Classic dashboards use precomputed metrics and static management zone filters. Latest Dynatrace dashboards are query-based, enabling precise analysis across metrics, logs, and traces with DQL. The built-in dashboard converter automates the migration of standard tiles, but some tile types and filters require manual work. These best practices help you prioritize, convert, and validate dashboards efficiently.
Enterprise environments often have hundreds of classic dashboards. Most are unused duplicates or experimental versions that were never cleaned up. Upgrading every dashboard wastes effort; focus on the ones teams actually rely on.
To prioritize correctly
Getting agreement on the prioritized list from all relevant team leads before conversion begins prevents requests to migrate low-priority dashboards mid-project.
The built-in dashboard converter automatically migrates supported tile types to their Latest Dynatrace equivalents. Run the converter on each prioritized dashboard rather than rebuilding from scratch.
When running the converter:
The classic original is not modified or overwritten during conversion. Teams can continue using the classic version until the Latest Dynatrace version is validated and approved.
Not all tile types convert automatically. The following categories require manual recreation:
SLO tiles: not auto-converted. Rebuild them by linking to the upgraded SLO definitions created in the Upgrade Configurations and Settings stage.
Problems tiles: rebuild using DQL against the dt.davis.problems table. For example:
fetch dt.davis.problems| filter dt.davis.is_duplicate == false| fields display_id, event.status| summarize {Open = countIf(event.status != "CLOSED"), Closed = countIf(event.status == "CLOSED")}, by:{display_id}
USQL tiles: rewrite as DQL-based query tiles. USQL and DQL syntax differ; review each query individually.
Custom chart tiles: rebuild using the Latest Dynatrace DQL-based visualization options.
Markdown tiles: replace with Latest Dynatrace text tiles or callout components.
Document each manually rebuilt tile against the original so reviewers can validate the output.
Classic dashboards often use management zone filters as global scoping controls. These filters are not converted automatically. Replace them with Latest Dynatrace dashboard variables scoped to the equivalent segment.
After conversion, configure a dashboard variable that references the appropriate segment, for example, the segment created during the IAM and Segments upgrade stage that covers the same scope as the original management zone. Assign the variable to the dashboard and update tile queries to reference it.
Management zone filter migration is one of the most common sources of post-conversion issues. Teams that validate a converted dashboard without noticing the filter is missing may report data discrepancies. Always check filter migration as part of your conversion review.
Each team must review and approve their upgraded dashboards before you decommission the classic versions. Without a deadline, the validation phase extends indefinitely as teams deprioritize the review.
Set a specific date for each team to complete their review and communicate it before starting conversion. For dashboards not validated by the deadline, escalate to the project sponsor before making decommission decisions.
Once a team confirms their upgraded dashboard meets operational needs, archive or hide the classic version; do not delete it immediately. Keep it accessible for a short period in case the team identifies issues after the classic version is no longer the default.
Return to Upgrade classic dashboards to continue your upgrade.