Release notes for October 2025
Grepr released these feature updates, improvements, and bug fixes on October 28, 2025.
New features and improvements
Support for paging through large exception lists in the Grepr UI
An update to the pipelines UI allows you to page through exceptions that are part of the configuration for an integration. This change improves the usability of the exception management interface when an integration has a large number of exceptions configured. To learn more about integration exceptions, see Selective reduction with exceptions.
The SQL transform now includes a percentiles UDF
The SQL transform in Grepr pipelines now includes a percentiles user-defined function (UDF). This UDF enables you to calculate multiple percentiles for a specified numeric expression, allowing for more advanced statistical analysis and insights in your pipelines. See Percentile functions.
Improved handling of complex JSON with the JSON parser
An updated JSON parser in Grepr pipelines improves handling of complex JSON structures, including nested objects and arrays. This enhancement enables more accurate parsing and extraction of fields from JSON log messages, allowing for improved log enrichment and analysis.
Better comparison of job versions with an upgraded diff viewer
The job version comparison interface has been upgraded to use the Monaco Editor diff viewer, replacing the previous basic diff visualization libraries. The new diff viewer offers improved performance, advanced diff algorithms, and enhanced readability, featuring collapsible unchanged regions and improved syntax highlighting for JSON comparisons.
Enhancements to simplify the configuration of JSON parsing
An update to the JSON parser form in the Grepr pipelines UI simplifies setup by adding configuration for processing nested JSON message paths.
Improved performance for data lake tables with data skew
This release includes a reimplementation of the data partitioning framework for tables in the Grepr data lake. This change improves performance by enabling higher throughput when a table’s data is distributed unevenly across partitions.
Support for additional timestamp formats when you configure pipelines
Grepr pipelines now support converting the following timestamp formats to the top-level log event field, eventTimestamp. This support is available in any pipeline step that requires parsing timestamps, such as the Grok parser or attribute remapper:
- Common Log Format with comma-separated milliseconds. For example,
2025-10-17 20:10:59,166. - The Apache and NGINX Common Log Format. For example,
14/Oct/2025:15:19:04 +0000.
Bug fixes
Fix for errors during pipeline processing with late-arriving messages
This release fixes a bug that could cause errors when handling late-arriving messages during pipeline processing.
Fix for incorrect handling of OTLP integration updates
Fixed a bug in the OTLP integration form where updating an existing integration would incorrectly use the integration ID instead of the name.
Fix for incorrect handling of logical operators in the Data Explorer
This release fixes a bug in Data Explorer queries that caused the OR and | operators to be replaced with AND.
Fix for non-editable filter queries
This release fixes a bug that prevents editing the filter query that’s configured on a pipeline sink.
Fix for incorrect handling of non-alphanumeric characters in Grok patterns
This release fixes a bug in the Grok parser that prevented proper handling of pattern names containing non-alphanumeric characters such as hyphens, underscores, or special symbols. This change maintains backward compatibility while resolving parsing failures that could occur with some grok pattern configurations.
The Data Explorer UI now correctly displays attributes and tags for New Relic queries
This release fixes a bug preventing the Data Explorer suggestions panel from correctly displaying attributes and tags associated with New Relic queries.
Fix to show Limit exceeded errors in the Data Explorer UI
This release fixes a bug that prevented “Limit exceeded” errors from being displayed in the Data Explorer UI when a query exceeds resource limits. Now, when such errors occur, users will see a clear error message indicating that the query has exceeded the allowed limits.