Explore Utility Computing Model Examples And Use Cases

Utility Computing Model

Computing resources including storage, processing power, and networking are made available on-demand and billed according to actual usage under the utility computing model, a framework for service delivery. It is comparable to how gas, water, and electricity are used and billed. This model is perfect for dynamic workloads and companies trying to cut expenses since it places an emphasis on scalability, cost-efficiency, and flexibility.

A key idea in cloud computing is the utility computing paradigm, which lets people and companies access top-notch IT services without having to own or maintain the infrastructure.

Utility Computing Example

Utility computing offers computer resources that are scalable and available whenever needed, much like public utilities like water or electricity. The following are actual instances of utility computing services and their uses:

Platforms for Cloud Computing

Amazon Web Services EC2 (AWS)

• Offers virtual servers on demand that may be scaled up or down in response to workload.
• Typical applications include managing extensive data processing activities, hosting web applications, and executing batch operations.

Google Cloud Compute Engine

• Makes containerized environments and scalable virtual machines (VMs) available.
• Workloads involving AI/ML, hosting applications, and rendering videos are common uses.

Virtual machines on Microsoft Azure

provides virtual machines (VMs) as cloud computing, storage, and networking solutions.
Common use: executing enterprise workloads on Linux or Windows.

Storage as a Useful Tool

Dropbox/OneDrive/Google Drive

• Systems for storing files in the cloud that bill according to usage and storage space.
• Common uses include teamwork, document sharing, and backups.

Simple Storage Service (S3 on AWS)

• Service for object storage with adjustable costs according to data amount and frequency of use.
• Large datasets, media assets, or backups are frequently hosted.

SaaS (Software-as-a-Service)

Salesforce CRM

• Software for customer relationship management (CRM) on the cloud that is paid for each user each month.
• Managing client data and sales pipelines is a common use.

G Suite, formerly known as Google Workspace

• Productivity apps with a subscription model, such as Google Sheets, Docs, and Gmail.
• Collaboration and team productivity are common uses.

Infrastructure as a Service (IaaS)

The Cloud Infrastructure of IBM

• On-demand networking, storage, and processing resources are offered.
• Operating enterprise-grade apps is a common use.

Ocean Droplets in Digital Form

• VAs that are scalable and priced according to CPU, RAM, and storage requirements.
• Hosting development environments, websites, and tiny apps are common uses.

Platform-as-a-Service (PaaS)

Heroku

• An application deployment and management platform for developers.
• Hosting web apps with automated scalability is a common use case.

Google App Engine

• A platform that provides completely managed hosting for applications.
• Building scalable online and mobile backends is a common use.

Pay-per-Use Analytics for Data

BigQuery in Google Cloud

• Based on the volume of data processed, serverless data warehouse services are priced.
• Analyzing big datasets for business information is a common application.

The Athena on AWS

• SQL query service for pay-as-you-go data analysis in AWS S3.
• Ad hoc querying is frequently used for data analysis.

Networks for Media Delivery (CDNs)

The cloudflare

• CDN service with fees determined by data transport volume.
• Common application: Increasing website speed by caching content near visitors.

The CloudFront by Amazon

• Low-latency content delivery via a usage-based CDN.
• Frequently used: providing web content worldwide and streaming video.

ML/AI as a Service

OpenAI GPT API

allows for text production and charges based on the number of tokens used.
Chatbots, content creation, and code completion are common uses.

The SageMaker on AWS

• Service management for creating, honing, and implementing machine learning models.
• Common application: implementing AI solutions or creating prediction models.

Redundancy and Recovery

Cloud backup using Veeam

• Cloud data and workload backup options that are pay-as-you-go.
• Common application: Preventing data loss in cloud-based workloads.

Azure Glacier

• Cost-effective archival storage solution for long-term preserves.
• Frequently used: Preserving data that is rarely accessed.

These examples show how utility computing makes flexible, affordable solutions possible across a range of industries, from analytics and artificial intelligence to hosting and storage.

Utility Computing Use cases

Access to computing resources can be made more economical and flexible via utility computing. Some typical use cases are as follows:

Uses in Business

• Using cloud-based servers to host websites and web apps while adjusting resource levels in response to demand is known as web hosting.
• Managing high traffic during sales or promotions, scaling infrastructure appropriately, and operating online storefronts are all examples of e-commerce.
• Business Resource Planning (ERP): Using cloud-based ERP solutions can lower initial expenses and upkeep.
• CRM stands for customer relationship management, and cloud-based CRM systems are used to handle customer data and interactions.

Machine learning and data analysis

• Using cloud-based data warehouses and analytics tools to process and analyze huge datasets is known as big data analytics.
• Cloud-based machine learning models are trained and implemented by utilizing robust computer resources.
• Building and implementing AI applications on cloud infrastructure, such as recommendation engines and chatbots, is known as artificial intelligence.

Software Development and Evaluation

• Cloud-based virtual development environments enable distant collaboration and rapid prototyping.
• Build, test, and deployment processes are automated via continuous integration/continuous delivery (CI/CD) pipeline.
• Software testing: Cloud-based automated tests improve software quality and speed up testing cycles.

Investigations in Science

• HPC on the cloud analyzes large datasets and simulates complex scientific models.
• Genetic data is analysed using cloud-based bioinformatics technologies.
• Using cloud-based climate simulations to research climate change and its effects is known as climate modeling.

Various Use Cases

• Creating and hosting online games and streaming them to a worldwide audience are both included in game development and streaming.
• Cloud-based platform testing and deployment of mobile applications is known as mobile app development.
• Disaster Recovery: Preserving vital data and apps with cloud-based backup and recovery solutions.
• Businesses and organizations may accelerate innovation, cut expenses, and optimize their IT resources by utilizing utility computing.

Cloud computing vs Utility computing

Feature	Cloud Computing	Utility Computing
Definition	Online manipulation, configuration, and application access are referred to as cloud computing. It provides applications, infrastructure, and online data storage.	Utility computing, sometimes referred to as pay-per-use or metered services, is a business model in which a service provider provides clients with infrastructure management and computer resources as needed.
Scope	On delivering computing services over the internet.	Primarily on the delivery model of computing resources.
Model	Various models, including IaaS, PaaS, and SaaS.	Pay-per-use, similar to traditional utilities like electricity or water.
Resource	Provides a wide range of services, from infrastructure to software applications.	Offers computing resources like processing power, storage, and networking.
Scope	Typically delivered through cloud service providers.	Can be implemented on-premises or through cloud providers.