What is Cloud Computing?
Cloud computing is the delivery of computing resources such as servers, storage, databases, software, and analytics over the Cloud rather than through local servers or personal devices. Users to access these resources on demand, making it possible to deploy applications, store data, and perform complex computations without maintaining physical infrastructure.
There are three main service models:
- Infrastructure as a Service (IaaS): Provides virtualised resources like storage and networking.
- Platform as a Service (PaaS): Offers application development and deployment platforms.
- Software as a Service (SaaS): Delivers fully functional software applications via the cloud.
Cloud computing includes deployment models such as public, private, and hybrid clouds, catering to different security, control, and scalability needs.
Example: A business might use a cloud service like Microsoft Azure to run its web applications without investing in physical servers.
Advantages of Cloud Computing
Cloud computing provides benefits that transform how businesses operate:
- Operational agility: Enables rapid deployment of resources, so businesses can respond quickly to market demands and innovation opportunities
- Resource optimisation: Dynamically allocates resources, preventing waste and optimal performance during demand spikes or dips
- Enhanced collaboration: Provides centralised access to data and applications for better collaboration among distributed teams
- Resilience and redundancy: Offers built-in disaster recovery and data backup for business continuity during outages or data loss.
- Cost flexibility: Offers predictable, subscription-based pricing models, so businesses can align IT costs with actual usage.
- Global reach: Cloud infrastructure spans multiple geographic regions, so businesses can deploy applications closer to their users for improved performance.
Example: A financial services software developer might scale its cloud resources during high-traffic events, then scale down afterwards, optimising costs and performance.
Here's a glossary of key terms associated with managed cloud services:
A
Auto Scaling
A cloud feature that automatically adjusts resources (e.g., servers) based on traffic or workload.
Example: Scaling up during peak hours for an e-commerce site.
Application Migration
The process of moving an application from one environment to another, such as from on-premises data centres to the cloud.
Example: Migrating a financial services application from local servers to Microsoft Azure to enhance scalability and performance.
Application Modernisation
Updating an existing application’s architecture, platform, or features to leverage modern technologies like cloud computing, microservices, or containers.
Example: Refactoring a legacy monolithic application into microservices using Kubernetes on Azure for better scalability and resilience.
Cloud Architecture
The design and organisation of cloud components such as servers, storage, networks, and software into a system that meets business requirements. It includes both front-end (user interface) and back-end (databases, servers) components, often incorporating microservices and APIs.
Example: Designing a cloud-native application architecture using Azure Kubernetes Service (AKS).
Availability Zone (AZ)
A geographic area within a cloud provider's region that houses isolated data centres.
Example: AWS's us-east-1a and us-east-1b.
B
Backup as a Service (BaaS)
A managed service for automatic data backups and recovery in the cloud.
Example: Using Veeam for offsite backups.
Bare Metal Server
A physical server is offered by cloud providers without virtualisation.
Example: Used for high-performance workloads like gaming or analytics.
C
Cloud Managed Services
A service in which a third-party provider manages an organisation’s cloud infrastructure for optimal performance, security, and scalability.
Example: Outsourcing the management of Azure Cloud infrastructure to a managed service provider (MSP).
Cloud Migration
Transferring data, applications, or infrastructure to a cloud environment.
Example: Moving on-premises servers to Azure.
Cloud Orchestration
Automated management and coordination of cloud services, often across multiple platforms.
Example: Using Kubernetes for container orchestration.
Cloud Service Provider (CSP)
A company offering cloud infrastructure, platforms, or software services.
Examples: AWS, Microsoft Azure, and Google Cloud.
Cloud-Native
Applications are designed to run efficiently in cloud environments using microservices and containerisation.
Example: A SaaS platform using Kubernetes and Docker.
Cost Optimisation
Managing cloud spending by analysing usage patterns, rightsizing resources, and leveraging discounts such as reserved instances or autoscaling.
Example: Implementing Azure Cost Management tools to identify underutilised virtual machines and reduce costs by transitioning to lower-cost instances.
D
Disaster Recovery as a Service (DRaaS)
A managed service providing rapid recovery of systems and data after an outage.
Example: Replicating systems to a secondary cloud region.
Data Sovereignty
Laws and regulations require data to remain within specific geographic locations.
Example: GDPR mandates data localisation within the EU.
F
Federated Identity Management (FIM)
A system that allows users to access multiple systems with one set of login credentials.
Example: Using Azure AD for single sign-on across cloud apps.
H
Hybrid Cloud
A computing environment that combines on-premises infrastructure with public and private clouds.
Example: Running critical apps in a private cloud while using a public cloud for scalability.
I
Infrastructure as Code (IaC)
Managing and provisioning cloud infrastructure through code rather than manual processes.
Example: Using Terraform to configure AWS resources.
Infrastructure as a Service (IaaS)
A cloud service model offering virtualised computing resources over the internet like storage, networking, and servers.
Examples: AWS EC2, Google Compute Engine.
L
Load Balancer
A tool that distributes incoming traffic across multiple servers to ensure high availability and reliability.
Example: AWS Elastic Load Balancer.
Latency
The delay in data transfer between the user and the cloud.
Example: High latency can affect video streaming quality.
M
Managed Kubernetes
A cloud service that automates Kubernetes cluster setup, maintenance, and scaling.
Example: Google Kubernetes Engine (GKE).
Managed Security Service Provider (MSSP)
A provider offering security monitoring and management services for cloud environments.
Example: Continuous threat monitoring for AWS.
P
Platform as a Service (PaaS)
A cloud service model providing a platform for developing, running, and managing applications.
Examples: Azure App Services, Google App Engine.
Private Cloud
A cloud environment dedicated to a single organization, offering enhanced security and control.
Example: VMware Cloud Foundation.
R
Reserved Instances (RI)
A pricing model offering discounts on cloud compute capacity in exchange for a long-term commitment.
Example: AWS EC2 Reserved Instances for predictable workloads.
Resource Tagging
A method of assigning metadata to cloud resources for tracking and management.
Example: Tagging resources by department or project in AWS.
S
Serverless Computing
A cloud execution model where the provider manages the infrastructure, and developers only deploy code.
Example: AWS Lambda or Azure Functions.
Service Level Agreement (SLA)
A contract outlining the service provider's performance and uptime commitments.
Example: A 99.9% uptime guarantee.
Software as a Service (SaaS)
A cloud model delivering applications over the internet on a subscription basis.
Examples: Salesforce, Microsoft 365.
V
Virtual Private Cloud (VPC)
A logically isolated section of a public cloud with enhanced security controls.
Example: Configuring a VPC in AWS to host applications privately.
Vertical Scaling
Increasing a server's capacity (e.g., adding more CPU or RAM) to handle greater workloads.
Example: Upgrading an instance type in AWS EC2.
W
Workload Management
Monitoring and optimising cloud resources to handle application workloads efficiently.
Example: Using auto-scaling to manage seasonal traffic spikes.