11.34.24 Platform Release

Released August 25, 2026

info

Upgrading to this release includes a one-time data migration and requires an extended maintenance window (approximately 8–10 hours). Upgrades should be scheduled accordingly.

New features and enhancements

This release introduces a new storage engine for the graph database backend, a significant rework that improves read, write, and query performance while reducing the platform's memory and resource footprint, particularly in large environments. It is complemented by a broad set of performance improvements across consolidation, compute, graph traversal, and Data Warehouse snapshots.

Addressed issues

• Platform stability: Lifecycle status calculations now complete reliably instead of stalling.

• Platform stability: Large aggregate queries now hold up better under heavy load, with improved memory management preventing silent failures and stalled recovery.

• Data consolidation: Vulnerability ticket consolidation now handles linked finding history more reliably in large environments, without timing out.

• Data consolidation: Improved data consolidation reliability by ensuring consolidation flows report failures instead of silently continuing when reference data fails to load completely, preventing data loss under high load.

• Remediation requests: Improved reliability of ad hoc remediation requests by ensuring the record identifier stays stable after creation, preventing duplicate or inconsistent remediation records.

• Data Warehouse: Improved Data Warehouse snapshot performance by significantly increasing the speed of relationship data extraction for large environments.

• Query performance: Improved graph traversal performance by optimizing how relationships are matched by type during query processing.

• Query performance: Improved query performance for high-volume data by adjusting indexes to support common filtering criteria.

• Query performance: Improved query performance by pushing relationship-degree calculations down to the storage layer for applicable queries.

• Query performance: Improved performance of classification rollup calculations by ensuring an efficient index path is used during large-scale compute jobs.

• Vulnerability computation: Improved vulnerability computation performance by reducing CPU overhead in condition evaluation for large environments.

• Platform resilience: Improved platform resilience by preventing event-log writes from blocking flow execution during storage write-stall conditions.

Known issues

• Query results can differ significantly depending on which internal execution path serves the request, for certain complex queries combining relationship traversals and multiple filter conditions.

• Certain automation flows that consolidate a small number of records can take an unusually long time to complete, because a large reference lookup runs unconditionally regardless of how many records actually need it.