Introduction to cloud Cambridge University.ppt

Cloud Computing
Introduction
Eva Kalyvianaki
ek264@cam.ac.uk
Anil Madhavapeddy
anil@recoil.org

My Background and Contact Details
 Dr Evangelia Kalyvianaki
 Senior Lecturer @CL since Oct. 2018
 PhD from the CL, Cambridge University (srg, netos group)
 Postdoc from Imperial College London
 Lecturer/Senior Lecturer in City University London
 I like building systems, working in Cloud computing,
distributed systems management and autonomic computing
 Office in FN15
 ek264@cam.ac.uk
 http://www.cst.cam.ac.uk/~ek264/
2

Course Logistics
 Resources:
 Web page: http://www.cl.cam.ac.uk/teaching/1920/CloudComp/
 Book:
 “Cloud Computing, Theory and Practice” Dan C. Marinescu,
Morgan Kaufmann
 Research papers (will be given per lecture)
 One coursework project in groups of three students each.
The project will be assessed via a project report and code
testing.
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Course Contents
1. Introduction to Cloud Computing
2. Virtualization I
3. Virtualization II
4. MapReduce Batch Processing
5. MapReduce in Heterogeneous Environments
6. Large-Scale Resource Management
7. Data Center Networking
8. Cloud Distributed Storage
9. Real-Time Data Stream Processing
4

5
Topic Main Lecturer Date
1. Introduction E. Kalyvianaki 17/01
2. Virtualization I A. Madhavapeddy 20/01
3. Virtualization II A. Madhavapeddy 22/01
4. MapReduce I E. Kalyvianaki 24/01
5. Tutorial I A. Grammenos 27/01
6. Tutorial II A. Grammenos 29/01
7. MapReduce II E. Kalyvianaki 31/01
8. Large-Scale Resource Management E. Kalyvianaki 03/02
9. Tutorial III A. Grammenos 05/02
10. Data Center Networking Dr. Paolo Costa, MSRC 07/02
11. Cloud Distributed Storage E. Kalyvianaki 10/02
12. Optimizing Storage Performance
using S3
Dr. Tim Harris, Amazon 12/02
13. Real-time Data Stream Processing E. Kalyvianaki 14/02
Timetable, all lectures @LT1

Lecture Contents
 What is Cloud Computing?
 Early models of Cloud Computing.
 Delivery models and services.
 Ethical issues in Cloud Computing.
 Cloud vulnerabilities.
 Parallel Computing.
 Distributed Systems.
6

What is Cloud Computing?
 What do you think?
 “Cloud computing is an information technology (IT) paradigm that
enables ubiquitous access to shared pools of configurable system
resources and higher-level services that can be rapidly provisioned with
minimal management effort, often over the Internet. Cloud computing
relies on sharing of resources to achieve coherence and economies of
scale, similar to a public utility.” https://en.wikipedia.org/wiki/Cloud_computing
 “Simply put, cloud computing is the delivery of computing services –
servers, storage, databases, networking, software, analytics and more –
over the Internet (“the cloud”). Companies offering these computing
services are called cloud providers and typically charge for cloud
computing services based on usage, similar to how you’re billed for gas
or electricity at home.” https://azure.microsoft.com/en-gb/overview/what-is-cloud-computing/
7

Delivery models
Infrastructure as a Service (IaaS)
Software as a Service (SaaS)
Platform as a Service (PaaS)
Deployment models
Private cloud
Hybrid cloud
Public cloud
Community cloud
Defining attributes
Massive infrastructure
Accessible via the Internet
Utility computing. Pay-per-usage
Elasticity
Cloud computing
Resources
Networks
Compute & storage servers
Services
Applications
Infrastructure
Distributed infrastructure
Resource virtualization
Autonomous systems
Cloud Computing Models, Resources, Attributes
8

Early Models of Cloud Computing
 Basic reasoning: information and data processing can be
done more efficiently on large farms of computing and
storage systems accessible via the Internet.
 Two early models:
1. Grid computing – initiated by the National Labs in the
early 1990s; targeted primarily at scientific computing.
 “Grid computing is the collection of computer resources from
multiple locations to reach a common goal. The grid can be thought
of as a distributed system with non-interactive workloads that
involve a large number of files.” from Wikipedia
2. Utility computing – initiated in 2005-2006 by IT
companies and targeted at enterprise computing.
 “Utility computing is a service provisioning model in which a service
provider makes computing resources and infrastructure
management available to the customer as needed, and charges
them for specific usage rather than a flat rate.” from Wikipedia
9

