MC can now surface Hex projects in lineage to help users evaluate impact of data issues on Hex projects.
We’ve improved our automated freshness monitor to better handle weekly patterns. We've sometimes heard customers refer to these as “bimodal” thresholds… meaning one threshold during weekdays, and a different threshold during weekends. These are valuable when the table updates during the week, but not (or less frequently) on the weekend.
Specific changes:
- We more accurately recognize weekends. We previously had hardcoded support for Sat/Sun weekends. Now, we dynamically recognize weekends regardless of where they fall in the week (e.g. Fri/Sat, or when there’s just a single day “off”)
- Tighter thresholds in the “active” period of the week. About 5% of tables that we’re tracking have had their thresholds reduced by >25% from this change!
- Thoughtful thresholds in the “off” part of the week. So if the table doesn’t start back up on Monday, we’ll alert.
In the future, we’ll extend these improvements to “Time since last row count change”, and also add bimodality for day/night behaviors.
Cozy up with some hot chocolate, because the banner in Monte Carlo is now filled with holiday cheer.
MC now supports Databricks oAuth M2M authentication with setup available via the CLI and UI.
Follow docs here to authenticate your MC Service Principal via M2M.
Next week, the UI of the login page will be refreshed. All functionality, links, and workflows from the login page remain the same. The changes are cosmetic only.
New login page
We are about to remove the two widgets at the top of the monitors page as the information they present appears in other dashboards in the product. This is the first step in our overhaul of the monitor list to improve usability and simplify monitor management workflows.
MC can now manage failures from Databricks Workflows. This helps users triage and resolves all data and system issues in one single platform. Follow docs here to set up the webhook connection to start alerting.
Azure Data Factory pipeline failures can now be managed via MC. This helps users centrally detect, triage and resolve Data Factory pipeline issues along with all other data incidents within MC. Follow docs here to start using.
MC-GitLab integration is now available. Users can leverage the integration to investigate code impact on tables. More details here https://docs.getmontecarlo.com/docs/gitlab
On the Assets page, users interact with our out-of-the-box monitors for Freshness and Volume. It's also where they can configure an explicit threshold, if they prefer that instead of the machine learning.
If a user adjusts sensitivity or switches to an explicit threshold, those changes are now captured in a "Change log" that they can easily view. This makes it easy to see who adjusted the settings, when, and how. This has been a well adopted feature in custom monitors, so we are glad to extend it here as well.
