GCP (Google Cloud Platform)
What is GCP?
GCP stands for Google Cloud Platform and is the collective name for cloud services provided by Google. Services such as Google Search, Google Maps, Gmail, and YouTube also run on GCP. Originally, services were provided separately, such as Google App Engine, a PaaS service released in 2008, BigQuery, a big data analytics service released in 2011, and Google Compute Engine, an IaaS service released in 2012. In 2013, these services were integrated and provided as Google Cloud Platform.
By using technologies and infrastructure actually used inside Google, efficient web development and operations are possible. Advanced technologies such as data analysis and machine learning, which are also Google strengths, can also be used.
What can you do with GCP?
Because GCP is a cloud service, you can use Google’s advanced technology while reducing introduction and operation costs, without preparing machines, networks, infrastructure, or development platforms yourself. You can do many things with GCP, but the following are representative examples.
Demand forecasting
GCP is characterized by excellent AI and data processing technologies. Customer data can be used for demand forecasting.
Data operations
BigQuery, provided by GCP, is a tool that simplifies data analysis and operations. It can greatly reduce the time and effort required to prepare data analysis and improve operational efficiency. BigQuery can also integrate with Google Analytics 4, enabling Google Analytics data to be analyzed through BigQuery.
Environment that can handle sudden load
GCP provides an environment that can withstand sudden load increases. Even when load rises sharply, it can distribute load and autoscale much faster than many other services.
Game development
Using App Engine, which is fully managed and has excellent autoscaling performance, makes game development possible with small teams and low cost.
Image classification
With AutoML, even without expertise in machine learning, users can create highly accurate models using AI technology simply by setting required items intuitively.
Changing the way work is done
Using Google Workspace can improve work efficiency and also change communication methods.
Benefits of using GCP
In addition to development using Google’s technology, GCP has several benefits in cost and convenience.
Costs can be reduced.
First, GCP has the advantage of relatively low cost. This benefit is easy to understand when comparing GCP with similar services such as AWS and Azure.
Services using the latest technologies are available.
GCP also provides services that use cutting-edge technologies for data analysis and machine learning. Similar services exist in AWS and Azure, but GCP services are known for high performance.
Work can be made more efficient.
Finally, Google handles massive amounts of data every day and can use that experience to perform data analysis efficiently. It is especially characterized by fast data processing, enabling analysis with speed.
Services provided by GCP
Computing
Compute Engine
Compute Engine is an IaaS service provided by Google that provides virtual machines in the cloud. Infrastructure environments such as virtual machines and networks can be used in the cloud, reducing deployment and operation costs.
App Engine
App Engine is a PaaS service provided by Google that provides a platform for running applications in the cloud. It enables app development in a stable environment provided by Google, requires no maintenance, and lets developers focus on development.
Storage
Cloud Storage
Cloud Storage is a highly available object storage service. It has unlimited capacity and automatic backup features, so it can be used not only as a place to store files but also to publish them on the web.
Cloud Datastore
Cloud Datastore is a fully managed NoSQL database. It can automatically scale as needed, enabling high-load processing to run quickly. NoSQL refers to databases that do not use the SQL language and are suitable for handling big data.
Big data
BigQuery
BigQuery is a service for analyzing big data in the cloud at high speed. With BigQuery, 250 million transaction records can be processed in about two and a half minutes, enabling real-time user data analysis.
Cloud Dataflow
Cloud Dataflow is a fully managed processing service that simplifies stream processing for massive real-time data and batch processing. It provides a programming model that integrates a wide range of processing patterns from data acquisition through transformation, analysis, and classification, reducing operational work such as resource management and performance optimization.
Services
Cloud DNS
Cloud DNS is a service that provides reliable and high-performance DNS from Google. DNS converts IP addresses into human-readable strings and is essential for domain management. Cloud DNS can be used to create DNS records.
Translate API
Translate API is an API that can detect and translate strings received through an API regardless of language. When integrated with Google Translate, it can instantly translate between thousands of languages, making multilingual communication easier.
Difference between GCP and AWS
A cloud service often compared with GCP is AWS, provided by Amazon. Like GCP, AWS provides a stable environment and is used by many companies.
There are two major differences between these cloud services.
GCP’s advantage is that it can use Google’s infrastructure. In particular, its services for big data analysis and machine learning using the latest technologies are strengths compared with other cloud services.
AWS, on the other hand, provides a rich set of services and enables flexible web development, including complex system construction. However, because there are so many services, design can easily become complex and specialized knowledge is required.
GCP is strong in data analysis, while AWS is flexible and broad in use. Since each has different strengths, it is best to choose based on the use case.