It's important to remember that all this activity takes place to support business or other organisational goals, so network intelligence should take those goals and policies into account. For example, the technical solution to a sudden wave of network activity might be to move some of the traffic to alternative links, but what if that activity is unofficial Web surfing in response to breaking news?
CA's Sonar technology puts network activity in a business context. It relates traffic to applications, and applications to system elements (such as routers and servers), giving insight into operational issues and costings.
Cruchley points out that autonomic, adaptive, and similar strategies promoted by various vendors mean systems will change dynamically, so such insights become essential. But like Munch, he calls for good change management processes. "The easy part is switching a new blade on... the hard part is managing the change around it," he says; you wouldn't start up a new server manually without following the established change process, so why would you do that in an autonomic environment?
CA's distributed intelligent architecture (DIA) combines facilities for policy-based self-deployment combined with the automatic discovery of servers and their sub-elements. Business rules are also incorporated, so the payroll system can be treated differently during pay and non-pay weeks, for example. When resources are scarce, it's important they are allocated according to business priorities.
Sonar can operate passively by watching for particular traffic and identifying the touchpoints, or in an active configuration, generating synthetic transactions. For example, it might identify the SAP-related traffic, and then monitor the service level agreements and sources of cost for those processes.
Similarly, Micromuse's Netcool/RAD identifies the key components in the service path between applications and users (eg, a mainframe, Web servers, load balancers, network links), and visualises the result. It takes the logical topology of the network and maps switches, servers, etc into applications. This has several advantages, according to Marks. Firstly, it allows a green/yellow/red light indication of a service's status. Secondly, monitoring can relate to service level agreements. Thirdly, the use of a service topology permits identification of the source of any problem.
With this tool, an IT department "can really prove its worth and compete against the threat of an outsourcing arrangement," he says.
The status of individual components is determined from Netcool agents running on servers, system logs, SNMP traps, and information collected by other software such as Netcool/Visionary and synthetic users at key locations around the network in order to get a true picture of response time. RAD assembles this information, determines if it is potentially service affecting, and then performs root cause analysis to display the nature and location of the problem and recommend a fix.
Conclusion
Networks are getting smarter, both in terms of the capabilities being added to the network fabric itself and the development of software and devices that are capable of managing network operations with little or no routine human intervention.
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