Cloud technologies

CLOUD TECHNOLOGIES
PRESENTED BY:
KAVANA K
KAVYASHREE S R
MAITHRI VAIDYA G
Siddaganga Institute of Technology, Tumkur, Karnataka

Contents
• Introduction
• Block Diagram
• Cloud Models
• Cloud Technologies
• Why cloud
• References

Introduction
The term Cloud refers to a Network or Internet. It implies that Cloud is something,
which is available at a remote area. Cloud can give benefits over system or web, i.e., on
open systems or on private systems.
Cloud computing is Internet-based computing, whereby shared resources, software
and information are provided to computers and other devices on-demand, like the
electricity grid.
The cloud computing is a culmination of numerous attempts at large scale computing
with seamless access to virtually limitless resources.

Cloud Models
Cloud computing offers organization an expanded storage than traditional
storage systems. There are various types of services and models working behind
the scene making the cloud computing practical and open to end clients. They
are as follows
 Deployment Models.
 Service Models.

Deployment Model
Deployment models characterize the type of accessibility to the cloud environment.
Cloud divide the accessibility into four types:
 Public : accessible to all the external clients through the internet.
Example: email, Google App Engine
Private : This cloud is setup particularly for an organization within its own data center.

Community: A few organizations together build and offer a similar cloud infrastructure
and also policies, requirements, values and concerns
 Hybrid : It is a group of public, private and community cloud.

Service Model
A cloud can connect with a customer (client or application) in an assortment of courses
through abilities called services. Services Models are the functional models where the
Cloud Computing is based. The three major types of services are:
Infrastructure as a Service (IaaS): IaaS enables the cloud provider to openly find the
infrastructure over the Internet in a practical way.
Platform as a Service (PaaS): It is the delivery of application development and
deployment platform over the internet as a service to developers, who can use the
platform to build, deploy and manage SaaS applications easily.
Software as a Service (SaaS): It is the conveyance of Applications (e.g., ERP or CRM) as a
help of end customers over the web through browsers.

Containers
The code of the application can be bundled with configurations and dependencies in a
systematic manner. Container in cloud computing is used to build blocks, which help in
producing operational efficiency, version control, developer productivity and
environmental consistency.
The container usage in online services benefits storage with cloud computing
information security, availability and elasticity.
 Containers offer a lightweight way to package an application together with all its
dependencies so that it is separate from other applications running on the same
infrastructure.

Kubernetes
Kubernetes is an open-source container orchestration system for
automating application deployment, scaling, and management.
It aims to provide a "platform for automating deployment, scaling, and operations
of application containers across clusters of hosts“. It works with a range of
container tools, including Docket.
Many cloud services offer a Kubernetes-based platform or infrastructure as a
service (PaaS or IaaS) on which Kubernetes can be deployed as a platform-
providing service.

Serverless computing
Serverless computing, also sometimes called function as a service (FaaS), allows
developers to write and deploy code in the cloud without provisioning resources.
Serverless computing is a misnomer referring to a cloud-computing execution model in
which the cloud provider runs the server, and dynamically manages the allocation of
machine resources.
Serverless computing can simplify the process of deploying code into production. Scaling,
capacity planning and maintenance operations may be hidden from the developer or
operator.
Serverless code can be used in conjunction with code deployed in traditional styles, such
as microservices. Alternatively, applications can be written to be purely serverless and
use no provisioned servers at all.

APIs
API stands for Application programming interface. In layman's terms, an API is an easy
way to enable an application to interact with another application, a Web service or a
cloud service.
A cloud API is a type of Application Programming Interface that facilitates development of
services as well as applications for provisioning cloud platforms, hardware, and software.
It acts as a service gateway to enable indirect and direct cloud software and infrastructure
services to cloud users.

Microservices
Microservices are an architectural approach to creating cloud applications, where each
application is built as a set of services. Each service runs in its own processes and
communicates through application programming interfaces (API).
Microservices are independent applications that can be knit together into a larger
system. Developers use microservices both to create new apps, and as a pattern to
break apart and refactor legacy monolithic apps for the cloud era.
Organizations often use microservices architecture in the cloud in order to increase
the speed of application development and deployment, as well as to improve
scalability.

Machine Learning
Artificial intelligence and its machine learning subset seem to be everywhere in the technology
industry these days.
The large amounts of data stored in the cloud provides a source of information for the machine
learning process.
 It provides scalable, low cost computing and secondly, it is a great way to store and process
large volumes of data.
Because machine learning projects run most efficiently on expensive high-performance
computing (HPC) systems equipped with GPUs, many organizations are finding that it is most
cost effective to run machine learning workloads in the cloud

Automation
Cloud automation is a broad term that refers to the processes and tools an organization
uses to reduce the manual efforts associated with provisioning and managing cloud
computing workloads. IT teams can apply cloud automation to private, public and hybrid
cloud environments.
Cloud automation is a central element of workload lifecycle management. Workloads in
the cloud are rarely long-term entities.
Cloud automation can also play a role in hybrid clouds by automating tasks in a private
cloud environment based on frameworks such as OpenStack , and driving integration with
public clouds, such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud
Platform (GCP).
Automation solutions that can handle hybrid and multi-cloud environments could see
particularly high demand.

Block Chain
Blockchain cloud services may offer organizations the ability to shift away from
traditional cryptography models.
Blockchain is the secure, distributed ledger technology that underlies crypto
currencies like Bitcoin.
Enterprises could use it for a lot of other purposes, like smart contracts, supply chain
management, digital content management, health care records, loan processing and
insurance claims.

Why cloud?
 The cloud is reliable in that it enables access to applications and documents anywhere in the
world via the internet.
 It is a safe way of storing and sharing data.
 Cost savings
 Security
 Flexibility and mobility
 Increased collaboration
 Quality control
 Disaster control
 Sustainability

References
https://www.datamation.com/amp/cloud-computing/slideshows/9-cloud-computing-technologies-
you-need-to-understand-for-2018.html
https://www.researchgate.net/publication/224600883_Current_Trends_in_Remote_Laboratories
https://www.cloudcodes.com/blog/container-in-cloud-computing.html
https://www.go4hosting.in/knowledgebase/cloud-server-hosting/what-is-the-use-of-api-s-in-cloud-
services
https://www.ibm.com/blogs/cloud-computing/2016/05/04/what-are-microserverices/
https://blog.g2crowd.com/blog/trends/artificial-intelligence/2018-ai/machine-learning-service-
mlaas/
https://cloudacademy.com/blog/what-are-the-benefits-of-machine-learning-in-the-cloud/
https://searchcloudcomputing.techtarget.com/definition/cloud-automation
https://www.salesforce.com/hub/technology/benefits-of-cloud/

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