Cloud computing - Characteristics
“Cloud Computing offers on-demand, scalable and elastic
computing (and storage services). The resources used for these
services can be metered and users are charged only for the
resources used. “ from the Book
Shared Resources and Resource Management:
1.Cloud uses a shared pool of resources
2.Uses Internet techn. to offer scalable and elastic services.
3.The term “elastic computing” refers to the ability of
dynamically and on-demand acquiring computing resources and
supporting a variable workload.
4.Resources are metered and users are charged accordingly.
5.It is more cost-effective due to resource-multiplexing. Lower
costs for the cloud service provider are past to the cloud users. 10

Cloud computing (cont’d)
Data Storage:
6.Data is stored:
 in the “cloud”, in certain cases closer to the site where it is used.
 appears to the users as if stored in a location-independent manner.
7.The data storage strategy can increase reliability, as well as
security, and can lower communication costs.
Management:
8.The maintenance and security are operated by service
providers.
9.The service providers can operate more efficiently due to
specialisation and centralisation.
11

Cloud Computing Advantages
1. Resources, such as CPU cycles, storage, network
bandwidth, are shared.
2. When multiple applications share a system, their peak
demands for resources are not synchronised thus,
multiplexing leads to a higher resource utilization.
3. Resources can be aggregated to support data-intensive
applications.
4. Data sharing facilitates collaborative activities. Many
applications require multiple types of analysis of shared
data sets and multiple decisions carried out by groups
scattered around the globe. 12

Cloud Computing Advantages
5. Eliminates the initial investment costs for a private
computing infrastructure and the maintenance and
operation costs.
6. Cost reduction: concentration of resources creates the
opportunity to pay as you go for computing.
7. Elasticity: the ability to accommodate workloads with
very large peak-to-average ratios.
8. User convenience: virtualization allows users to operate
in familiar environments rather than in idiosyncratic ones.
13

Types of clouds
1. Public Cloud - the infrastructure is made available to the
general public or a large industry group and is owned by
the organization selling cloud services.
2. Private Cloud – the infrastructure is operated solely for
an organization.
1. Hybrid Cloud - composition of two or more Clouds
(public, private, or community) as unique entities but
bound by a standardised technology that enables data and
application portability.
2. Other types: e.g., Community/Federated Cloud - the
infrastructure is shared by several organizations and
supports a community that has shared concerns.
14

Why cloud computing is (could) be successful
when other paradigms have failed?
 It is in a better position to exploit recent advances in
software, networking, storage, and processor technologies
promoted by the same companies who provide Cloud
services.
 Economical reasons: It is used for enterprise computing; its
adoption by industrial organizations, financial institutions,
government, and so on has a huge impact on the economy.
 Infrastructures Management reasons:
 A single Cloud consists of a mostly homogeneous (now more
heterogeneous) set of hardware and software resources.
 The resources are in a single administrative domain (AD). Security,
resource management, fault-tolerance, and quality of service are
less challenging than in a heterogeneous environment with
resources in multiple ADs.
15

Challenges for cloud computing
1. Availability of service: what happens when the service
provider cannot deliver?
2. Data confidentiality and auditability, a serious problem.
3. Diversity of services, data organization, user interfaces
available at different service providers limit user mobility;
once a customer is hooked to one provider it is hard to
move to another.
4. Data transfer bottleneck; many applications are data-
intensive.
16

More challenges
5. Performance unpredictability, one of the consequences of
resource sharing.
 How to use resource virtualization and performance isolation for
QoS guarantees?
 How to support elasticity, the ability to scale up and down quickly?
6. Resource management: It is a big challenge to manage
different workloads running on large data centers. Are self-
organization and self-management the solution?
7. Security and confidentiality: major concern for sensitive
applications, e.g., healthcare applications.
Addressing these challenges is on-going work! 17

Cloud Delivery Models
1. Software as a Service (SaaS) (high level)
2. Platform as a Service (PaaS)
3. Infrastructure as a Service (IaaS) (low level)
18
source Wikipedia

Infrastructure-as-a-Service (IaaS)
 Infrastructure is compute resources, CPU, VMs, storage, etc
 The user is able to deploy and run arbitrary software, which
can include operating systems and applications.
 The user does not manage or control the underlying Cloud
infrastructure but has control over operating systems,
storage, deployed applications, and possibly limited control
of some networking components, e.g., host firewalls.
 Services offered by this delivery model include: server
hosting, storage, computing hardware, operating systems,
virtual instances, load balancing, Internet access, and
bandwidth provisioning.
 Example: Amazon EC2
19

Platform-as-a-Service (PaaS)
 Allows a cloud user to deploy consumer-created or acquired
applications using programming languages and tools
supported by the service provider.
 The user:
 Has control over the deployed applications and, possibly, application
hosting environment configurations.
 Does not manage or control the underlying Cloud infrastructure
including network, servers, operating systems, or storage.
 Not particularly useful when:
 The application must be portable.
 Proprietary programming languages are used.
 The hardware and software must be customised to improve the
performance of the application.
 Examples: Google App Engine, Windows Azure
20

