytics, and artificial intelligence. This is what makes it a crucial tool for professionals.

Ever since Google has started its infrastructure to business users via a public cloud, it's been a massive success. Its tool suits if cloud services have been rapidly glowing. Cloud AI is the most recent addition to it. Data storage, app deployment, security, networking, computing resources, management tools and IoT are some of the other useful services to count.

For more information, you can read this article: What is Google Cloud Platform: All in One Guide to GCP

Pros and Cons of GCP

Every single service has its advantages and disadvantages for its users, so does Google Cloud Platform. Let's discuss some pros and cons of GCP to expand our understanding.

Pros

• Strong Focus on Innovation

Google has a strong emphasis on the consistent implementation of technological advancements. GCP customers and users are likely to take advantage of exciting and new technologies. Technologies such as artificial intelligence integration can be utilized by customers to analyze their data thoroughly.

• Extensive Range of Cloud Computing Services

There's an extensive range of cloud computing services easily available for end users and businesses. These services offered by GCP include networking, data storage, computing power, machine learning, API integration, data analytics and app deployment. These innumerable yet reliable services make it a great tool. This tool serves a perfect solution for companies with various or constantly changing cloud requirements.

• Enhanced Security

Google Cloud Platform offers reliable security options. These options include IAM (Identity and Access Management), KMS (Key Management Service), and SCC (Security Command Center). This gives upright and robust cybersecurity measures to organizations while handling their data remotely.

• Global Scope of Network Infrastructure

Organizations using Google Cloud Platform have easy access to Google’s powerful and globally spread network infrastructure. This allows the execution of multi-region redundancy. It also allows utilizing cheap locations for hosting the foremost workload.

Cons

• Complicated Pricing Model

GCP has relatively complicated pricing models as compared to other cloud providers. This factor makes it tough for organizations to manage and predict their expenses for cloud computing.

• Proprietary Platform

It is also essential to keep a note of the fact that GCP is proprietary. This factor makes it difficult to migrate data. It also becomes tough to deploy applications if a company wants to leave Google’s services. It can be more high-priced than cloud services from less known providers or open-source solutions.

• Limited Assistance

This platform offers comparatively limited support for some instances. Its support team could be difficult to access and might not turn out to be as responsive. These factors impact data availability and productivity in cases of ongoing problems with the cloud infrastructure.

Applications of GCP

Let's discuss some major applications of GCP.

• Data Storage - With Google BigQuery, businesses can use an enterprise-level data warehouse in GCP. In addition, Cloud SQL provides a database-as-a-service model for MySQL, PostgreSQL and Microsoft SQL Server databases. Cloud BigTable can be used for NoSQL databases and Cloud Storage offers options for unstructured data and large files like images.

• Business Intelligence - GCP’s integrated BI tool Looker Studio provides smooth data visualization and reporting directly on the platform. This allows data analysts and consultants to gain meaningful insights and build shareable visuals for presentations and consulting calls.

• Machine Learning - GCP also offers services to implement machine learning models such as Cloud AutoML and Cloud Machine Learning Engine. Businesses can use these tools to train, implement and validate their models directly in the cloud. This helps in automating and enhancing their business intelligence processes.

• IoT Management - This platform is ideal for managing a company-wide IoT (Internet of Things) network. Services for IoT device connection and management like Cloud IoT Core make it easy to set up and supervise various IoT devices.

• App Deployment - GCP can also be used to implement applications developed with Python, Java, Ruby, and other programming languages. This process is done by utilizing the service App Engine. This makes the process of hosting applications easy and swift for businesses.

• API Development - GCP has integrated tools such as Apigee API platform and developer portal for API development.

Google Cloud Platform’s Pricing Model

Users only pay for the services they utilize. This flexible factor is called a pay-as-you-go model . Google Cloud Platform’s pricing model can be quite complicated as the tools and services are priced separately. Cost estimation can be done using the GCP pricing calculator. It offers diverse tools to keep a track of your costs and spending. Let's discuss more about Google Cloud platform’s pricing model.

Free Tier

It offers a free tier which is a great option for users wanting to give a try to the platform. It allows you to learn about deploying small development projects and cloud computing. You can receive a free credit of $300 upon connecting your credit card. This credit can be used for your projects.

Free tier gives you an offer of using 20+ products. This includes Firestore, AutoML, Cloud Storage, BigQuery and Google kubernetes Engineer. In addition to that, a 30-day free trial is also offered by Looker to explore the data platform.

Product Pricing

• Looker - Pricing is compiled from platform costs to run Looker instance and user costs for licensing individual users.

• Google BigQuery- The computing cost to conduct SQL queries and amount of data you store in the warehouse decides the pricing.

• Google Bigtable -Pricing depends on the type of Bigtable instance and the number of nodes in the instance’s clusters, as well as the number of storage tables used and the amount of network bandwidth used.

• Compute Engine- Selecting the type of VMs you want decides the pricing.

• Cloud Storage -Pricing depends on the amount of data stored in buckets, data processing done by Google, and network usage (amount of data moved between buckets).

• AutoML - Pricing is decided individually for google cloud platform training online, implementing the and utilizing the model to make predictions

• Google Kubernetes Engine - Pricing depends on edition, computing resources, cluster operation mode, and cluster management fees.

Google Cloud Certifications

GCP offers a wide range of certifications to help you enhance your learning. Attaining one of these would validate your expertise, skills and potential to employers.

• Foundational Certification - It offers an in-depth knowledge of cloud technologies. This certification also provides a complete synopsis of the product suite provided by GCP. Candidates are not required to have any technical prerequisites. It is ideal for entry-level candidates.

• Associate Certification - This credential provides all the key skills to help you implement and manage cloud projects with GCP. It is definitely ideal for cloud engineers who already have in-depth experience in deploying cloud applications.

• Professional Certification - This credential offers advanced skills in implementing, designing and maintaining GCP products and projects. It is an ideal option for specialists with experience in setting up cloud workspaces.

Conclusion

It is safe to conclude that Google Cloud Platform stands as a robust and scalable cloud solution. It is curated to meet the diverse requirements and demands of modern businesses. This platform’s global infrastructure ensures high performance. As this platform continues to evolve itself in AI and sustainability, it remains a key tool for improving digital strategies and driver growth.