The Landscape of Enterprise Applications - a personal view

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The Landscape of Enterprise Applications - a personal view Geoff Sharman Copyright geoffrey.sharman@bcs.org.uk www.dcs.bbk.ac.uk/~geoff/

Typical Web Application? Web servers Application Servers Database Servers Requests from web browsers Member DB Auction DB Static pages served from web server/content management system Dynamic pages assembled by applications on application servers May 12th 2011 APSG Enterprise Applications 2

Did you do any of these today? Buy something in a supermarket? Buy a ticket for travel or entertainment? Make a telephone call (mobile or fixed)? Use a cash machine or debit card? Pay for something with a credit card? Use electricity, gas or water? The chances are you used a traditional online transaction system (running on a mainframe?) May 12th 2011 APSG Enterprise Applications 3

That's Cloud Power? May 12th 2011 APSG Enterprise Applications 4

What's an Enterprise, or an Enterprise System? May 12th 2011 APSG Enterprise Applications 5

What is a System? Outputs Inputs information information control function energy material internal organisation, possibly including sub-systems energy material Physical, chemical, biological, social systems - real-time dynamic behaviour May 12th 2011 APSG Enterprise Applications 6

An Enterprise is a System for delivering economic & social outputs Outputs Inputs products, services information employment, financial returns Control function internal organisation, possibly including sub-systems information, finance labour, energy materials, services Related pairs of inputs & outputs are often referred to as transactions May 12th 2011 APSG Enterprise Applications 7

Interesting What's an Enterprise? Large numbers of customers Large numbers of transactions Large financial throughputs Complex behaviour/operations Sustainable operation High scale for an extended period May 12th 2011 APSG Enterprise Applications 8

An Enterprise System is the automated part of an enterprise = a real-time model of the enterprise Outputs Inputs products, services information employment, financial returns Control function hardware/software Enterprise System information, finance labour, energy materials, services May 12th 2011 APSG Enterprise Applications 9

Where would you find an ES? Probably not here: (primary industry, 5% of economy) Agriculture, fisheries, forestry, water extraction Mining, oil & gas extraction Possibly here: (secondary industry, 40% of economy) Construction, utilities Transport, distribution, communications Manufacturing (discrete & continuous) Probably here: (tertiary industry, 55% of the economy) 10 Financial & business services, media, retail Education, healthcare, tourism, entertainment Public admin May 12th 2011 APSG Enterprise Applications 10

Brief History of Enterprise Systems May 12th 2011 APSG Enterprise Applications 11

Pioneers of Enterprise Systems 1952 Joe Lyons & Co. Leo system - batch accounting & payroll operations 1965 American Airlines Sabre system - online flight reservations & check in 1993 Amazon.com - direct customer service, just-in-time delivery 2001 Google.com - customised search using large amounts of data 2008 Apple iphone - mobile applications May 12th 2011 APSG Enterprise Applications 12

Getting Closer to the Customer 6 5 4 3 System Type 1=Batch, 2=Online, 3=Network, 4=Web, 5=Social/mobile 2 1 0 1960s 1970s 1980s 1990s 2000s May 12th 2011 APSG Enterprise Applications 13

What were the Key Innovations? 1950s main storage (delay lines, ferrite cores), secondary storage (magnetic tape), batch job scheduler 1960s operating system, direct access storage, database management, time sharing terminals 1970s TP monitor, relational database 1980s personal computer, networking 1990s World Wide Web 2000s search engine, social networking, mobile May 12th 2011 APSG Enterprise Applications 14

Programming Paradigms May 12th 2011 APSG Enterprise Applications 15

Time Sharing/Conversational At logon time, operating system allocates: Memory address space for application Operating system process Files, communications channels, etc. These remain dedicated to user until logoff Paradigm is widely used, but: No sharing of resources Not scalable beyond few hundred users May 12th 2011 APSG Enterprise Applications 16

TP Monitor PseudoConversations TP Monitor acquires & retains shared resources Applications, memory, processes, threads, files, databases, communication channels, etc. On receipt of user transaction request, provides concurrent access to resources for application Frees resources as soon as output message sent Highly scalable to 10s of thousands of users Requires stateless application programming Conversation state held in scratchpad files May 12th 2011 APSG Enterprise Applications 17

