System Implementation – 27th Edition (Spring 2010)

System Implementation – 27th Edition (Spring 2010)

Successful system implementation requires good leadership and careful planning. A good understanding of every component of the system is critical in putting together an implementation strategy. Enterprise IT environments involve integration of a variety of vendor technologies. Interoperability standards within commercial software environments are voluntary, and even the most simple system upgrade must be validated at each step of the integration process.

Enterprise GIS environments include a broad spectrum of technology integration. Most environments today include a variety of hardware vendor technologies including database servers, storage area networks, Windows Terminal Servers, Web servers, map servers, and desktop clients,—all connected by a broad range of local area networks, wide area networks, and Internet communications. All these technologies must function together properly to support a balanced computing environment.

A host of software vendor technologies including database management systems, ArcGIS Desktop and ArcGIS Server software, Web services, and hardware operating systems—all integrated with existing legacy applications. Data and user applications are added to the integrated infrastructure environment to support the final implementation. The result is a very large mixed bag of technology that must work together properly and efficiently to support user workflow requirements.

The integration and implementation of distributed computer technology have become easier over the years as interface standards have matured. At the same time, enterprise environments have become larger and more complex. The complexity and risk associated with an enterprise system deployment are directly related to the variety of vendor components required to support the final integrated solution.

Centralized computing solutions with a single database environment are the easiest environments to implement and support. Distributed computer systems with multiple distributed database environments can be very complex and difficult to deploy and support. Many organizations are consolidating their data resources and application processing environments to reduce implementation risk and improve administrative support for enterprise business environments.

GIS Staffing
Good leadership begins with proper staffing. Successful GIS enterprise deployments are normally supported by an executive business sponsor, and the GIS manager should report to senior management.

Figure 12-1 shows an overview of a traditional GIS matrix organization. Enterprise GIS operations must be supported by an executive committee with influence and power to make financial and policy decisions for the GIS user community. GIS manager should establish a technical coordinating committee responsible for providing technical direction and leadership. Committee leaders should chair working groups assigned and aligned with each technical discipline to address organizational issues and report on system status. The user community should be represented throughout the review process.

A formal organizational structure provides a framework for establishing and maintaining the long-term support required for successful enterprise GIS operations. This basic organization structure can be useful in managing GIS in small to large organizations, and the same type of organizational structure can be effective in managing community GIS operations.



Identify Key Staff Functions
Several technical disciplines are required to support successful GIS operations. Figure 12-2 identifies the role and key functional responsibilities required to support enterprise GIS operations.

The complexity of these responsibilities will vary with the size and extent of each individual GIS implementation, although every organization will need some level of support and expertise in each of these areas.



Build Qualified Staff
Training is available to help build qualified staff and improve GIS user productivity. Organizations should make sure their teams receive the required training they need to be effective in their job. Figure 12-3 provides an outline of recommended ESRI training courses available to support GIS staff.



System Architecture Deployment Strategy
Normally planning is the first step in supporting a successful system deployment. A system design team should review current GIS and hardware system technology, review user requirements, and establish a system architecture design based on user workflow needs. A deployment schedule, as shown in Figure 12-4, should be developed to identify overall implementation objectives.



Phased implementation strategies can significantly reduce implementation risk. Computer technology continues to evolve at a remarkable pace. Integration standards are constantly changing with technology and, at times, may not be ready to support immediate system deployment needs. New ideas are introduced into the market place every day, and a relatively small number of these ideas develop into dependable long-term product solutions. The following best practices are recommended to support a successful enterprise GIS implementation.

Pilot Phase • Represent all critical hardware components planned for the final system solution. • Use proven low-risk technical solutions to support full implementation. • Include test efforts to reduce uncertainty and implementation risk. • Qualify hardware solutions for initial production phase.

Initial Production Phase • Do not begin until final acceptance of pilot phase. • Deploy initial production environment. • Use technical solutions qualified during the pilot phase. • Demonstrate early success and payoff of the GIS solution. • Validate organizational readiness and support capabilities. • Validate initial training programs and user operations. • Qualify advanced solutions for final implementation.

