Cloud Computing Cheat Sheet

The core ideas of Cloud Computing distilled into a single, scannable reference — perfect for review or quick lookup.

PiqCue — piqcue.com/cloud-computing/cheatsheet

Quick Reference

Infrastructure as a Service (IaaS)

A cloud computing model that provides virtualized computing resources over the internet, including virtual machines, storage, and networking. IaaS gives users the most control over their computing environment while eliminating the need to manage physical hardware.

Platform as a Service (PaaS)

A cloud service model that provides a platform allowing customers to develop, run, and manage applications without dealing with the underlying infrastructure. PaaS abstracts away operating system management, patching, and server provisioning so developers can focus solely on writing code.

Software as a Service (SaaS)

A cloud delivery model where software applications are hosted by a provider and made available to customers over the internet, typically via a web browser. SaaS eliminates the need for organizations to install, maintain, or update software on individual machines.

Serverless Computing

A cloud execution model where the cloud provider dynamically manages the allocation and provisioning of servers. Despite its name, servers still exist but developers do not need to think about them. Billing is based on actual resource consumption rather than pre-purchased capacity.

Containerization

A lightweight form of virtualization that packages an application and its dependencies into a standardized unit called a container. Containers share the host operating system kernel, making them more efficient than traditional virtual machines while ensuring consistent behavior across environments.

Hybrid Cloud

A computing architecture that combines on-premises infrastructure (private cloud) with public cloud services, allowing data and applications to move between the two environments. This approach provides greater flexibility and more deployment options while meeting regulatory and compliance requirements.

Auto-Scaling

The ability of a cloud system to automatically adjust computing resources based on real-time demand. Auto-scaling monitors metrics like CPU usage, memory consumption, or request counts and adds or removes instances to maintain performance and optimize costs.

Infrastructure as Code (IaC)

The practice of managing and provisioning computing infrastructure through machine-readable configuration files rather than through manual processes or interactive tools. IaC enables version control, repeatability, and automated deployment of entire infrastructure stacks.

Multi-Tenancy

An architecture where a single instance of a software application serves multiple customers (tenants). Each tenant's data is isolated and invisible to other tenants, even though they share the same underlying infrastructure and application codebase.

Cloud-Native Architecture

An approach to building and running applications that fully exploits the cloud computing delivery model, using practices such as microservices, containers, service meshes, immutable infrastructure, and declarative APIs. Cloud-native applications are designed for resilience, scalability, and rapid iteration.

Key Terms at a Glance

API Gateway:A managed service that acts as a single entry point for API calls, handling request routing, authentication, rate limiting, and monitoring for backend microservices or serverless functions.

Auto-Scaling:The automatic adjustment of computing resources in response to real-time demand, adding instances when load increases and removing them when demand drops to optimize performance and cost.

Availability Zone:An isolated data center within a cloud region, with independent power, cooling, and networking, designed to protect applications from single points of failure.

Bare Metal:A physical server dedicated to a single tenant without a hypervisor layer, providing maximum performance and hardware-level control for workloads that cannot tolerate virtualization overhead.

CDN (Content Delivery Network):A distributed network of proxy servers and data centers that delivers web content to users based on geographic proximity, reducing latency and improving page load speeds.

CI/CD:Continuous Integration and Continuous Delivery/Deployment—a set of automated practices where code changes are built, tested, and deployed to production frequently and reliably through automated pipelines.

Container:A lightweight, standalone executable package that includes application code and all its dependencies, sharing the host OS kernel and running consistently across different computing environments.

DevOps:A cultural and technical practice that unifies software development and IT operations, emphasizing automation, continuous delivery, monitoring, and collaboration to accelerate the software release cycle.

Docker:An open-source platform for building, shipping, and running applications inside containers, providing tools to package applications with their dependencies into portable, reproducible images.

Elasticity:The ability of a cloud system to dynamically acquire and release resources to match current demand precisely, scaling out during peaks and scaling in during lulls to minimize costs.

High Availability:A system design approach that ensures a specified level of operational uptime by eliminating single points of failure through redundancy, failover mechanisms, and geographic distribution.

Horizontal Scaling:Adding more machines or instances to a system to distribute workload, as opposed to vertical scaling which increases the power of existing machines. Preferred in cloud environments for flexibility.

Hypervisor:Software that creates and manages virtual machines by abstracting physical hardware resources and allocating them to multiple isolated virtual environments running on the same host.

Kubernetes:An open-source container orchestration platform that automates deploying, scaling, and managing containerized applications across clusters, providing self-healing, service discovery, and rolling updates.

Latency:The time delay between a user's request and the system's response, measured in milliseconds. In cloud computing, latency is affected by geographic distance, network congestion, and processing time.

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