Representational State Transfer Underlying paradigm for Web hypertext transfers Commonly abbreviated as REST Web servers manage network & provide concurrent access Defines stateless clients for rendering data Highly scalable to 10s of thousands of users Does not define how to build update applications on the Web Disallows cookies - no scratchpad Does not define server application model May 12th 2011 APSG Enterprise Applications 18

Google Applications Underlying paradigm for Google search and other applications Uses GAE (Google App engine) Requires stateless clients Concurrent access to scratchpad storage via GFS/BigTable Highly scalable to 10s of thousands of users Especially suitable for applications using readonly data, e.g. search data, maps, etc. May 12th 2011 APSG Enterprise Applications 19

Why do these Paradigms Work? All these paradigms embody the many-to-one relationship between customers and the enterprise The TP, Restful, & Google paradigms provide scalable concurrency & enable the enterprise to exploit economies of scale None of them is a complete description of what modern enterprise systems need May 12th 2011 APSG Enterprise Applications 20

What Paradigm is Needed? Stateless applications provide the highest scalability and work well for read only requests But commercial applications, e.g. web shopping, need conversation state & concurrent update Use HTTP because it supports any-client-to-any server, unlike object-based protocols Hold state on client or replicated server file system Collect updates that form part of a transaction Permanently save data at end of conversation May 12th 2011 APSG Enterprise Applications 21

Current Enterprise System Challenges May 12th 2011 APSG Enterprise Applications 22

Enterprise Business Challenges Enterprise business people care about two primary objectives: Reducing costs: automating/eliminating internal processes reducing operating costs for enterprise systems reducing ownership costs for enterprise systems Increasing revenue: Winning new customers Retaining existing customers Getting more business from existing customers May 12th 2011 APSG Enterprise Applications 23

Enterprise System Challenges 1) Multi-channel applications - acting consistently to the customer 2) Multi-business service - providing multiple offers consistently 3) Effective customer knowledge - acting more intelligently to the customer 4) Effective market knowledge - foreseeing what customers will want next May 12th 2011 APSG Enterprise Applications 24

Multi-Channel Applications Many enterprise systems are designed to support particular sales channels, eg.: Store checkout systems Kiosk/ticketing systems Call centre systems Web based systems Mobile systems Business offer may depend on channel, but Applications should treat the customer consistently, whichever channel he/she uses May 12th 2011 APSG Enterprise Applications 25

Typical M 2 Architecture sync msgs sync msgs Presentation / Channel server(s) - Static/ Dynamic web pages - Portals - Channel specific M 2 = Multi-Channel, Multi-Business async msgs Integration server - Tight coupling - Loose coupling - Stand-in processing - Flow ctrl/compensation Line of business Application and Data server(s) May 12th 2011 APSG Enterprise Applications 26

Customer Knowledge Many web systems allow customer to explore options before & after a transaction: high browse to buy ratio in web shopping evaluations of product, service, etc. If we identify the customer, we can study: search patterns history of actual transactions customer likes & dislikes May enable better offers to the customer need more data & may require real time parallel computation May 12th 2011 APSG Enterprise Applications 27

Market Knowledge Many enterprise systems collect data about a mass of customer transactions: Collected/refined in data warehouse Linked with tools for analytics / Bus Intelligence Used to produce periodic reports & analyses This process may be ineffective: Too slow/costly for business needs Only structured data much unstructured data New methods use very large data sets Best practice uses highly parallel processing May 12th 2011 APSG Enterprise Applications 28

Highly Parallel Processing Google is the best known exponent Many processes crawling the Web in parallel Combine results using MapReduce technique Store results in Google File System Effectively substitutes concurrency for parallelism Also widely used in scientific applications: e.g. SETI @Home used subscriber PCs IBM Blue Gene protein modelling project 4K processors generated 10 μsec simulation Uses hardware cluster plus GPRS May 12th 2011 APSG Enterprise Applications 29

Summary When building an Enterprise System, we are building a model of (part of) the enterprise: Model must be real time and scalable Customer can use anywhere, anytime, any device Access any business offering consistently Know and respond intelligently to each customer Meta-Enterprise System should analyse system & aggregate behaviour of customers Detect trends and respond to them May 12th 2011 APSG Enterprise Applications 30