BigPanda is a useful AI-powered platform for IT operations because it helps me with large amounts of alerts and monitoring data. I like how it can correlate different events and turn them into more meaningful incidents instead of making teams manually review every alert. Its AI features can also provide incident summaries, identify possible root causes, and recommend actions, which can make troubleshooting much faster. Review collected by and hosted on G2.com.

BigPanda is mainly designed for enterprise IT and operations teams, so it can feel complex if you are not already familiar with monitoring, incident management, and AIOps. It also depends on having good integrations and data from your existing IT tools to provide useful context. Review collected by and hosted on G2.com.

Big Panda's Open Box Machine Learning architecture uses transparent logic to cluster alerts into an incident unlike other tools that just group alerts or predict a root cause without explaining why. BigPanda has completely transformed how our team handles operational alert noise. By consolidating millions of fragmented alerts into actionable incidents, it has drastically reduced our alert fatigue and cut down our MTTR. While it does require a serious investment in upfront data tuning and comes with a premium enterprise price tag, the return on investment is undeniable. It bridges the gap between our monitoring tools and ServiceNow beautifully, saving our analyst hours of manual troubleshooting during outages. Review collected by and hosted on G2.com.

We do have few legacy log sources that send inconsistent data and so BigPanda cannot correlate it properly as it relies on tagging, normalization, and regular expressions to group alerts. This is causing us to continually tune rules. Review collected by and hosted on G2.com.

BigPanda’s Open AIOps engine is excellent at cutting through massive alert noise. In a complex environment with multiple monitoring sources such as Dynatrace, Splunk, and ServiceNow, BigPanda seamlessly correlates thousands of raw events each day into high-confidence, actionable incidents. Its real-time topology mapping and automated root-cause analysis give operational teams clear, end-to-end visibility, helping drastically reduce our MTTR (Mean Time to Resolution) without forcing engineers to constantly switch between separate dashboards. Review collected by and hosted on G2.com.

The biggest drawback for me is the complexity of the initial setup. Fine-tuning event-correlation patterns to fit a large environment takes time and requires careful, ongoing adjustments so you don’t miss important signals. The user interface also comes with a bit of a learning curve, especially for team members who are new to the platform. Review collected by and hosted on G2.com.

BigPanda has been instrumental in tackling alert storm and brings clarity into incident management for us. Instead of toggling between numerous monitoring tool UIs to correlate alert events to a potential incident, we can visualize related alerts and focus on what matters. It speeds up troubleshooting and minimizes the likelihood that crucial alerts go unnoticed. Review collected by and hosted on G2.com.

Pricing is can get expensive if you're a small team to put it up over and also configure our integrations as well as correlation for the alerts in our environment take a little longer to get just right. Review collected by and hosted on G2.com.

I find BigPanda most appealing because it effectively filters out alert noise and provides a concentrated perspective on situations. It simplifies incident triage by grouping related events together, which makes it easier to identify and focus on the problems that truly matter. This means my team spends less time chasing a long list of individual alerts and can concentrate on the issues that require attention. The process significantly reduces time spent on incident prioritization and helps us get to the root of problems more quickly. The initial setup was straightforward, and once integration was implemented, the platform was simple to use for my team. Review collected by and hosted on G2.com.

The amount of tweaking required to enable the correlation and alerting to function precisely as desired is one area that could be improved. To ensure that related events are appropriately categorized and the team isn't still experiencing needless noise, some fine-tuning may be necessary in a larger setting. Additionally, I would like additional freedom to modify incident views and dashboards for various operations teams. Stronger incident reporting and analytics are other things I'd like to see. Without requiring as much human analysis, it would be helpful to simply monitor trends like recurrent problems, alert volume, and response times. The team would be more confident in the incident suggestions if they had better insight into the reasons behind the correlations between certain incidents. Review collected by and hosted on G2.com.

They have a very nice and slick UI interface, modern and clean UI which really helps me to look through the incidents, alerts, and monitored data. The layout of info has impressed me because it is so easy to navigate to find the necessary details of incidents, alerts, etc. Their performance is quite good for us and even though we were getting a high number of alerts, BigPanda always was performing well without any lag. Review collected by and hosted on G2.com.

I think my main concern is the cost as you scale in terms of users and number of alerts. It can get pricey very quickly with all of your alerts, and systems being watched. The integration experience is good across the board, but some of the integrations require a lot of setup and tinkering to work the way you intended. Making these integrations easier to set up for basic functionality could enhance my experience. Review collected by and hosted on G2.com.

What I like most about BigPanda is its ability to correlate alerts from multiple monitoring tools and turn a large volume of noisy alerts into meaningful incidents. The centralized visibility, alert enrichment, and AI-powered correlation make it easier to identify the probable root cause and prioritize critical issues, which helps the operations team respond faster Review collected by and hosted on G2.com.

The main area for improvement is the documentation and learning curve. Some features can take time to understand, and the product could provide clearer guidance for configuration and advanced use cases. Some integrations may also require additional customization Review collected by and hosted on G2.com.

What I like best about BigPanda is its focus on simplifying complex IT operations. I like how it uses automation and AI to help teams identify problems quickly and work more efficiently. The platform also brings different data together in one place, which makes it easier to understand issues and take the right action. Review collected by and hosted on G2.com.

One thing I dislike about BigPanda is that it can take some time to understand and get comfortable with all its features. For new users, the platform may feel a little complex at first, maybe they can't able to understand especially when dealing with a lot of information and settings. Review collected by and hosted on G2.com.

Personally I find it helpful when you are having a day where alerts are being flooded in. Before BigPanda we had multiple monitoring products we were jumping around in and sometimes 10-15 alerts could pop up from one network problem. This corrals those alerts and shows you the full picture. Typically I use it when we are having some sort of connectivity problem, device down type alerts, or any type of infrastructure incident that makes multiple boxes start complaining. It helps eliminate a lot of unnecessary clicking. Review collected by and hosted on G2.com.

It was a little hard for me to fully trust the correlation at first. I found myself still going into the originating monitoring product to verify that nothing was being missed. Review collected by and hosted on G2.com.

I really like BigPanda's correlation engine; it's genuinely good at grouping related alerts into one incident instead of leaving us to piece it together manually. I appreciate the integrations as it plugs into pretty much everything we already use like Splunk, ServiceNow, and New Relic, so we didn't have to rip and replace our stack. The automation and runbooks are a huge plus; routine responses trigger automatically, saving us time and allowing engineers to focus on novel problems. The dashboards provide a clear overview of what's happening without needing to dig through raw logs, which is especially handy when something's actively breaking. Overall, the noise reduction feature has saved us the most time day to day. Review collected by and hosted on G2.com.

I found the initial setup and tuning takes work; getting the correlation rules dialed in to match our environment required real time and trial and error. It's not plug-and-play out of the box. There's a learning curve for new users; some of the more advanced features, like custom automation and deeper correlation logic, aren't intuitive at first, making onboarding longer than I'd like. Pricing is not cheap, especially as you scale up the number of integrations and data volume. I also think reporting could be more flexible; the built-in dashboards are good for a quick view, but pulling custom reports for leadership means exporting data and working with it elsewhere. None of these are dealbreakers, but they're the things I'd want to see improved. Review collected by and hosted on G2.com.