Final Implementation Phase • Do not begin until final acceptance of initial production phase. • Plan a phased rollout with reasonable slack for resolving problems. • Use technical solutions qualified during previous phases. • Prioritize rollout timelines to support early success.

Virtual Desktop and Server Technology
Virtual server technology is continuing to mature and reduce the cost of managing a rapidly changing IT environment. Figure 12-5 identifies a deployment strategy taking advantage of virtual server technology. Many GIS operations are being deployed into virtual server environments. Many ESRI development and testing operations are currently supported in virtual desktop or virtual server environments. Vendors are improving management and performance monitoring of virtual server environments, and it is becoming more practical to manage and deploy production environments in virtual server deployments.



Platform virtualization technology provides IT managers with a way to abstract the installed platform software environment from the physical platform hardware. There are two fundamental levels of virtualization, one being virtual desktop environments hosted within a physical platform operating system that interfaces with the physical platform hardware and the other being a virtual server environment hosted on a hyper-visor layer that interfaces with the assigned physical platform hardware. In both cases, the virtual desktop or server contains its own dedicated operating system and software install separate from other virtual systems deployed on the same hardware.

There are many recognized benefits and some potential disadvantages with virtual desktop/server deployments.

• The benefits include faster provisioning times, physical server platform consolidation, fast recovery from system failures, simplified production delivery and recovery, and optimum configuration control. All of these benefits directly contribute to lower overall systems management costs and a more stable operating environment.

• The disadvantages include additional software cost and some performance overhead. There may also be functional limitations (limited access to hardware graphic cards and performance monitoring software) which in many cases can be managed with the proper deployment selections.

The real need for more rapid adaptive deployment schedules (to keep pace with changing technology) which also must be coupled with more stable production deployments (reduced production downtime and more rapid failure recover) drive the need for virtualized platform environments - virtualization is one solution that addresses some real IT management needs.

The potential disadvantages can be managed by proper deployment strategies. The performance overhead for virtual desktop environments is much higher than for server environments, and for this reason virtual desktops are normally limited to software development environments where performance and scalability is not a critical factor.

Server consolidation benefits can be leveraged in a Staging environment, were multiple release candidates can undergo test and validation in preparation for production deployment. Several production release candidates can be testing in parallel on the same physical server platform.

Production deployment can benefit from deploying an existing virtual server install (Staging configuration that has completed final test and acceptance) to a higher capacity production physical server by simply moving the Staging server release to the production platform. If there is a production failure identified after deployment; it is a simple process to move the production environment back to the previous release. Deploying virtual server staging environments to a physical server production environment is also a viable option - ensuring optimum performance and scalability for the production environment. Virtual server migration software is available to accomplish these provisioning tasks during live operations with no production downtime.

Virtual server performance impacts will depend on the workflow environment, and can vary between 20 - 50 percent (and sometimes higher) in the most efficient virtual server configurations. Hardware platform performance has improved over 70 percent within the past year, which more than overcomes the virtual server processing overhead. The new servers also provide higher capacity (discussed in chapter 9), which opens the door wider for server consolidation benefits. Virtual server deployments appear to be moving to mainstream IT production environment. The big question is no longer whether it makes sense to deploy on virtual servers, but rather when and which software vendor virtualization solution will provide the highest return on investment.

Technology Product Life Cycle
Figure 12-6 provides an overview of the technology product life cycle, from initial introduction of a new idea (product innovation) through end of life. Technology is changing faster every year, and managing technology change within a production environment is a challenge for GIS managers and IT administrators.



We are seeing an increasing number of new ideas introduced into the marketplace, with each idea promising improved user productivity and simplified system administration. These new ideas must integrate with existing systems that are constantly changing, and initial implementation can be painful.

Some of these ideas deliver on their promises, and in time they provide significant productivity advantages and reduce overall cost of administration. Soon a new idea comes along that performs better at reduced cost, and organizations must move on to new frontiers leaving legacy systems behind.

