Logbook releases

Enhancements

• Logbook now shows logs that are secondarily associated with a Work item, Strategy, Workspace, or Board — not just the logs created directly for it. All secondary associations display by default, and you can filter by association type to narrow the view. Each secondarily associated log and its source entity is hyperlinked, so you can navigate directly to it based on your permissions.
  

• Sorting on custom attributes, which was temporarily unavailable during recent performance improvements, has been restored.

Enhancements

Total Log Counts by Log Type in Planview Portfolios - New attributes representing total log counts by log type are now available for column sets, such as Risks, total log count or Issues, total log count. Previously, users could see a total log count on a project but had no way to tell what was behind that number. A high log count could mean a backlog of unresolved risks, open issues, or pending decisions — and there was no way to tell at a glance. With this release, per-log-type count attributes let users instantly see the breakdown, so users can prioritize the right projects for the right reasons.

A new Sync Log Types from Logbook option has been added to the Manage Attributes screen, letting administrators manually sync log types.

Enhancements

• Log entries can be filtered by custom attributes and assignees.
• Anvi-powered insights are now available for Logbook data. Ask Anvi natural-language questions about the risks, issues, changes, decisions, and assumptions logged against your work — for example, "Give me a summary of all risks and issues in this project" or "What risks should I worry about in the next 7 days?" This capability is generally available in Planview Portfolios and Planview AgilePlace, and available as a Labs feature in Planview ProjectPlace. Contact Planview Support to enable the Labs feature.

Enhancement

• Pagination was implemented, which provides an 8.8x improvement in load times. This performance gain enables Logbook to handle significantly larger datasets without negatively affecting user experience.