= Εισαγωγή στο Cloud !
Apostolos rootApostolos@swarmlab.io
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== Cloud - Intro

Cloud computing is the **on-demand availability of computer system resources**, especially data storage and computing power, without direct active management by the user. The term is generally used to describe data centers available to many users over the Internet. 

Large clouds, predominant today, often have functions distributed over multiple locations from central servers. If the connection to the user is relatively close, it may be designated an edge server.

Clouds may be limited to a single organization (enterprise clouds), or be available to many organizations (public cloud).

Cloud computing relies on sharing of resources to achieve coherence and economies of scale. 

image:./Cloud_computing.svg.png[alt="Cloud_computing"] +
From Wikipedia, the free encyclopedia +
https://en.wikipedia.org/wiki/Cloud_computing[^]




=== Cloud Computing Tutorial for Beginners

* Cloud Computing Tutorial for Beginners
+
video::RWgW-CgdIk0[youtube]


== Cloud computing architecture

Cloud computing architecture refers to the components and subcomponents required for cloud computing. These components typically consist of a front end platform (fat client, thin client, mobile device), back end platforms (servers, storage), a cloud based delivery, and a network (Internet, Intranet, Intercloud). Combined, these components make up cloud computing architecture. 

=== Virtualization

In computing, virtualization refers to the act of creating a virtual (rather than actual) version of something, including virtual computer hardware platforms, storage devices, and computer network resources. 

=== Containerization

Containerization has become a major trend in software development as an alternative or companion to virtualization. It involves encapsulating or packaging up software code and all its dependencies so that it can run uniformly and consistently on any infrastructure. The technology is quickly maturing, resulting in measurable benefits for developers and operations teams as well as overall software infrastructure.

=== Virtual Machines vs Docker Containers

- A container image is a lightweight, stand-alone, executable package of a piece of software that includes everything needed to run it.

Docker is the service to run multiple containers on a machine (node) which can be on a vitual machine or on a physical machine.

- A virtual machine is an entire operating system (which normally is not lightweight).


* Virtual Machines vs Docker Containers
+
video::TvnZTi_gaNc[youtube]

==== Docker Containers

image:./container-what-is-container.png[alt="Container",align="center",width=550,height=550] 


==== Virtual Machines 

image:./container-vm-whatcontainer_2.png[alt="VirtualMachine",align="center",width=550,height=550] 

==  Orchestration

Container orchestration automates the deployment, management, scaling, and networking of containers. Enterprises that need to deploy and manage hundreds or thousands of Linux® containers and hosts can benefit from container orchestration. 
Container orchestration can be used in any environment where you use containers. It can help you to deploy the same application across different environments without needing to redesign it. And microservices in containers make it easier to orchestrate services, including storage, networking, and security. 

Containers give your microservice-based apps an ideal application deployment unit and self-contained execution environment. They make it possible to run multiple parts of an app independently in microservices, on the same hardware, with much greater control over individual pieces and life cycles.

Managing the lifecycle of containers with orchestration also supports DevOps teams who integrate it into CI/CD workflows. Along with application programming interfaces (APIs) and DevOps teams, containerized microservices are the foundation for cloud-native applications.


Container orchestration used for:

-    Provisioning and deployment
-    Configuration and scheduling 
-    Resource allocation
-    Container availability 
-    Scaling or removing containers based on balancing workloads across your infrastructure
-    Load balancing and traffic routing 
-    Monitoring container health
-    Configuring applications based on the container in which they will run
-    Keeping interactions between containers secure

===  Kubernetes vs Docker Swarm

* Kubernetes vs Docker Swarm
+
video::FmrAGliHvzQ[youtube]

==== Technical Comparisons

image:./1-2-683x1024.png[alt="dockerSwarmVsKubernetes"] +
image:./2-1-683x1024.png[alt="dockerSwarmVsKubernetes"] +



==== Conclusion

When comparing Docker Swarm vs Kubernetes, it becomes apparent that the origins of both platforms have played key roles in shaping their features and communities today.

Docker, realizing the strength of its container technology, decided to build a platform that made it simple for Docker users to begin orchestrating their container workloads across multiple nodes. However, their desire to preserve this tight coupling can be said to have limited the extensibility of the platform.

Kubernetes, on the other hand, took key concepts taken from Google Borg, and, from a high level perspective, decided to make containerization fit into the former platform’s existing workload orchestration model. This resulted in Kubernetes emphasis on reliability, sometimes at the cost of simplicity and performance.


==== Popularity of searches for each platform

image:./Screen-Shot-2018-01-09-at-5.59.05-PM-700x410.png[alt="dockerSwarmVsKubernetes"] +

Origin: 
https://www.nirmata.com/2018/01/15/orchestration-platforms-in-the-ring-kubernetes-vs-docker-swarm

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'''

.Reminder
[NOTE]
====
:hardbreaks:
Caminante, no hay camino, 
se hace camino al andar.

Wanderer, there is no path, 
the path is made by walking.

*Antonio Machado* Campos de Castilla
====