Selecting the right technology at the right time will optimize business performance. Introducing new technology before it is ready for prime time can reduce productivity and increase implementation cost. Delaying too long can result in missed opportunities. Getting the timing right promotes success.



System Testing
Conducting proper testing at the right time can contribute to implementation success. Functional component and system integration testing should be conducted for new technology during prototype development and before introduction into production. The primary focus during this testing is to make sure everything works. Performance targets established during the initial system design can be evaluated during early testing, paying close attention to map display performance and layer complexity (see Chapter 3 Software Performance). This is an opportunity to evaluate workflow functions and reduce processing overhead.

Enterprise system environments are becoming more complex. Testing should be conducted in a production software environment (same operating system, service pacts, software architecture, etc). Configuration challenges such as firewall access, security, and high availability should be configured and tested before deployment. Figure 12-7 shows a typical data center architecture for emerging enterprise GIS operations. Development and test environments should be established to represent the complete software configuration for each production release cycle.



Functional Testing
Figure 12-8 identifies best practices for planning and conducting functional system testing.

A test plan should be developed with clearly defined test requirements, establish configuration control (software versions, operating system environment), and provide test procedures. Testing should be completed before production deployment. Testing should be conducted using the software versions and operating system that will be deployed in the production environment.



Performance Testing
Figure 12-9 identifies some cautions and warnings associated with system performance testing.

Performance testing can be expensive and the results misleading. Normally initial system deployments need to be tuned and optimized to achieve final performance goals. Often system performance bottlenecks are identified and resolved during initial deployment. Early application development focuses primarily on functional requirements, and performance tuning is not complete until the final release. Actual user workflow environments are difficult to simulate, and test environments seldom replicate normal enterprise operations.

The scientific method introduced with grade school science fair projects provides some fundamental best practices that directly apply to system performance testing. Performance testing should only be conducted to validate a hypothesis (something you think you know). The primary objective of a performance test is to validate the hypothesis (confirm what you know). The test is a success only if it proves the hypothesis (testing does not teach you what you don't know).

Initial performance testing often fails to support the test hypothesis. With further analysis and investigation, test bottlenecks and/or improper assumptions are identified that change the test results. Performance testing is only successful if it validates the test hypothesis. A scientific approach to testing (Scientific Method)can help develop a true interpretation of the technology. Technology is changing with each service pack release, and this requires an open mind and willingness to continually change what we believe to be true.

System performance testing is best conducted during the initial production deployment. During this phase, real users doing real workflows can generate a real user environment. Critical system components should be monitored during the initial deployment to identify processing bottlenecks and resolve system conflicts. Compliance with design performance targets can be validated by observing system throughput and utilization during initial user operations. Initial deployment acceptance should include validation that user workflow performance goals are met.

Systems Integration Management
Basic project management practices promote implementation success. Project teams should be established, individuals should be assigned specific responsibilities, a task plan should be developed to support implementation planning, a configuration control plan and change control process should be established, and an implementation schedule should be published to support project deployment milestones.

A system architecture design can provide the framework for establishing an implementation plan. The implementation plan should be developed after final selection of the hardware vendor solution. Figure 12-10 provides a typical system deployment schedule. Specific decision milestones should be included in the schedule and each major task effort clearly identified.

An implementation project manager should be assigned to make sure all tasks are well-defined, and every participant has a clear understanding of his/her responsibilities. A clear set of acceptance criteria should be developed for each implementation task and a formal acceptance process followed to ensure integration issues are identified and resolved at the earliest opportunity.

The capacity planning tool can be used by project managers to establish performance milestones and validate performance targets are met throughout deployment. Peak users can be identified for different project milestones, and system throughput and server utilization can be reported at each milestone to demonstrate performance goals are met.