Software-as-a-Service (SaaS)
 Applications are supplied by the service provider.
 The user does not manage or control the underlying Cloud
infrastructure or individual application capabilities.
 Services offered include:
 Enterprise services such as: workflow management,
communications, digital signature, customer relationship
management (CRM), desktop software, financial management, geo-
spatial, and search.
 Not suitable for real-time applications or for those where
data is not allowed to be hosted externally.
 Examples: Gmail, Salesforce
21

The Three delivery models of Cloud Computing
22

Cloud activities
 Service management and provisioning including:
 Virtualization.
 Service provisioning.
 Call center.
 Operations management.
 Systems management.
 QoS management.
 Billing and accounting, asset management.
 SLA management.
 Technical support and backups.
23

Cloud activities (cont’d)
 Security management including:
 ID and authentication.
 Certification and accreditation.
 Intrusion prevention.
 Intrusion detection.
 Virus protection.
 Cryptography.
 Physical security, incident response.
 Access control, audit and trails, and firewalls.
24

Cloud activities (cont’d)
 Customer services such as:
 Customer assistance and on-line help.
 Subscriptions.
 Business intelligence.
 Reporting.
 Customer preferences.
 Personalization.
 Integration services including:
 Data management.
 Development.
25

Ethical issues
 Paradigm shift with implications on computing ethics:
 The control is relinquished to third party services.
 Data is stored on multiple sites administered by several
organizations.
 Multiple services interoperate across the network.
 Implications:
 Unauthorised access.
 Data corruption.
 Infrastructure failure, and service unavailability.
26

De-perimeterisation
 Systems can span the boundaries of multiple organisations
and cross the security borders.
 The complex structure of Cloud services can make it
difficult to determine who is responsible in case something
undesirable happens.
 Identity fraud and theft are made possible by the
unauthorised access to personal data in circulation and by
new forms of dissemination through social networks and
they could also pose a danger to Cloud Computing.
27

Privacy issues
 Cloud service providers have already collected petabytes of
sensitive personal information stored in data centers around
the world. The acceptance of Cloud Computing therefore
will be determined by privacy issues addressed by these
companies and the countries where the data centers are
located.
 Privacy is affected by cultural differences; some cultures
favour privacy, others emphasise community. This leads to
an ambivalent attitude towards privacy in the Internet
which is a global system.
28

Cloud Vulnerabilities
 Clouds are affected by malicious attacks and failures of the
infrastructure, e.g., power failures.
 Such events can affect the Internet domain name servers
and prevent access to a Cloud or can directly affect the
Clouds:
 in 2004 an attack at Akamai caused a domain name outage and
a major blackout that affected Google, Yahoo, and other sites.
 in 2009, Google was the target of a denial of service attack
which took down Google News and Gmail for several days;
 in 2012 lightning caused a prolonged down time at Amazon.
29

Back to Basics -- Parallel Computing
 “Parallel computing is a form of computation in which many
calculations are carried out simultaneously, operating on the
principles that large problems can often be divided into smaller
ones, which are then solved concurrently (in parallel).” Wikipedia
 Hardware and software systems allow us to:
 Solve problems demanding resources not available on a
single system.
 Reduce the time required to obtain a solution.
30

Parallel Computing – Amdahl’s Law
 The speedup S measures the effectiveness of parallelisation:
S(N) = T(1) / T(N)
 T(1)  the execution time of the sequential computation.
 T(N)  the execution time when N parallel computations are executed
 Amdahl's Law: if α is the fraction of running time a
sequential program spends on non-parallelisable segments of
the computation then:
S ≅ 1/ α
 This is a theoretical upper bound on the best speedup we can
get from parallelising a certain program.
31

Back to Basics -- Distributed systems
 Collection of autonomous computers, connected through a
network and distribution software (often) called middleware
which enables computers to coordinate their activities and to
share system resources for a common goal.
 Characteristics:
1. The users perceive the system as a single, integrated computing
facility.
2. The components are autonomous.
3. Scheduling and other resource management and security policies are
implemented by each system.
4. There are multiple points of control and multiple points of failure.
5. The resources may not be accessible at all times.
6. Can be scaled by adding additional resources.
7. Can be designed to maintain availability even at low levels of
hardware/software/network reliability. 32

Summary
 What is Cloud Computing?
 Early models of Cloud Computing.
 Delivery models and services.
 Ethical issues in Cloud Computing.
 Cloud vulnerabilities.
 Parallel Computing and Distributed Systems (brief)
33

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