architecting enterprise grids: possible inflection points

IADIS International Conference Applied Computing 2007

ARCHITECTING ENTERPRISE GRIDS: POSSIBLE INFLECTION POINTS Kemal A. Delic, Martin Antony Walker Hewlett-Packard Comp. France/Switzerland

ABSTRACT Grids, which originated in academic research more than a decade ago, are now entering a mature, commercial stage. They may represent crucial infrastructure for the future of enterprise computing. We reflect on ‘architecting’ of ‘enterprise grids’ by suggesting that enterprise data centers will morph into enterprise grids (EG), whose growth will be driven by future enterprise applications (EA). We point out two classes of enterprise applications as ‘inflection points’ potentially leading to widespread use of enterprise grids. Requirements for EA are briefly compared with typical parallel applications on academic grids. In conclusion, we suggest a few grid architecting principles. KEYWORDS Enterprise Grids, Architecting, Enterprise Applications

1. INTRODUCTION - INFRASTRUCTURAL CHANGE Enterprise IT architecture may experience the following turning point: instead of a group of enterprise data centers (DCs) being cost-heavy assets, grids could turn them into potential revenue making engines. How? In analogy with the exploitation of other property assets, grids resources should be commercialized or traded in exactly the same manner. Thus, CIOs will create a business plan that will either show income from grids or reduce costs by trading services with other players (computing cycles, data storage, or combinations of both – appearing as enterprise service grids). To come to this point, enterprise data centers should be re-architected properly aiming at such an explicit business objective [1]. A Enterprise Grid Bid

Regulatory Auditing Settlement Body

Grant

Grid Exchange Market Offer Scan

Deal B Enterprise Grid

Propose

C Enterprise Grid

Figure 1. The Rise of Grid Exchange Markets (GEM) : The Long-View Vision

We envision in the longer perspective the rise of Grid Exchange Markets (Fig. 1) which will enable smooth and efficient exchange of grid services. Basically, they should implement bidding/reservation/exchange protocols enabling smooth functioning in a manner similar to other known

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ISBN: 978-972-8924-30-0 © 2007 IADIS

exchange markets (money, stock, commodities, derivatives). This structural change will hopefully trigger wider commercial use and spread of enterprise grids. Assuming that this happens, appropriate regulatory, auditing and settlements bodies will oversee functions and regulate monetary flows among partners. We presume that this monetary interest will lead to the further developments of standards, technologies and regulation policies.

2. ENTERPRISE GRID APPLICATIONS The fate of grids in enterprise computing will depend on the widespread deployment of enterprise applications. These are large-scale, dependable applications serving a huge number of concurrent users, representing major workloads and typically executed on mainframe computers or specialized clusters. Currently they are denoted by the following acronym soup: ERP, CRM, SCM, EKM etc. A Conceptual model of the enterprise grid enabling interoperation of enterprise applications is given in Fig. 2.

Clients

Customers

Enterprise

CRM

ERP

Partners

SCM

EKM

Suppliers

Enterprise Grid

Figure 2. Enterprise Grid interconnecting DCs and enterprise applications

We believe that some enterprise applications will be only need slight adjustment for deployment on enterprise/corporate grids, while others will require a major re-architecting, re-designing and re-engineering effort. Broadly classified they will belong to: Enterprise resource planning (ERP) (2) Supply chain management (SCM) (3) Customer/Client relationship management (CRM) (4) Corporate finance and HR operations (CF/PM). Important to observe is that some of these might have inherent, serial/sequential architectures which could be difficult to parallelize and spread jobs over grids. Still, they all should be orchestrated into well-performing enterprise IT fabrics. We also expect that some novel applications will appear, and some entirely new uses of enterprise grids for internal purposes might be born. Generically, enterprise grids could be denoted as data, computational or content grids. Here are some of possible wider uses: (1) Very large-scale simulations and visualizations (to improve understanding, support decision making, provide optimization insights and planning assistance) (2) Digestions of huge corporate IT data sets coming from various production/live or staging platforms for analysis/debugging – to detect predictive signals, improve performances, support planning and decision making (event log analysis of a grid itself, for example (3) Enterprise content management (huge volumes, rapid dynamics, heterogeneous by nature) – objective to tag, categorize, classify content for various ultimate purposes (4) Enterprise knowledge management – becoming today more important then ever in the current global economy transitions. Highly abstracted, generic EA can be viewed as a composite application (web servers, application servers, database servers) supported by Storage Area Networks (SAN) and protected by corporate firewalls and made efficient via load balancers (security and overload protection) (Fig. 3). One point of warning here; while high-performance parallel file system have made significant advances in the recent years, it will still take

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IADIS International Conference Applied Computing 2007

some time and effort until they reach level of maturity and robustness required and expected by enterprise grade applications. Until then, their deployment should be carefully planned and managed [5].

