elastic

elastic/rally

Macrobenchmarking framework for Elasticsearch

2.0K stars 339 forks 2.0K watchers Python Apache License 2.0

elasticsearch

7 Open Issues Need Help Last updated: Jul 8, 2026

Open Issues Need Help

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Implement `percent_completed` for `wait-for-recovery` tasks 4 days ago

enhancement good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Migrate JFR parameter recording-template to jfr-recording-template about 1 month ago

good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Record elasticsearch's source revision in the metrics stored in the rally-results and rally-races indices (when using pipeline benchmark-only) about 2 months ago

:Metrics good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Rally should not overwrite pre existing templates by default 2 months ago

good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Improve assertion logging/messaging when operation does not return metadata 4 months ago

enhancement help wanted :Usability :Load Driver good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Make git operations more resilient 7 months ago

:Usability good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch

Add Memory Maps telemetry device over 1 year ago

AI Summary: Implement a new telemetry device for the Elasticsearch Rally macrobenchmarking framework. This device should periodically report the number of memory maps used by the Elasticsearch process by reading the `/proc/<ES PID>/maps` file. This addresses the need identified in Elasticsearch issue #119652 for better memory usage monitoring during benchmarks.

Complexity: 4/5

enhancement good first issue

2.0K

Macrobenchmarking framework for Elasticsearch

Python

#elasticsearch