We're thrilled to announce that Sifflet now integrates natively with ServiceNow! This integration brings Sifflet's data observability capabilities directly into your existing ServiceNow incident management workflow, ensuring that data quality issues are never missed.

The new integration empowers you with:

• Centralized Data Quality Incident Management: Integrate Sifflet with ServiceNow to ensure all data quality incidents detected by Sifflet are tracked and managed within your existing ServiceNow environment.
• Automated Incident Creation: Sifflet can now automatically create a ServiceNow incident whenever a monitor failure triggers a Sifflet incident. This eliminates manual steps and ensures rapid response to data quality problems.
• Customizable Incident Templates: Create custom ServiceNow incident templates within Sifflet and assign different templates to different Sifflet monitors. This allows you to tailor the information included in each ServiceNow incident, providing the right context for efficient resolution.
• Direct links from Sifflet to ServiceNow: Access your Sifflet-created ServiceNow incidents from Sifflet's UI.

Ready to connect Sifflet to ServiceNow? Check out our detailed documentation available here.

App version: v458

You can now set a custom email subject when creating or editing monitors, instead of using the default Sifflet subject. This gives you more control over your email notifications, making it easier to prioritize and process alerts.

App version: v455

We've added a "dbt Runs" tab to all Sifflet assets generated from your dbt models (e.g., tables, views). This tab provides a centralized view of your dbt model execution history, allowing you to:

• Quickly see the status and duration of each run.
• Access the complete run history for the asset's dbt model.
• View useful metadata like every run's start and end time and its logs.

The tab will also be used to provide insights into the resource usage and efficiency of dbt runs. Additional information, such as estimated run costs, will be available soon!

App version: v453

When a new user is created in Sifflet, they will now receive an email with login instructions. The email guides them through setting a password or using SSO, based on the enabled login methods.

App version: v452

Two new APIs have been added:

• Decrypt Monitor Groups - Retrieve a dictionary for a specified Monitor of the hashed values alongside their decrypted values for a Monitor
• Decrypt Monitor Run Groups - Retrieve a dictionary for a specified Monitor Run of the hashed values alongside their decrypted Values

{
  "decryptedValues": {
    "7rhxMMfI/00nEPCeU4JF1yh6DG5HrDYpv6Ruq4npF/s=": [
      "Los Angeles"
    ],
    "RAEabd4cIdK7i6arZWQKoweEDcCUAFvkroRld/hyQzU=": [
      "New Orleans"
    ],
    "ZNMTMMDB9mVQeOOE4fQL3SBF1Q/U78hvgywLuASeZGI=": [
      "Philadelphia"
    ],
    "0ujO9ut/7CYQZWLVzYGUigbccqABrL0el0+GJv5xRTQ=": [
      "Brooklyn"
    ],
    "7kC4JpawlbYAk3gVWN9JOO+toV/lOnRgc0a2YWPD1wU=": [
      "San Francisco"
    ],
    "nXVWkm7SsR9kv4y8JL4zkY1Fo/KTlm42VE//lrdrt0A=": [
      "Chicago"
    ]
  }
}

Why is this useful? As these decrypted values reflect column values in the source database they are not stored or exposed everywhere in sifflet for compliance reasons, specifically not in the data sharing. These APIs allow you to map the hashed values in your data share with their true values.

Previously in Sifflet Offsets could be a bit confusing. No offset for an hourly monitor would monitor the last complete hour, and No Offset for a daily monitor would monitor the current day.

We're standardising these options for all monitor granularities

Now:

• Default Offset: 1 - A default offset of 1 will query the last complete timeslot
• Zero Offsets: Setting offsets to 0 will query the current timeslot , the current day, the current hour. This is good when your days data should be complete by a certain time or if you want to compare a value at a specific time of day!

There is no action to change anything on your side!

Data Quality as Code

While your previous configs will still work we're introducing a new parameter to streamline this. Offsets previously needed you to specify a granularity, leading to potential confusion. This new offsetPeriodsparameter will automatically account for your time period granularity.

  timeWindow:
    field: auto
    firstRun: P365D
    offsetPeriods: 2

We suggest using this version moving forward !

When a monitor is failing and a resolution is planned but will take time, you really don't want to keep receiving alerts telling you something is wrong !

We've introduced a new Muting capability to stop alerts. Simply find the little bell Icon in the monitor action bar to mute monitors !

What's next? Dynamic muting options such as "mute until passing"

Previously, when forgetting your password, you had to reach out to a user with an admin system role to have them reset your password so you could access your account again.

We're introducing a streamlined and secure "Forgot password?" workflow to make account recovery faster and easier. You can now reset your password in just a few clicks directly from the login page, with email-based verification ensuring a safe and user-friendly process.

Note: The "Reset password" workflow remains available, as it can be handy for self-hosted Sifflet deployments that don't include a SMTP server.

Read more about the "Forgot password?" workflow

App version: v446

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