Private vs Public Cloud: Key Differences, Architecture, and Cloud Service Models

#cloud #cloudcomputing #containers #docker

Introduction

Cloud computing is often discussed in terms of private and public clouds, but the difference between them is often misunderstood. There are different types of computing models, such as private cloud, public cloud, hybrid cloud, and multi-cloud. For me, "private" was the most confusing, and it took me some time to understand it correctly.

In this article, we’ll break down the architectural differences, trade-offs, and when each model makes sense.

Traditional Data Center

To understand it better, let's first understand how a traditional data center works. To set up a traditional data center, you need to purchase hardware for servers, switches, routers, etc. In other words, you're responsible for the setup and maintenance of the hardware where the software code will run. Servers are installed on the racks along with network switches, routers, etc. So why a traditional data center is becoming less popular? because it's quite expensive, the resource may not be 100% utilized (you really do not want to run a micro-service on one complete hardware server), you need a lot of capacity planning, any addition of capacity like installing a new server may take longer time and quite risky, as you may accidentally knock down some network wire or power supply (that may result in an outage). But, it's still in use mostly because of the need to keep sensitive data in a personal data center and compliance requirements. Below is an illustration of a traditional data center.

Private Cloud

To overcome traditional data center challenges, the private cloud model comes to the rescue (though it has its own challenges, but it helps with better resource utilization). Before we move ahead and try to understand private cloud, let's see another popular term, IaaS (Infrastructure as a Service).
To place it in simple language, IaaS is a model where you won't have to worry about the underlying hardware layer and only concentrate on the OS, runtime, and code (though you're still relying on the memory and CPU from actual hardware).

Note: Hypervisor is a component that creates an abstraction on top of the actual hardware that lets you run the virtual machine.

So, from the above illustration, you're responsible for the operating system (OS) layer, and above that, that's the virtual machine (VM) box. Coming back to the private cloud, it's a hybrid between traditional and IaaS. In the private cloud model, you still own the hardware, but we run technology like a hypervisor to create a VM and run your application on top of it. That helps to better resource utilization, as on a single hardware server, you can probably run more than one VM. As an application team, you're in more control of the virtual machine, which enables you to better utilize the resources and easily scale horizontally (in a microservice architecture pattern). The team can decide on how much memory and vCPU (virtual CPU) are required by their application, and easily scale out the application instances.

Private Cloud Examples

VMware vSphere
OpenStack
Nutanix

Public Cloud

Now, going to a public cloud model, if you take away the hardware, hypervisor, OS, and runtime components from the earlier IaaS diagram, you're left with your application and its data. Public cloud means the infrastructure is owned and operated by a cloud provider, and multiple customers share the underlying resources. Services may be offered as IaaS (VMs), PaaS (managed platforms), or SaaS (applications).

You're responsible for your application code and its data. So, in other words, a public cloud is a cloud model where you don't own any hardware; you pay for services that you use in various pricing models like per request, per hour, etc. Cloud providers like AWS provide you with EC2 as a compute instance/server where you can run the code without any hardware operational challenges. In a public cloud provider case, the cloud provider owns the hardware in their physical location. There are a lot of benefits of using the public cloud, e.g., not much capacity planning is needed, capacity can be increased quite easily and quickly, etc. What is the disadvantage of using the public cloud? As such, there is no real downside to it; however, there could be compliance restrictions on storing sensitive data in a public cloud. Not because the public cloud is accessible to all, but because maybe the system that stores data may not be portable to the cloud, or the organization really does not trust the public cloud.

Public Cloud Examples

AWS EC2
Google Cloud Compute Engine
Azure Virtual Machines

Hybrid and Multi Cloud

Once you understand public and private clouds, hybrid and multi-cloud models are quite straightforward.

Hybrid cloud means you're running code in both places, i.e., private cloud in your physical data center and public cloud provider. Why will you do that? You're still migrating to a public cloud, you need a failover strategy (where failover will happen to the private cloud), and of course, sensitive data.
Hybrid cloud is often used when:

Sensitive data remains on-prem
Burst workloads move to public cloud
Gradual migration from data center to cloud

In a multi-cloud model, you want to run the application in multiple cloud providers like AWS, GCP, Azure, etc. And again, why would you do that? You don't want to get locked on a single cloud provider and want the flexibility and freedom to move to a different cloud service when the cloud provider increases the price.

When to Choose Cloud Model?

Choose Private Cloud When

Strict compliance requirements
Data sovereignty
Legacy systems

Choose Public Cloud When

Rapid scaling required
Startup/cost flexibility
Managed services needed

Take Away

Feature	Private Cloud	Public Cloud
Ownership	Organization	Cloud provider
Infrastructure	Dedicated	Shared (multi-tenant)
Cost Model	High upfront cost	Pay-as-you-go
Scalability	Limited by hardware	Nearly unlimited
Control	High	Moderate
Examples	VMware, OpenStack	AWS, Azure, GCP

If you have reached here, then I have made a satisfactory effort to keep you reading. Please be kind to leave any comments or ask for any corrections. Happy Clouding!