Operations (i.e. API queries and mutations) can now be directly shared and loaded from the API explorer!

Learn more in our docs.

Coming soon in November: we are announcing Monte Carlo's foray into data observability for SAP Hana, starting with the ability to run SQL Rules and detect Volume anomalies. SQL Rules can be created in either the UI and/or programmatically via Monitors-as-Code (API/SDK too). These monitors can be used to generate notifications to relevant stakeholders, circuit break pipelines, and conduct RCA (e.g. sampling). Asset entries are also created in Monte Carlo and Custom Lineage APIs are available to write lineage across databases to data warehouses.

Previously, this was only supported for different kinds of custom rules, but is now available for any custom monitor type. If the severity is set on a custom monitor, then all incidents generated by that monitor will inherit that severity.

Users can now send Monte Carlo notifications directly to Jira to create Jira Issues. Previously, a user could only create a Jira Issue by clicking a button from IncidentIQ. However, for Incidents from certain critical tables or critical monitors, some customers wanted to send those Incidents straight to Jira without having a human-in-the-loop. With this recent improvement, it’s now easy for them to do that.

Note: this improvement is only available in Notifications 2.0. Learn more in our docs.

Monte Carlo now integrates with Webex, which offers a collaboration tool similar to Slack and Microsoft Teams. This integration allows sending of notifications directly to channels within Webex, to keep data teams and stakeholders up to date on any recent data issues.

Check out the docs to learn how to set this integration up.

Comparison Rules now support segmentation. Full details in the docs. Previously, users could do comparisons like:

• Count of rows: to compare counts, like the count of yesterday's orders
• Single value: to compare metrics, like the sum of revenue from yesterday's orders

Now, you can also do:

• Segmented values: to compare segmented metrics, like the sum of revenue by product from yesterday's orders (limited to 100 segments)

Today we are announcing Monte Carlo's foray into data observability for Azure Synapse, starting with the ability to run SQL Rules and detect Volume anomalies. SQL Rules can be created in either the UI and/or programmatically via Monitors-as-Code (API/SDK too). These monitors can be used to generate notifications to relevant stakeholders, circuit break pipelines, and conduct RCA (e.g. sampling). Asset entries are also created in Monte Carlo and Custom Lineage APIs are available to write lineage across databases to data warehouses.

Today, Azure Synapse Dedicated SQL Pools (formerly SQL DW) are supported, but we are looking to expand support. If you require additional Azure support, please fill out the form here.

Users can now raise a warning or deprecation in Alation from within MC. This allows users to much create more visibility in Alation for major data issues, without ever needing to leave MC. See more details in our MC<>Alation documentation.

Users can now create rules that run 2 separate queries pointed at different databases (or the same database), and compare the results. The most common use case for this is to ensure that the sync of data from a source database to a different target database has been successful (e.g. SQL Server to Snowflake).

Create these by selecting Comparison Rules in the monitor menu, or click here.

More detail available in our docs.

With GetAccountAuditLog via the API, you can now retrieve granular user activity logs from your MC environment. This feature is designed specifically to address requirements from Security & IT teams that want the ability to extract and retain these logs for SEIM (Security Event & incident Management) purposes.