You can now manually trigger metric monitors either from the UI (via the Run button) or through the API. This gives teams flexibility to run monitors exactly when their data pipelines finish loading, avoiding wasted compute from partial runs and ensuring results reflect the latest data.
You can now schedule monitors to run immediately after your ETL jobs complete, reducing time-to-detection (TTD) from hours to minutes. Whether you use Airflow, dbt, or other supported orchestration tools, Monte Carlo can trigger monitors as soon as a job finishes successfully.
Snowflake users may now raise monitor query timeouts up to 1 hour directly from the UI.
Support for BigQuery, Redshift, and Databricks is in progress.
Note: raising the timeout increases usage of your Snowflake warehouse. Use longer timeouts only when needed to avoid unnecessary spend.
Comparison monitor is now available for Salesforce CRM. This allows users to ensure integrity of data flowing from CRM to warehouse. Docs.
You can now connect Monte Carlo to Datadog Incident Management. Create or link incidents directly from alerts, sync status and ownership automatically, and add Datadog as a notification channel.
We've released much better support for "Chargebacks", a common need in enterprises who wish to attribute consumption & cost back to the appropriate lines of business. Detailed documentation is available here.
Specifically, we have shipped a new Consumption data export which details consumption by monitor for the last 30 days. This can be easily joined to the Monitors data export using monitor_id, which allows enterprises to trace credit consumption back to particular creators, domains, audiences, etc. Different enterprises have different processes for how they manage and trace chargebacks, so this flexibility is important.
This is only available for customers that meet BOTH of the following conditions:
When receiving an alert from Monte Carlo, the troubleshooting agent can automatically work through 100s of hypothesis and highlight the ones that are most likely to have caused the issue. It will consider changes in the data, system issues (e.g. Airflow or dbt failures) apd code changes when analyzing an alert, and will automatically traverse lineage to identify the root cause.
Learn more in the Troubleshooting agent documentation.
When a user tries to open an alert they don’t have permission to view, Monte Carlo now provides a clear path forward with an Access Request option. Here’s how it works:
We hope to streamline the process of getting unblocked, both by giving users a clear way to request access and by reducing the back-and-forth in organizations where it isn’t obvious who to contact. At the same time, access decisions remain fully in the hands of admins, ensuring the right level of control.
Advanced Monitors now fully support SAP HANA, enabling users to leverage Data Profiler and Monitoring Agent recommendations, as well as deploy metric, validation, and comparison monitors on their SAP HANA assets.
MC shipped a series of improvements to the domains creation experience -
