To keep an organization’s digital core up and running, ITOps needs deep visibility and insight into every aspect of it. However, that quest for visibility often leads to monitoring and observability tool sprawl, layers of disjointed, fragmented data silos and ultimately, an uncontrolled volume of alerts that make it difficult to detect and respond to the ones that are actually important. Enriching alerts with context raises their level of actionability, allowing organizations to effectively cut through the noise and reclaim control of their IT operations.

As applications, services and infrastructure accumulate over time (organically or through mergers and acquisitions), ITOps organizations add monitoring tools that generate more alerts. As alert volume increases over time, the quality and usefulness of alerts tend to decline, making it hard to discern which alerts are important and need attention. In many cases, however, no structured practice exists for regularly assessing alerts to determine whether they need to be modified or retired. Left alone over time, the resulting environment of IT noise can dramatically overwhelm even the most well-designed incident and alert management workflows and intentions.

Consider the hypothetical case where an organization receives 500 monitoring alerts in its first year. As the scope of monitoring grows, the number of new alerts generated, in addition to the existing alerts, increases by 15%. After 10 years, assuming none of the alert sources were taken out of service, there will be 12,175 total configured alerts in the environment.

At that rate, the proportion of noise to signal would grow from 5% at the outset to become the majority of all alert traffic by year 10. A few years later, the number of actionable alerts—or those that should be acted upon based on the alerts’ quality, priority and other contextual data—would level off and begin to fall as growth in the number of noisy alerts accelerates. A company that began monitoring in the year 2010 would have more than three times as many noisy alerts as actionable ones by 2022. This hypothetical case reflects the reality in many organizations, where most alert data is unactionable noise.

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Cutting through alert noise with high-quality alerts

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