191CS721 cloud computing Unit-III(iii).pptx

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1. Cloud Service Models Service Models are divided into three classes, according to the abstraction level of the capability provided by the providers, namely: Infrastructure as a Service ( IaaS ) Basic, service users maintain software(User controls-OS, Data , Application) Examples: Amazon EC2, Windows Azure, Google Compute Engine.

2. Cloud Service Models Platform as a Service ( PaaS ) Users are given software and hardware automatically( User controls Application, Data) Examples:, Windows Azure, Heroku, Force.com, Google App Engine, Apache Stratos. Software as a Service ( SaaS ) All software and hardware is transparent User only knows their own access point Examples: Google Apps, Microsoft Office 365.

3. Cloud Service Models Software as a Service (SaaS) Traditional desktop applications such as word processing and spreadsheet can now be accessed as a service in the Web. This model of delivering applications, known as SaaS . The capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure. The applications are accessible from various client devices through either a thin client interface, such as a web browser (e.g., web-based email), or a program interface. The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. SaaS Examples: Google Apps, Salesforce, Workday, Concur, Citrix GoToMeeting, CiscoWebEx .

4. Cloud Service Models Platform as a Service (PaaS) Another approach is to offer a higher level of abstraction to make a cloud easily programmable, known as Platform as a Service (PaaS). The capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages by the provider. The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, or storage, but has control over the deployed applications and possibly configuration settings for the application-hosting environment. PaaS Examples: AWS Elastic Beanstalk, Windows Azure, Heroku, Force.com, Google App Engine, Apache Stratos.

5. Cloud Service Models Infrastructure as a Service (IaaS) Offering virtualized resources (computation, storage, and communication) on-demand is known as Infrastructure as a Service (IaaS). The capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, and deployed applications; and possibly limited control of select networking components (e.g., host firewalls). IaaS Examples: Amazon Web Services (AWS), Cisco Metapod , Google Compute Engine (GCE), Joyent

6. Architectural Design Challenges Service Availability and Data Lock-in Problem Service Availability in Cloud might be affected because of Single Point Failure -Depending on single service provider might result in failure. Distributed Denial of Service-Cyber criminals, attack target websites and online services and makes services unavailable to users. Data Lock-in: Users may want to move data and applications out from a provider that does not meet their requirements. Data Privacy and Security Concerns Security and privacy affect the entire cloud computing stack, since there is a massive use of third-party services and infrastructures that are used to host important data or to perform critical operations

7. Architectural Design Challenges Unpredictable Performance and Bottlenecks Multiple VMs can share CPUs and main memory in cloud computing, but I/O sharing is problematic.Weak Servers that does not provide data transfers properly . Handling huge amount of data (data intensive) is a bottleneck in cloud environment. Distributed Storage and Widespread Software Bugs The database is always growing in cloud applications. There is a need to create a storage system that meets this growth Cloud Scalability, Interoperability and Standardization Cloud resources are scalable and portable,. The ability of virtual machine to run on any virtual platform. Software Licensing and Reputation Sharing licensing schemes to widen the business coverage.