Conclusion

This report reveals a critical truth: Monitoring and observability tools generate vast amounts of data and noise without delivering the actionable context L1 detection teams need to identify, triage, and respond to alerts. As a result, frontline L1 teams struggle to distinguish actionable signals from noise, requiring large in-house and managed service provider (MSP) teams to manage all the data and escalate issues to L2 incident response teams.

In addition, while many organizations say they are centralizing observability, the data shows that most have 20 or more integrations with monitoring, observability, and other tools. It suggests that many are struggling to optimize them to reduce noise for siloed incident response teams that don’t use those tools.

BigPanda helps enterprises quickly detect, prioritize, and respond to actionable incidents. The BigPanda team is also dedicated to helping customers get the most value from the platform. They monitor usage to help customers adopt best practices for better event and incident management outcomes.

As enterprises adopt a more autonomous and agentic ITOps platform like BigPanda, they can automate incident detection and remove blind spots from their observability data. Using AI-driven correlation across not just observability data, but also service desk tickets and external service provider dependencies such as ISP, utility, and cloud provider outages, enables teams to detect early signals of incidents and respond fast.

Schedule a Demo

The next BigPanda report will examine the business value customers receive from the BigPanda platform.

Sign up to receive an alert when the business value report is published.