Query improvements and trace enhancements

We were busy refining the core query experience last week, making it faster and more intuitive to explore your data. These updates focus on streamlining workflows that you use every day, from field selection to trace correlation.

Enhanced query field interactions

Working with fields in the query builder is now more intuitive. Previously, when you viewed the query results and clicked a field name in the sidebar, Axiom opened unique values. You can now select fields by clicking field names, and clicking the number on the right of a field name displays the unique values. This makes building queries faster and reduces unnecessary clicks when you’re exploring your data.

Smarter trace correlation across datasets

Trace linking just got smarter. Previously, you could only correlate logs and traces when the trace ID was stored in the trace_id field. Now, Axiom automatically detects trace IDs in any field containing trace in its name, whether that’s attributes.trace_id, custom_trace_id, or any other variation.

This enhancement makes it much easier to correlate between your logging and tracing datasets, especially if you’re using custom field naming conventions or migrating from other observability platforms.

Support for new versions of OpenTelemetry semantic conventions

We have added support for versions 1.36 and 1.37 of OpenTelemetry semantic conventions. These versions introduce updated attribute names for AI operations. Your existing traces continue to work seamlessly, while new traces benefit from the latest standards for tracking AI prompt inputs and completion outputs.

This ensures you’re getting the most accurate and standardized view of your generative AI workloads.

Adding support for new versions of OpenTelemetry semantic conventions means that the shape of your data can change. For more information, see Semantic conventions.

Enhanced data ingestion safeguards

We’ve strengthened data ingestion with better handling of edge cases and invalid data. Axiom now automatically sanitizes problematic data during ingestion to ensure your datasets remain clean and queryable.

When you ingest data that exceeds our limits, Axiom now handles it gracefully by replacing oversized strings with clear indicators, converting invalid float values like NaN and infinity to null, and preventing deeply nested structures from breaking your queries. We’ve also improved how reserved field names are handled — if you accidentally use internal field names like _sysTime, Axiom automatically renames them with a _user_ prefix to avoid conflicts.

These improvements mean more reliable data ingestion and fewer surprises when exploring your datasets, especially when working with diverse data sources or migrating from other platforms. For more information, see Limits on ingested data.

More of our favorite changes

• Enhanced help text for data trimming operations
• Better date parsing that now correctly handles formats like 25/09/2025, 19:15
• Improved chart options menu with better organization and visual hierarchy
• Fixed query field pagination to prevent infinite loading loops
• Better modal context handling for chart editing interfaces
• Fixed chart options editing interface that was previously inaccessible in some scenarios
• Resolved issue where query builder menus could be hidden behind other interface elements
• Fixed alignment issues in section bar actions across the dashboard
• Improved error handling for date parsing edge cases