What happens when you receive a notification that something is wrong with your system and you have no clue what it means, or why you’re receiving that alert? Maybe you have to parse through the alert conditions to suss out what the alert indicates, or maybe you need to ping a coworker and ask. Not knowing what to do with an alert also contributes to alert fatigue, because it increases the toil and time required to respond.

Your payment systems have slowed to a crawl, customers are getting impatient and abandoning their shopping carts both online and in stores, and you’re losing money every minute this problem goes on. Behind the scenes, technical responders are scrambling to resolve the issue before it impacts more customers—and before even more money is lost.

Within the cyber security industry, it is well known that as a company grows, so does its attack surface. This trend lends itself largely to the fact that as more employees are hired, more company-owned machines (laptops, tablets, etc.) are distributed. The risk is that once a company-owned machine is given to an employee, it is up to the employee whether to follow the security best practices set forth by your company. Your technological asset has now become a security risk.

Alert noise is reaching an all-time high in IT organizations. The volume of these alerts from disparate tools and technologies has reached a point where they are greatly undermining the ability of IT organizations to properly manage, secure and optimize services and applications for users and customers. DEJ’s recent study on AIOps found that organizations currently spend $1.27 million annually on avoidable incident escalations that result from non-contextual and non-actionable alerts.

GroundWork Monitor offers Parent Child configurations for distributed monitoring, enabling the monitoring of a subset of an infrastructure where Child servers report the state and performance metrics to a central, or “Parent” GroundWork server.

Have you ever been paged for a critical issue and started troubleshooting only to find an obvious drop in requests that weren’t caught by a static threshold? Or a significant increase in a metric that didn’t cross a static threshold? Or even, evidence of warning alerts triggered long ago that should have enabled someone to resolve the issue and prevent it from causing business impact, but instead was ignored in the massive alert volume received by the team?

Keeping a server running optimally on a consistent basis involves managing multiple system elements simultaneously. Automated scripts and specialized software can handle the tasks your server needs to complete on a daily basis—but when one of these experiences an error, it can throw the entire system off.