It’s hard work managing networks for enterprise clients, and that work gets harder all the time as networks get larger and more complex, client activities grow more bandwidth-hungry, and user patience evaporates.
In this work, network managers rely on alerts to tell them that something is wrong with the network before users get irritated and start opening tickets; guide them to the root cause of the problem; and help them understand how to fix it, making them vital for efficient management.
The more relevant, timely, and detailed those alerts, the more they can ease the burden for network managers, which lies behind the recent rising interest in customizing network alerts.
Today’s alert systems are crucial, but they have weak points which handicap IT teams. For a start, networks have masses of data sources relating to almost every entity in the IT environment, each generating automated alerts. Every vendor has its own best practices for when, why, and how to trigger an alert, potentially resulting in millions of events per hour. Network managers are flooded with alerts, each bearing data that needs to be read, understood, and analyzed.
The problem is compounded by the fact that the alerts are neither specific nor relevant enough to provide accurate information. Many systems are highly sensitive and produce numerous false alarms, and alerts are not set according to the behavior of each network, which can vary widely. As a result, alerts could be about anything from extremely consequential events to trivial blips. The network manager has to investigate each with the same rigor, examining logs for root cause insights and possible resolutions.
This makes root cause analysis very work-intensive. Network management teams have to comb logs for relevant data and collect it into a single place. Simply gathering data takes time, because there is so much to sort through. Log data is difficult to scan, with information stored in hard-to-read formats and units that change from line to line and device to device. A network operations employee might have to decide what to do with thousands of such lines.
Unfortunately, most of today’s network alert systems go broad, but not deep. They provide a useful wide overview, but don’t dig deep enough into networking to guide IT teams through the maze of data.
Network managers can customize which notifications reach them through different channels, but there’s no way to adjust the thresholds at which alerts are generated. Teams have no choice but to get all the alerts, all the time.
Network management systems currently take alert data from their logs and send it to another system, which displays the information in a different format (e.g. JSON) that can hold richer data than the original log and is easier to understand. However, network ops teams still receive thousands of these reports on a regular basis, and have to find a way to understand them.
As a result, network operations teams generally possess all the data they need to resolve network issues, but very few of the tools that would assist them in the process. Barely anything is automated; a team has to manually assign an expert to collect the relevant data, analyze the implications, and produce meaningful and actionable insights and resolutions.
Customized alert notifications can address each of these pain points and more. A customized network alert notification system filters out irrelevant alerts, making those that remain more relevant. Fewer alerts reach IT teams, so they can dedicate more time and attention to the complex and significant ones before them.
Customized network alerts can help speed up root cause analysis and resolution. Without the distractions and confusions of extraneous alert information, network managers can more quickly identify relevant data. Some systems, such as NetOp, make it even faster by automatically pushing the relevant data and helping teams to proactively resolve issues. They can put together meaningful anomalies and draw on patterns of recurring issues to surface insights and resolutions that are more likely to be correct.
Alerts that are set according to specific network behavior are more granular, and can compound multiple KPIs to deliver a deeper and more targeted view of the source of the problem. They are more informative, cutting analysis time and helping network operations teams reach resolution more quickly.
The current method for monitoring network issues is highly reactive. Teams often don’t know about a network problem until someone gets in touch about it, and then they start investigating root causes and resolutions. But customized alert systems like NetOp can preempt a trouble ticket. They use artificial intelligence (AI) to understand how the network behaves, and set customized alert levels according to each network’s particular behavior. This way, network teams can receive advance notice about an event and resolve it faster, sometimes even before the user notices that there is an issue.
Organizations that use a better-adapted threshold for alerts will avoid constant disturbance from inapplicable alerts triggered by over-sensitive vendor network threshold settings. Network operations teams will need fewer resources to sift through logs, find the relevant data among the haystack, and analyze it for insights and resolutions, bringing cost reductions to the organization.
Network managers will be freed to focus on more important issues, like network resilience and advance threat planning, rather than constantly rushing to put out fires. Teams can work more efficiently on a daily basis thanks to the noise reduction from fewer irrelevant alerts, and feel greater job satisfaction through decreased stress and pressure.
NetOp can address all the weak points left by today’s alert systems. It enables network ops teams to tune network alert settings more finely, so they are only triggered by a particular combination of signals or frequency of violations. After learning the behavior of the network, NetOp’s AI engine can go further and set dynamic AI-managed thresholds that are customized for each particular network.
By employing AI, NetOp can identify the pertinent alerts for any given network issue, correlate data, and produce insights that serve as a shortcut to root cause analysis and issue resolution. With the help of NetOp, network operations teams can often proactively resolve issues before a ticket is opened, saving time and other resources which can be deployed elsewhere to improve and strengthen the networks.
By saving network operations teams time and effort in identifying and resolving network issues, customized alerts can become indispensable tools to ensure greater uptime, more resilience, lower costs, and less frustration across the organization, ultimately helping underpin business strategies and drive profits.
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