Slack integration was improved to support automatic messages updates. Whenever a monitor returns to an OK state, the original Slack alert message now updates in real-time to reflect the resolution, keeping everything clear and up to date.

This enhancement ensures your team instantly sees when issues are resolved, reduces channel clutter, and keeps everyone aligned without extra effort. Stay focused and responsive with more efficient incident communication in Slack!

Read more about Slack integration

App version: v443

Data lineage is a crucial tool for understanding how data flows through your systems. However, large and intricate pipelines can quickly become overwhelming. With the new lineage node retraction feature, you can hide specific nodes from your data lineage view. This makes it easy to:

• Focus on What Matters: Hide less critical nodes to simplify your view.
• Speed Up Troubleshooting: Quickly identify root causes and dependencies without visual noise.

This enhancement gives you the flexibility to declutter complex lineage graphs by collapsing nodes that are not immediately relevant to your analysis, enabling clear navigation of your data ecosystems.

Read more about lineage

App version: v435

Webhooks were enriched to send a new type of events. Sifflet webhooks now send real-time notifications for:

✅ Monitor Success Runs: Get notified when a monitor runs successfully, providing confidence that your data quality test went smoothly and that the latest verified data is reliable

❌ Monitor Failing Runs (Existing): Continue receiving events when a monitor detects an issue, ensuring you never miss a potential problem.

These new events allow you to push more comprehensive Sifflet monitor insights to your notification, ticketing, or data catalog tools as well as build even more sophisticated programmatic workflows.

Read more about the webhook integration

App version: v434

Long overdue, but Sifflet Insights browser extension now clearly lets you know when it's unable to connect to Sifflet, making the onboarding flow much smoother.

Read more about Sifflet Insights browser extension

App version: v433

The Filter conditions method now supports the OR operator between conditions when creating a domain. This enhances flexibility by allowing you to define domains containing assets that either come from specific sources or are tagged with a specific tag or label.

Read more about domains

App version: v433

There are two scenarios for monitors going from Failing to Passing

• Monitors that scan the entire table: When the last run of the monitor succeeds the monitor will change status to Passing because the entire table has been scanned and the anomaly is not present anymore.
  i.e. A monitor detected 50% null values on a column, and the next run detects 0% null values, the problem has been fixed.
• Incremental Monitors: Incremental monitors require human interaction to go from failing to passing, by qualifying all the anomalies. Why is the behaviour different? because a successful run on an incremental monitor does not mean the issue has been resolved. For example if there were null values in yesterday's data, but there are none in today's data, there is nothing that suggests yesterday's data has been fixed.

We recently introduced Dynamic Monitor Statuses , allowing monitors to change their status based on qualifications made by the user.

A new flow will now ensure that qualifying a monitor to make it passing will now close the incident associated automatically.

When qualifying a monitor as passing, either via manually qualifying points or by using the global monitor Qualify as passing option, this will now propagate to the incident.

Note: An incident with multiple monitors will only close automatically if all the monitors are passing!

📘

Coming Soon

Closing an incident will currently not propagate to monitors, this is coming soon !

A brand-new centralized Settings section got introduced, bringing together all previously scattered settings pages into one intuitive location. This new section smoothes navigation within the application and makes it easier for your teams to find and manage all settings.

Note: Access and permissions of individual pages remain unchanged.

Read more about the Settings section

App version: v428

Automatically Monitoring Tables is being simplified. The new Automatic Monitoring configuration will ensure you can cover entire schemas or databases with default monitoring!

The Following monitors can be applied automatically:

Freshness (Metadata): Dynamically alerts if the time since the last update

Volume (Full Table Scan): Dynamically Alerts if the total number of rows in the table diverges from its usual norm.

Schema Change: Alerts if the schema changes, such as a column dropping from a table.

All these monitors will only be created on Tables and will query metadata so they should all be pretty much Free to run on your warehouse !

To access this feature navigate to our new Settings Menu and to the Automatic Monitoring section

Note: New tables added to the activated schemas will automatically be monitored when detected by Sifflet.

Created Monitors can easily be filtered on via the Creation Method Filter of the Monitors page:

This feature is in Beta:

• Currently limited to 1000 monitored datasets
• Will allow selection of dataset types other than Tables in the future, such as Views ( impacting the query cost on the warehouse )
• Subject to monitor availability on the technology: i.e. Metadata Freshness only available on select Technologies.

Ensuring Sifflet sources successfully run is critical to ensure your metadata is always up-to-date. You can now get alerted on failing source runs, making it easy to promptly react in case Sifflet is no longer able to pull metadata from your data stack because of an authorization issue, a connectivity problem or anything else.

Read more about the Notify on source failure setting

App version: v424