I like the ease of use of Monte Carlo, especially how setting up monitoring is very simple. The integration with external tools like Slack and Jira is top-notch, sometimes eliminating the need to go to the Monte Carlo website to interact with an alert for its entire lifecycle. The user interface is generally very user-friendly, with only a few minor exceptions. I also love the quick pace at which the Monte Carlo team responds to issues, bugs, feature requests, and improvement suggestions. Review collected by and hosted on G2.com.

The biggest pain point for me is the lack of possibility to merge alerts from metric monitors into one incident. We often have an issue that triggers many alerts, and we have to manage each alert separately, even though all have the same root cause. Since metric monitors are the backbone of Monte Carlo, it's really frustrating. This has been the case for a year and a half now. Another issue is the too fast and too big changes; I expected more stability at this stage. It's really difficult to keep up with paradigm shifts. For example, the change for Table monitors caused confusion. I recently ingested a big data set only to learn that tables are now monitored by default upon ingestion, which was contrary to previous behavior where you had to set up monitoring manually. Review collected by and hosted on G2.com.

I really like how straightforward it is to use. I also like the table where it includes everything, from the old and new primary locations which has really been helpful plus the direct link to the tour, also that we get reports on time. Review collected by and hosted on G2.com.

For example, in the menu where you can see the progression of the work (like fixed and in progress etc), I feel like there are too many options, which makes it confusing. Also, regarding the graphs, I think it would be easier if we just kept the table. Review collected by and hosted on G2.com.

I like how easy it is to use without feeling cluttered, and how it highlights the best visualizations. I like how easily it connects to MCP servers and my AI Agent can access it. I like its performance. I was able to onboard to it quite easily. Review collected by and hosted on G2.com.

I don’t dislike anything about it, but there’s still room for improvement, and I think optimizations could be made across the board. Review collected by and hosted on G2.com.

I like the support we get from the team. The functionality is easy to navigate & the agents provide excellent insight & visibility. Review collected by and hosted on G2.com.

I feel the alerts can be too noisy on occasions, but the triage alert & monitor recommendations do reduce this. The tool still does "double count" on occasions which can be hard to react to. Review collected by and hosted on G2.com.

It just works, point at the database and it learns about your data. It will then surface any anomalies. We've been using for >4 years now and it's saved us and our customers numerous incidents Review collected by and hosted on G2.com.

Nothing to dislike in general but when observing data, latency can be an issue. There generally has to be a passage of time for an issue to become apparent. Review collected by and hosted on G2.com.

I’ve created many monitors for different use cases. It’s very easy to set them up, and they’re very useful for detecting issues. Monte Carlo is a user-friendly tool. Review collected by and hosted on G2.com.

Monte Carlo is improving and updating the UI, which is good to see. However, sometimes it feels like certain features get changed even when it isn’t really necessary. Review collected by and hosted on G2.com.

The web UI is good to look at and in the beginning wasn't very confusing to navigate. Review collected by and hosted on G2.com.

They constantly make changes to their backend that are not useful and impact the monitors and assets that were carefully setup from the onboarding process. Their out of the box volume and freshness monitors are practically useless for many reasons. That leaves you with custom SQL and metric monitors (which are really just a SQL type wrapper and more confusing than just making specific changes to existing SQL). I'm left with a question. Why? Why would a smart organization waste this much money on something that could be achieved with simple chron jobs and scripts? Review collected by and hosted on G2.com.

its very user friendly and easy to setup monitors, i also love you can use ml to predict data patterns without having to come up with your own thresholds Review collected by and hosted on G2.com.

some of the options are limited when it comes to monitoring and editing, i dont like when im comparing two tables i need to create a new monitor if i wanna switch the table or that if my grouping results in too many options i cant monitor anymore. some of the editing and duplicating options could be more intuitive for small changes Review collected by and hosted on G2.com.

I like that Monte Carlo’s automated anomaly detection and alert triage, with its native AI agent, helps me review and respond to many critical events. Setup was very seamless—just an API-level integration of the data pipeline. I find it really good and helpful for anomaly detection and monitoring. Review collected by and hosted on G2.com.

I’d like to see better alert grouping and built-in redaction of PII in alerts. Monte Carlo works with raw data pipelines that sometimes contain PII, and I don’t want it exposed to analysts and users working in the tool or viewing alerts. Review collected by and hosted on G2.com.

Alerts are pretty smart. I love that slack messages show up right along with each alert too Review collected by and hosted on G2.com.

I think sometimes the alerts could be understood by an AI as an ongoing issue so everyone knows any repeated alerts belong to the same category of issues Review collected by and hosted on G2.com.