Unit2 Saa S Definition Software as a Service

Unit-2

Saa. S Definition • Software as a Service (Saa. S) is defined as software that is deployed over the internet. • With Saa. S, a provider licenses an application to customers either as a service on demand through a subscription, in a “pay-as-you-go” model, or (increasingly) at no charge when there is opportunity to generate revenue from streams other than the user, such as from advertisement or user list sales.

Benefits • No additional hardware costs • No initial setup costs • Usage is scalable • Updates are automated • Cross device compatibility • Accessible from any location • Applications can be customized and white-labeled

Saa. S

Saa. S

• Paa. S: Platform as a Service The most complex of the three, cloud platform services or “Platform as a Service” (Paa. S) deliver computational resources through a platform. • Paa. S makes the development, testing, and deployment of applications quick, simple, and cost-effective, eliminating the need to buy the underlying layers of hardware and software. • One comparison between Saa. S vs. Paa. S has to do with what aspects must be managed by users, rather than providers: With Paa. S, vendors still manage runtime, middleware, O/S, virtualization, servers, storage, and networking, but users manage applications and data.

Paa. S Features • Operating system • Server-side scripting environment • Database management system • Server Software • Support • Storage • Network access • Tools for design and development • Hosting

Paas Benefits • • • They don’t have to invest in physical infrastructure Makes development possible for ‘non-experts Flexibility Adaptability Teams in various locations can work together Security

Paas Architecture Model

Google App Engine

Microsoft Azure

SQL Azure

Iaa. S

Amazon EC 2

Dbaas • Database as a Service (DBaa. S) is a cloud-based approach to the storage and management of structured data. DBaa. S delivers database functionality similar to what is found in relational database management systems (RDBMSes) such as SQl Server, My. SQL and Oracle. • Being cloud-based, DBaa. S provides a flexible, scalable, ondemand platform that's oriented toward self-service and easy management, particularly in terms of provisioning a business' own environment

Challenges of Dbaas

Communication as a Service (Caa. S)

Map Reduce Framework Map (k 1, v 1) list (k 2, v 2) Reduce (k 2, list(v 2)) list (v 2)

Map. Reduce Applications • • Distributed grep Count of URL-access frequency <URL, total-count> Term vector per host <word, frequency> Reverse Web-link graph <target, Source> : < host, term-vector> Statistical algorithms • Support Vector Machines(SVM) • Linear Regression(LR) • Naive Bayes(NB) • Neural Network(NN) Analysis & Aggregation phases

Hadoop Architecture Description • It is an open source software development project. It is a project hosted by the Apache Software Foundation. Hadoop is software focused on reliable, scalable, distributed computing. • Hadoop is a parallel processing system implemented as a Map. Reduce engine layered on top of a fault-resilient distributed file system.

The basic functionalities of Hadoop Distributed File System (HDFS) • Large files are split into blocks of equal size • These blocks are distributed across the cluster for storage • Because node failure is a reality to be considered in a larger cluster, each block is stored multiple times (typically three times) on different computers

• Prepare the Map() input – the “Map. Reduce system” designates Map processors, assigns the K 1 input key value each processor would work on, and provides that processor with all the input data associated with that key value. • Run the user-provided Map() code – Map() is run exactly once for each K 1 key value, generating output organized by key values K 2. • “Shuffle” the Map output to the Reduce processors – the Map. Reduce system designates Reduce processors, assigns the K 2 key value each processor would work on, and provides that processor with all the Map-generated data associated with that key value. • Run the user-provided Reduce() code – Reduce() is run exactly once for each K 2 key value produced by the Map step. • Produce the final output – the Map. Reduce system collects all the Reduce output, and sorts it by K 2 to produce the final outcome.

Hadoop Architecture