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Show Configuration Changes in Anomaly Reports

See this idea on ideas.ibm.com

Add a feature to track changes in system configurations and show them in anomaly reports. 
This can work by pulling data about configuration changes (like from billing systems or logs) and marking the dates of those changes in the reports. 
This way, users can easily see if anomalies happened because of changes or something unexpected.
 It also helps track if the system is set up the way it’s supposed to be and lets users understand why changes were made.

Idea priority High
  • ADMIN RESPONSE
    Jan 24, 2025

    Can you explain this in more details ? Might need a more detailed description of the use case.

  • Guest
    Reply
    |
    Jan 30, 2025

    Customer want to add a feature in Cloudability that will track changes in system configurations (such as billing system updates, infrastructure changes, or settings modifications) and display them in anomaly reports.

    This means that when Cloudability detects a cost or usage anomaly, users will be able to see if any recent system changes happened around the same time, helping them quickly figure out if the change caused the anomaly or if something unexpected happened.ˀ̉
    Currently, when there’s a sudden cost spike or an unexpected drop in usage, teams have to manually investigate:
    Were any settings changed? Was there a new policy or pricing update? Did someone adjust a cloud configuration that led to this anomaly?

    With this feature, Cloudability will automatically pull data about system changes and highlight them in the anomaly report, so teams can quickly identify the cause of the issue without guessing.

    Example:
    A system admin updates a cloud billing setting on Jan 29 to switch from on-demand to reserved instances.

    Cloudability detects a cost spike on Jan 31 in a specific service.

    The anomaly report now includes a marker showing:

    • What system change happened (e.g., "Billing Setting Changed: Reserved Instances Enabled")
    • The exact date and time of the change
    • Who made the change
    • The user sees the correlation and quickly understands that the cost spike was expected due to the system update.