Where is IBM at with its autonomic computing initiative?
We started in 2002 with a focused initiative to drive the concept of self-managing systems across IBM and the industry. I don’t think of autonomic computing as an IBM initiative, but an industry initiative that IBM wants to help lead. We have had a two-prong approach: to help make IBM products more self-managing and to help drive the industry as a whole towards better self management through open standards and broad research. We have been working with a number of partners to drive open standards which will allow for autonomic behaviours across a heterogeneous IT environment — WSDM, SML and the CIM Simple Policy Language are examples of this. We have also engaged with numerous universities to encourage more research in developing self-managing systems.
How has IBM incorporated this idea of intelligent automation across its software and hardware brands?
Autonomic features run across the entire IBM portfolio, from chips to business systems management software. For example, several years ago we announced chip technology that is self-modifying using our eFuse technology. Our DB2 product line has implemented numerous autonomic technologies to manage the formerly labour-intensive management tasks associated with large databases. The same can be said for IBM’s TotalStorage products — reducing the cost of management for large storage-area networks. IBM WebSphere, our J2EE application server, now has policy-driven autonomic technology that allows for dynamic workload redistribution and self-optimisation.
How does IBM’s Tivoli management software fit into its autonomic vision?
Tivoli is a very important piece of the autonomic strategy. The work described above is at the IT component and subsystem level. Tivoli delivers autonomic value at the datacentre level. Tivoli is focused on integration of the various system management technologies to deliver the policy-driven automation capabilities we call the Autonomic Data Centre. Encoding into the system the decision-making loops for repetitive tasks takes a huge workload and burden off the IT administrator. Making it policy-based then links it to the business that IT supports.
What are some common ways IBM customers are using autonomic computing today?
In the database world, many of the tasks formerly requiring database administrators’ time to keep the database optimised are now handled by intelligent algorithms and autonomic managers built into DB2. Manual workload prioritisation and balancing processes have been replaced by policy-driven management in IBM WebSphere. System failover processes have been automated via policies in Tivoli’s System Automation. Tivoli Provisioning Manager and Intelligent Orchestrator provide a policy-driven approach to dynamically adding servers to a server pool when more resources are required.
How can customers tie together disparate automation efforts to achieve a more automated datacentre?
Through open standards. Complete datacentre autonomic behaviour will not be possible without agreement on some key standards and conventions, which is why IBM is pushing so hard for standardisation in the IT management space that includes standard models, standard protocols, standard interfaces to resources and standard data formats.
How does autonomic computing differ or relate to operational automation efforts such as run-book automation?
Automation technologies like run-book automation are steps along the path to autonomic computing. We talk about autonomic computing as an evolutionary process and have even defined the five levels of autonomic computing. Run-book automation today is about level three. As automation becomes more mature, with capabilities being decision-based or policy-based versus time-based or human-initiated, it will evolve to be true autonomic behaviour, which makes the IT infrastructure responsive to the business it serves via well-defined business policies and service-level agreements.
Can emerging technologies drive or enable the adoption of autonomic computing?
Yes. Virtualisation and SOA are two good examples of this.
In two ways. First, they both are enablers for making autonomic computing possible. Dynamic provisioning of virtual resources, for example, is much easier than dynamic provisioning of physical resources. Likewise for SOA, the existence of an SOA infrastructure makes autonomic management at the datacentre level much easier, as you can ride on that infrastructure (web service interfaces, ESB, XML transformations) for your IT management events just like you do for business events. Second, they both bring another level of complexity to IT management. How do you monitor a virtual application if it keeps getting re-hosted on different physical machines? With more complexity comes a greater need for autonomic management.
What areas are still not quite there yet in terms of automation?
I think there is a lot of work to be done in learned behaviour. We have a lot of technology now for encoding behaviours into autonomic systems — policies, run books, workflows, CMDBs, IT process automation. But we don’t have many examples of the system learning behaviours that can then be retained as knowledge. I think there is a lot of exciting work to be done here.
What inhibitors remain to autonomic computing?
We have done ethnographic studies in IBM Research on how IT operators and administrators will react to increased automation in the datacentre. It has to be presented in a way that lets the human manage the rate and pace of adoption, not have it forced upon them. Part of the challenge is convincing folks that autonomic computing will allow them to do their job better, not take their job away.