The control plane provides management and orchestration across an organization's cloud environment. This is where configuration baselines are set, user and role access are provisioned, and applications sit so they can execute with related services.
2. Cloud computing service Types
IaaS, PaaS & SaaS
Within the cloud deployment models, there are several types of cloud services, including infrastructure, platforms, and software applications. Cloud service models are not mutually exclusive, and you can choose to use more than one in combination or even all of them at once.
Here are the three main cloud service models:
Infrastructure as a Service (IaaS)
IaaS delivers on-demand infrastructure resources, such as compute, storage, networking, and virtualization. With IaaS, the service provider owns and operates the infrastructure, but customers will need to purchase and manage software, such as operating systems, middleware, data, and applications.
Platform as a Service (PaaS)
PaaS delivers and manages hardware and software resources for developing, testing, delivering, and managing cloud applications. Providers typically offer middleware, development tools, and cloud databases within their PaaS offerings.
Software as a Service (SaaS)
SaaS provides a full application stack as a service that customers can access and use. SaaS solutions often come as ready-to-use applications, which are managed and maintained by the cloud service provider.
Serverless computing
Serverless computing in cloud service models is also called Function as a Service (FaaS). This is a relatively new cloud service model that provides solutions to build applications as simple, event-triggered functions without managing or scaling any infrastructure.
3. Containers
In this way, containers virtualize the operating system and run anywhere, from a private data center to the public cloud or even on a developer’s personal laptop. From Gmail to YouTube to Search, everything at Google runs in containers.
Separation of responsibility
Containerization provides a clear separation of responsibility, as developers focus on application logic and dependencies, while IT operations teams can focus on deployment and management instead of application details such as specific software versions and configurations.
Workload portability
Containers can run virtually anywhere, greatly easing development and deployment: on Linux, Windows, and Mac operating systems; on virtual machines or on physical servers; on a developer’s machine or in data centers on-premises; and of course, in the public cloud.
Application isolation
Containers virtualize CPU, memory, storage, and network resources at the operating system level, providing developers with a view of the OS logically isolated from other applications.
Kubernetes, also known as K8s, is an open source system for automating deployment, scaling, and management of containerized applications.
It groups containers that make up an application into logical units for easy management and discovery.
6. Virtual Machines
A virtual machine (VM) is a digital representation of a physical computer. It behaves like an actual computer, with its own CPU, memory, and storage. VMs run within a software-based environment, separate from the host system.
Here are some common uses and benefits of VMs:
Cloud Deployment: VMs are used to build and deploy applications in cloud environments.
Testing and Development: Developers create VMs to test new operating systems or software.
Efficient Resource Utilization: VMs allow multiple virtual environments to run on a single physical infrastructure, reducing the need for many physical servers.
Isolation and Portability: VMs remain independent of each other and can be easily moved between different hosts.
In summary, VMs provide flexibility, cost savings, and efficient resource management.
7.Virtual Machines vs Containers
8. Microservices
Microservices are an architectural and organizational approach to software development. In this model, software is composed of small, independent services that communicate over well-defined APIs. Here are some key points about microservices:Independence: Each microservice is developed, deployed, operated, and scaled independently without affecting other services. They don’t share code or implementation with each other.
Specialization: Each service focuses on solving a specific problem or business capability. If a service becomes complex, it can be broken down into smaller services.
Agility: Microservices foster small, independent teams that take ownership of their services. This allows faster development cycles and better overall throughput.
Flexible Scaling: Services can be independently scaled to meet demand for specific features, optimizing infrastructure needs and maintaining availability.
With monolithic architectures, all processes are tightly coupled and run as a single service. This means that if one process of the application experiences a spike in demand, the entire architecture must be scaled. Adding or improving a monolithic application’s features becomes more complex as the code base grows. This complexity limits experimentation and makes it difficult to implement new ideas. Monolithic architectures add risk for application availability because many dependent and tightly coupled processes increase the impact of a single process failure.
With a microservices architecture, an application is built as independent components that run each application process as a service. These services communicate via a well-defined interface using lightweight APIs. Services are built for business capabilities and each service performs a single function. Because they are independently run, each service can be updated, deployed, and scaled to meet demand for specific functions of an application.
10. Edge Computing
Data Storage Terminologies
Split Brain situation - In a synchronous replication configuration - a split-brain situation where both arrays serve data for the same volume.