Figure 12-11 shows some of the ArcGIS Server and system tools used for performance monitoring. Additional performance validation tools were discussing in Chapter 3 (ArcGIS Server 9.3.1. map optimization tools and the mxdperfstat performance monitoring tools). The performance terms and relationships discussed in Chapter 5, particularly the relationship between throughput (peak users or peak transaction rates) and utilization (server CPU or network bandwidth utilization), can identify if the deployed solution is performing within the initial project performance milestone.  Figure 12-12 shows how the capacity planning tool (CPT) can be used by project managers to establish specific project performance milestones and measure compliance. The CPT test tab is designed to translate throughput and utilization measurements to workflow service times that can be compared directly to the initial project workflow performance targets. Monitoring progress in meeting performance milestones can reduce deployment risk and ensure project delivery success.

When performance issues are identified early in deployment, proper adjustments can be made before impacting production workflow productivity (simpler map displays - less layers or generalize layers with large number of features, reduce number of current batch jobs during peak system loads, evaluate preprocessing alternatives (map cache, generalized geodatabase layers, etc). Chapter 3 identified a variety of ways to improve GIS display performance. Identifying and resolving performance issues before they become production level performance problems will promote deployment success.



System Tuning
System tuning is a critical part of final system integration and deployment. Initial system deployment is the first opportunity to begin performance tuning. Heavy batch processing efforts should be identified and separated from interactive user workflows and supported through a separate batch process queue. System backups and heavy processing workloads should be scheduled during off-peak workflow periods. System component performance metrics should be monitored on a periodic basis particularly during peak workflow periods to identify performance bottlenecks and address system deficiencies. Figure 12-31 provides an overview of the components supporting an enterprise GIS environment. Any component has the potential to introduce a weak link in the overall system performance equation.



Business Continuance Plan
Every organization should carefully assess the potential failure scenarios within its system environment and protect critical business resources against such failures. Enterprise GIS environments require a significant investment in GIS data resources. These data resources must be protected in the event of a system failure or physical disaster. Business recovery plans should be developed to support all potential failure scenarios. Figure 12-14 provides an overview of the different system backup strategies. A business continuance plan should be developed to address specific organizational needs in the event of a system failure or disaster recovery.



Managing Technology Change
Enterprise GIS operations require a combination of strategic planning and a continued investment in technology. Technology is changing very rapidly, and organizations that fail to manage this change fall behind in productivity and overall cost management. Managing technology change is a major IT challenge.

Enterprise operations should include a periodic cycle of coordinated production system updates. The planning and technology evaluation should occur one periodic cycle ahead of each production deployment, and these efforts should be coordinated to support operational technology needs. Figure 12-15 identifies a conceptual system architecture planning and deployment strategy for technology change management.

Planning and Evaluation: Planning activities should be established in a periodic cycle, coordinated to support the organization's operational and budget planning needs. Strategic plans should be updated to support a multiyear deployment strategy and published periodically (normally on an annual cycle).

The planning and evaluation process should include a requirements evaluation (strategic plan update), technology refresh (training and research), requirements analysis (process and requirements review), test and evaluation (evaluate new technology alternatives), and prototype validation (pilot test programs). Efforts should be scheduled to support the annual system deployment upgrade cycle.

System Deployment: Operational system upgrades should be planned on a periodic cycle, scheduled to implement validated operational enhancements from the planning and evaluation program. System deployment phases should include initial implementation (implementing changes in an operational test environment) to support deployment authorization. The program should also include planned schedules for new technology procurement and deployment on a periodic schedule (in some cases deployment upgrades can be implemented on a monthly or quarterly basis). All production system upgrades should be planned and scheduled with full support for ongoing operations.

Conclusion
Successful implementation depends on a good solid design, appropriate hardware and software product selection, successful systems integration, and careful incremental evaluation during installation. A phased approach to implementation reduces project risk and promotes success, providing the opportunity for early success and flexibility to incorporate new technology at low risk prior to final system delivery.

Guidelines are available to support a successful system design, even for large complex systems. Final purchase decisions are influenced by both operational requirements and budget limitations, introducing unique challenges for system design. Good leadership, qualified staff, and proven standard practices support successful deployments.

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