Deployment risk

Risk alerts bring everything together by flagging conditions that indicate elevated deployment risk. These alerts help you move from passive observation to action, notifying when multiple risk factors align and it may be time to pause or reassess further changes.

For this tile, we're going to do things a little out of sequence, as we'll combine signals from our previous tiles into a composite risk score. Each KPI contributes a small risk weight, and when multiple signals degrade together, the dashboard escalates from 0-100.

As we're relying on signals from our other tiles, before configuring this tile, make sure that you've built the following tiles and published them as a KPI:

• Change failure rate
• Deployment success rate
• Unresolved critical issues

Configuring the tile

Configure the following in the tile editor:

1. SQL Analytics: Enable the toggle.
2. dataset1:
   1. Data Source: Select RollUp.
   2. Data Stream: Select KPI.
   3. Parameters > KPIs: Select the KPIs you published for your tiles.
3. SQL > Query: Enter a query to heuristically combine your existing KPI values into a single deployment risk assessment.
   
   This example extracts the current deployment success rate, change failure rate, and unresolved critical issue count, normalizes each onto a common 0-1 risk scale, before finally combining them into a weighted 0-100 risk index.
   
   Copy

   WITH kpi_values AS (
     SELECT
       MAX(CASE 
             WHEN LOWER("Name") LIKE '%deployment success rate%' 
             THEN "value" 
           END) AS deploy_success_pct,
   
       MAX(CASE 
             WHEN LOWER("Name") LIKE '%change failure rate%' 
             THEN "value" 
           END) AS change_failure_pct,
   
       MAX(CASE 
             WHEN LOWER("Name") LIKE '%unresolved critical%' 
             THEN "value" 
           END) AS unresolved_critical_count
   
     FROM dataset1
   )
   
   SELECT
     ROUND(100 * (
       0.40 * LEAST(GREATEST((95 - deploy_success_pct) / 15, 0), 1) +
       0.35 * LEAST(GREATEST((change_failure_pct - 5) / 25, 0), 1) +
       0.25 * LEAST(GREATEST(unresolved_critical_count / 10, 0), 1)
     ), 0) AS risk_index
   FROM kpi_values;

4. Columns: Ensure Risk Index has a Type of Number and has Decimal Places set to 0.

Adding a monitor

By applying thresholds to the Risk Index, you define what “safe to deploy,” “proceed with caution,” and “pause and reassess” mean in your own environment.

This transforms the tile from a passive score into an operational control, giving you a clear signal when additional investigation or rollback planning may be required before pushing further changes.

Configure the following in the tile editor:

1. Monitoring: Enable the Monitoring toggle.
2. Type: Select Threshold.
3. Value: Select Top.
4. Column: Select Risk Index.
5. Conditions:
   1. Error: Enable the toggle, then configure as Greater than, and supply an appropriate value. For example, 65. This represents a high-risk state where teams should pause further releases and reassess.
   2. Warning: Enable the toggle, then configure as Greater than, and supply an appropriate value. For example 35. This signals elevated risk. Deployments may still proceed, but with increased scrutiny.
6. Click Save.

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