Network Management Proactive, Reactive or Predictive?
Proactive, Reactive or Predictive Network Management
Enterprise infrastructure today is complex, where more and more devices are coming online and being connected to more and more networks. As a result of this complexity the potential of human errors will be on the rise. Network outages are becoming more common, since IT teams are being asked to do more with less. As a result, the process of picking a network management software has never been more essential. Enterprises that choose to be reactive will suffer outages that will cause business interruptions, slowdown in user productivity and damage brand prestige. Companies that choose inaccurately can have costs as high as $46MM per year. (Source: Evolven)
Today’s Status Quo and the Risk Involved by Not Opting for Change
As an IT pro, you know the reactive model well. You’re using it now. You learned it from others. Passed down through generations of IT operational teams. With the same old solution (ie: Network Management solutions that are SNMP based), come the same issues: hundreds of false positives, endless hours of being on call, constant firefighting, etc. As the enterprise infrastructure gets more complex, the possibility of outages and failures increases based on the law of probability. If you continue with the status quo reactive model, the likelihood of receiving a service call from an angry user or a system generated alert corresponding to an app failure is almost inevitable. The biggest drawback to IT Ops teams will be time. Time that could have been spent on expanding capabilities will now be reduced to writing scripts manually or searching through runbooks for solutions to prevent the next failure.
The Proactive Model
Being in an IT Ops team, we all know that this model is best for network management, but it is difficult to achieve manually. Some IT pros set priority to sectors of their infrastructure they see as “most vulnerable” and develop their own tool set to implement proactive techniques to manage their network. The problem arises since many of the tools used to have different capabilities. For example a monitor for bandwidth maybe great at handling historical data, while others do better with real time. Many companies do their best with the systems they have by hacking a variety of tools together to create a manageable infrastructure. They often create checklist that will sequence device backups or process that need to be restarted manually. Often this method works, but not for long, since IT pros work in crowded environments where transparency may not always be the norm. The proactive method of network management by itself, is flawed since it’s scalability is limited to the capabilities of the tools used for monitoring failures and outages.
The Predictive Model
With the rise of machine learning algorithms comes a new age in network management: The Predictive Age. Used primarily, by early adopters in IT ops teams, this model implements predictive analytics and automation methods to anticipate issues before they become downtime often without the need of multiple tools and checklists. Imagine being in an IT teams using the predictive method of network management that:
Benefit from the wiki effect of network knowledge gathered by machine learning, often with remediation steps and links to product information about the issue. Enhanced capabilities of 24/7/365 predictive modeling for 99.9999% often elusive with ancient monitoring tools. Furthermore, the predictive model supports multiple technologies from F5, Blue Coat Proxys, Cisco, PAN and Check Point firewalls.
If you’re an IT Pro today, the possibilities of using machine learning to leverage your workload, have deep visibility and reduce service interruption while cutting support and operating costs is here. All with one tool: indeni was created to make the life of IT pros easier, by using a predictive model of network management to ease the burden of complex networks.
With Indeni, you are just steps away from predicting your network outage before the alarms go off or your customers take to Twitter to rant about the lack of performance in your brand.