One of the leading cloud service providers is Google Cloud Platform (GCP), which offers business organisations options for their services. Any rookie will first find GCP confusing and might get overwhelmed and not start it. This is not true; once you understand the fundamentals, it will be simpler to start with cloud computing.
What is Google Cloud Platform (GCP)?
Google Cloud Platform is a set of cloud computing services offered by Google that provide platform as a service and serverless computing environments. GCP lets users develop, deploy, and scale applications and services on the same infrastructure Google uses for its services, such as Search and YouTube. We can now see some of GCP’s essential features, which are:
Compute Engine
Compute Engine is an IaaS offering that provides highly customisable virtual machines in GCP. It can scale from a few instances for small projects to thousands of cases for large-complex workloads, with high-performance VMs at its core.
Custom Machine Types: Custom Machine Types enable the custom configuration of machine types according to your workload’s specific requirements, including adjustments to the CPU, memory and disk configurations.
Global Availability: Compute Engine is available in several regions to ensure global low-latency services.
Auto-Scaling: Auto-Scaling supports elastic scaling based on demand, so you pay only for what you use, minimising cost.
Cloud Storage
Cloud Storage is a blend of object storage solution by Google designed to store any amount of data at any time. It is very appropriate for businesses that need to store vast volumes of unstructured data, including photos, videos and backups.
Multi-Regional and Regional Storage: Multi-regional storage provides redundancy across many regions, while regional storage is available for cost-effective, single-region storage.
High durability: Its rate is enormously high, so even when hardware fails, your data will not be lost and kept safely.
Lifecycle management: Automatically transition data from one storage class to another to optimise cost. For example, older data that is not accessed quite as frequently can be transitioned automatically to more frugal storage tiers.
BigQuery
BigQuery is GCP’s fully-managed, serverless data warehouse designed for large-scale data analytics. It lets you run SQL-like queries on large datasets at tremendous scale and speed, without having to manage underlying infrastructure.
Real-Time Analytics: BigQuery allows the analysis of enormous amounts of data in real-time, thus enabling businesses to make more timely and better decisions.
Serverless Architecture: It is a fully managed service; you don’t have to provide or maintain the hardware resources.
Integration with Google’s Ecosystem: This integration is seamless with other GCP services such as Dataflow, Dataproc, and Cloud Machine Learning Engine. That’s why BigQuery provides a powerful solution for combining data processing and analytics.
Kubernetes Engine
It is a managed environment for running, managing and scaling containerised applications. Containers represent a new best way to deploy application programs in consistent environments. Kubernetes is the leader among platforms for managing containerised applications at scale.
Auto-Scaling and Auto-Repair: GKE automatically scales your container clusters based on traffic and repairs failed nodes without downtime.
Security: GKE integrates with GCP’s system, which provides powerful protection for workloads.
Machine Learning
GCP boasts a full-fledged suite of AI and Machine Learning services, from pre-built models such as Vision AI and Natural Language Processing to tools for building custom models with TensorFlow.
AutoML: AutoML enables beginner developers to implement personalised models with very few lines of code, thereby altering AI development among people who lack deep technical expertise.
Pre-trained Models: These models allow developers to bring huge machine learning strengths into their applications with minimal effort on the developers side.
Cloud Platform
Google is always experimenting and developing new features and services for GCP. With the growing demand for cloud solutions, GCP will be a key product that helps businesses grow agile, data-driven and scalable.
Some of the future trends are:
Multi-Cloud Capabilities: GCP makes significant investments in multi-cloud solutions, allowing businesses to use Anthos to distribute workloads among many cloud providers.
Better AI and Machine Learning: More automation and improvements in AI services should make it easier for developers to implement machine learning models.
Conclusion
It is a broad platform that uses easy tools and services that beginners and experts can use. By mastering the following basic features: Compute Engine, Cloud Storage, BigQuery, and many more, you can use the power of cloud computing for projects or business. The London School of Emerging Technology (LSET) knows the value of such diverse platform professionals, which is why LSET brings you a Google Cloud Platform course for beginners. You can learn and craft your knowledge into action by getting into LSET’s internship programs, which help you start your career in the GCP field.