Server monitoring is an essential tool for all industries, whatever company size, as no one is happy when a server goes down. When it happens, it’s usually a fire drill for the IT team to figure out what’s wrong, and some times it results to a blame game with no clear culprit.
Server monitoring software is essential for alerting you when there are issues that may lead to server down time, before it really happens. Proactive monitoring can help you resolve issues quickly and, most importantly, giving you data so you can avoid downtime.
The benefits of server monitoring are many, but these are the most important:
- Increased server, services, process, and application availability
- Fast detection of network and server outages and protocol failures
- Fast detection of failed servers, services, processes and batch jobs
Here are a few specific principles of server monitoring that can minimize downtime.
Unified Server Monitoring
Obviously, effective server monitoring shouldn’t be only about whether a physical or cloud-based server is up or down.
In order to be proactive, you’ll need a better sense of how the environment around the server is performing with server monitoring software that can monitor everything, from disk space to the air temperature in the server room, but also servers, network equipment, databases, websites, and SNMP-enabled devices.
To do this, you need a unified monitoring solution that can monitor it all: What website traffic is doing, where the choke points are, how individual workstations are operating, and so on. When the server goes down, you’ll have a full map of your network’s status to pinpoint and fix the issues.
By monitoring servers and the entire network with one unified solution, you gain a better view of what is going on around the servers and can then monitor multiple possible points-of-failure within a process. Fixing a single-point-of-failure within a process before it becomes a total failure, results in a “marked” decrease in downtime.
Proactive server monitoring alerts
Proactive alerting allows systems administrators to set up alerts to notify users of potential issues before a device, server, or network goes down.
A critical capability allowing proactive alerts is the ability to configure parent-child relationships. Server monitoring software solutions capable to map out relationships and dependencies on the network will give you a better sense of what’s failing during a downtime.
For example, if you get an alert that a firewall goes down and you can’t reach a server beyond it, you don’t have to waste time figuring out if something is wrong with the server; you can immediately identify that the downed firewall is the problem.
But proactive alerts are realized with Threshold Crossing Alerts (TCA). The capability to define thresholds on monitored performance indicators such as latency, response time is very important, as it is the main function that can notify administrators of issues before they become critical.
Machine learning in server monitoring
The next level of proactively heading off downtime is realized with machine learning. With machine learning, the server monitoring software can “learn” key behaviors of your network, like the rate at which data is used and use predictions and anomaly detection to proactively alert you of potential future issues.
For example, let’s assume your hard drive gets X amount of data every day taking into account seasonality. A machine learning capable server monitoring software will then predict the number of months you’ll run out of space . If this happens, the hard drive will start writing over old data, and you’ll lose it forever.
By alerting you to this issue, you can be sure to plan ahead and either move data or purchase more space. In addition, machine learning can be used to detect anomalies in data rates, that can point you to processes or components that are misbehaving and creating as a result data in an abnormal rate.
Server monitoring is an essential way to get to the heart of an emerging issue proactively, proof its cause, and fix it accordingly, decreasing downtime.