We recently started using BigPanda for event and alert management. Our team, new to incident management, is still learning. 

BigPanda is used for event correlations, deduplication, suppression, and auto incident creation. Those are the basic functionalities that we were looking for.

If the solution is already deployed in the customer environment, we leverage what the customer has invested in and add on to the existing environment. We use this solution for event management and correlation. We also use it for root cause analysis and SOP-based Runbook Automation. We monitor incident dragging and incident root cause analysis.

Event management.

We use BigPanda to connect to Slack, and all our alerts from BigPanda automatically go to Slack. I'm a DevOps engineer and I believe we are customers of BigPanda. 

We primarily use this solution for predictive analysis and for enhancing our forecast.

We wanted a 'one-stop-shop' for event monitoring, visualization, and infrastructure development with AI. Unfortunately, BigPanda attempts a little bit of everything and fails at most. 

The AI, in particular, was worthless. The visualization is primitive and not configurable. The only thing they seemed to be able to do is to collect a bunch of identical error messages into one - which is great and all, however, hardly the 'advanced AIOPS solution' they tout.   

The best of a bad lot was the error message deduping. We wanted a 'one-stop-shop' for event monitoring, visualization, and infrastructure DevOps with AI. 

We use BigPanda to aggregate alerts from multiple sources (Nagios, Sensu, Wavefront, Splunk, etc.) and correlate related alerts into incidents.

We use BigPanda for monitoring and management. Our servers are all configured with New Relic, which sends the data to BigPanda.

We use the solution for a central management console.

We use this solution for alerting purposes to track the health of our infrastructure and services.

BigPanda is an endpoint protection solution against ransomware.