Incorporating self-managing capabilities into an IT environment is an evolutionary process. It is ultimately
implemented by each organization through the adoption of self-managing autonomic technologies, supporting processes,
and skills. Throughout this evolution, the computer industry will further develop self-managing technologies to help
continue to improve staff productivity, reduce operating costs and, ultimately, increase business resiliency.
It is possible for an organization to calibrate the degree of autonomic capability that their current infrastructure
and organization has and to develop action plans to increase the autonomic potential. There are five phases of this
progression through the levels of autonomic maturity.
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Management Areas
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Levels of Autonomic Maturity
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Basic
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Managed
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Predictive
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Adaptive
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Autonomic
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Process
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Informal, reactive, manual
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Documented, improved over time, use of industry best practices, manual process to review IT performance
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Proactive, shorter approval cycles
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Automation of resource-management and transaction-management best practices, driven by service level
agreements
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Automation of IT Service Management and IT Resource Management best practices
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Tools
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Local, platform and product specific
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Consolidated consoles, problem management system, automated software install, intrusion detection, load
balancing
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Role-based consoles, product configuration advisors, real- time views of current and future IT
performance, automation of some repetitive tasks
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Policy management tools drive dynamic change based on resource-specific policies
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Costing and financial analysis tools, business and IT modeling tools, trade-off analysis
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Skills
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Platform specific, geographically dispersed with technology
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Multiple platform and multiple management tool skills
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Cross-platform system knowledge, IT workload management skills, some business-process knowledge
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Service objectives and delivery per resource, analysis of impact on business objectives
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e-business cost-and-benefit analysis, performance modeling, advanced use of financial tools for IT
context
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Benchmarks
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Time required to fix problems and complete tasks
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System availability, time to close trouble tickets and work requests
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Business system availability, service level agreement attainment, customer satisfaction
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Business system response time, IT contribution to business success
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Business success, competitiveness of service level agreement metrics, business responsiveness
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The autonomic levels of maturity, as they correspond to the different areas of management focus for an IT
infrastructure, are:
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Manual – in which IT professionals perform the management functions.
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Managed – in which systems management tools can be used to collect details from managed resources, helping to
reduce the time it takes for the administrator to collect and synthesize information as the IT environment becomes
more complex.
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Predictive – in which new technologies are introduced to provide correlation among several managed resources. The
management functions can begin to recognize patterns, predict the optimal configuration and offer advice about what
course of action the administrator should take. As these technologies improve and as people become more comfortable
with the advice and predictive power of these systems, the technologies can progress to the closed loop level.
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Adaptive – in which the IT environment can automatically take actions based on the available information and the
knowledge about what is happening in the environment.
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Autonomic – in which business policies and objectives govern the IT infrastructure operation. Users interact with
the autonomic technology tools to monitor business processes, alter the objectives, or both.
It can be seen from this that there is significant business value in progressing from one autonomic maturity level to
the next, since administrative personnel would then be able to focus on a wider scope of operations and business
processes, and the IT system is more reliable and self-managing.
In addition to increasing levels of automation, the automation is applied across broader scopes and within more
processes as the organization progresses to higher levels of autonomic maturity. Of course, increasing the autonomic
maturity could also involve changes in procedures, skills and organization as more tasks and activities are handled by
the technology itself.
This view supports autonomic computing evolution by enabling incremental adoption of additional autonomic capabilities.
The adoption model structures a solution space so that a business can produce an incremental action plan to take
advantage of offered autonomic capabilities.
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