Web Server

App Server

DB Server

Management Loops

Generic Enterprise Application (EA) Stack

Firewall Load Balancing

Storage Area Network

Figure 3. Composite Enterprise Application

We believe that the majority of enterprise applications can be reduced to this generic form. A consequence is that management thus becomes simpler and less expensive. This form also provides a unified view into entire application stack (as in the LAMP approach in open source) which has important architectural, design and operational advantages. Thus, we aim to abstract enterprise grid applications into this aggregated form.

3. SOME ARCHITECTING PRINCIPLES At the very high conceptual level, architecting of enterprise grids can be abstracted as mapping of enterprise applications onto heterogeneous enterprise resources. Consequently, in generic terms, one should aim to: + understand very well the nature, resource use and performance requirements of enterprise grid applications (study of EA workflows) + establish a holistic view of the grid infrastructure and provide necessary control tools (monitoring and management of resources) + ensure that enterprise decision-makers and users understand price/performance improvement and support evolutionary changes + assess evolving needs for the next 3 to 5 years, as EG will represent a major business investment and give realistic estimates of the benefits of enterprise grids deployment

Grid Utilization Rate

Grid Operational Risks

(MIN)

(MAX) Grid Cost/ Performances (MIN/MAX)

Figure 4. Grid Management Objectives : Delicate Trade-Offs

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ISBN: 978-972-8924-30-0 © 2007 IADIS

Architecting efforts are seen as the delicate, balancing acts aiming to: (1) maximize utilization of resources, (2) improving system cost/performances and (3) minimizing operational risks (Fig. 4). The overall aim of grid management should be to achieve an optimal set of operational parameters here and maintain them in balance. This remains to be a very complex issue and creates several practical and research challenges. Further research will clarify an overall architecture of grid monitoring and grid management system which will form the basis for billing and accounting system as crucial component of commercial grid uses.

4. CONCLUDING COMMENTS Grids are the result of aggregation and virtualization of various enterprise resources leading to major price/performance improvements, which might spawn an entirely new class of large-scale applications. So far, research applications requiring grid resources (e.g., large-scale distributed computations) have not faced the hard challenges of business deployment of grids. These challenges have been summarized into ‘grid dependability’ [2], comprising security, availability, reliability, safety and privacy concerns. Another point is that scientific application of grids typically require homogeneous resources, while enterprise applications will have different grid topology requirements and very different workload characteristics [3] (asynchronous, real-time time requirements for trading desks in financial institutions, for example). For different types of grid applications, the focus will be different. Thus, for financial (services) grid applications privacy and security will be of prime importance; for telecommunication (non-stop) industry reliability will be the key; and for movie (rendering) industry timeliness will play the major role [4]. Architecting decisions should take into account these differences. We conclude by mentioning two questions that require further work. What are meaningful measures of grid performance? A supercomputer can be a node in a grid, but a grid is not a supercomputer. Grids will have to be multi-tiered CyberInfrastructures [6] in order to accommodate the spectrum of possible applications. Finally, the relationship among grids, service oriented architectures and web services will be increasingly important to enterprise grids.

ACKNOWLEDGEMENT We would like to thank the anonym reviewers for providing useful comments.

REFERENCES Paul Strong, 2005. ‘Enterprise Grid Computing’, ACM Queue, Issue 6 (July/August 2005) Kemal A. Delic, 2005. ‘On Dependability of Corporate Grids, ACM Ubiquity, Vol. 6, Issue 45 (Dec 7-13, 2005) Jerry Rolia et al., 2003. ‘Grids for Enterprise Applications’, http://citeseer.ist.psu.edu/rolia03grids.html Duncan Johnston-Watt, 2006. ‘Under New Management’, ACM Queue, Vol 4 No 2, March 2006 Selam Kapetanovic, Private Communication, January 2007 Gordon Bell, Jim Gray, Alex Szalay, 2005. ‘Petascale Computational Systems: Balanced CyberInfrastructure in a DataCentric World’, September 2005

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