May 2026 monthly summary for the opensearch-project/OpenSearch development effort. Focused on delivering distributed analytics capabilities, strengthening reliability across the analytics engine, and expanding data-binning capabilities, while advancing end-to-end prepared-plan execution and cross-shard consistency. Key achievements (top 3-5): - Analytics Engine: Implemented Analytics Engine - Aggregation and Fragment Processing Enhancements with a distributed aggregation mode, prepared-plan aggregation infrastructure, improved fragment-conversion workflow, and state-expanding aggregates across shards using Rust UDAFs and DataFusion integration. - DataFusion integration and planning: Introduced aggregate decomposition resolver alignment with the backend plan adapter, and consolidated resolver logic to a robust end-to-end prepared-plan path (prepare_partial_plan, prepare_final_plan, and execute_local_prepared_plan). - Bucketing functions: Added new PPL bucketing functions (span_bucket, width_bucket, minspan_bucket, range_bucket) to enhance data binning capabilities. - Cross-shard reliability: Reduced type and wire-format fragility by collapsing fragmentation/conversion layers, stabilizing string/utf8 handling and timestamp coercion, and addressing empty-partial scenarios in streaming with synthetic zero-row schema when necessary. - QA and robustness: Introduced a sandbox QA module for analytics engine REST integration tests; expanded test coverage for state-expanding aggregates and end-to-end flows across shards. Business value and impact: - Enabled scalable, distributed analytics with prepared plans and Rust-backed UDAFs, improving throughput and reliability for large datasets. - Expanded analytics capabilities via bucketing, enabling richer binning-based analyses. - Increased resilience and predictability of distributed queries by aligning planner, fragment conversion, and data-plane type handling, reducing runtime surprises and failures in multi-shard runs. - Reduced operational risk through sandbox QA coverage and streamlined end-to-end plan lifecycles between Java and Rust components. Technologies and skills demonstrated: - Rust (UDAFs, performance-sensitive components) and DataFusion integration - Arrow IPC and Substrait-based plan translation - Calcite/OpenSearch planner enhancements and AggregateDecomposition/Resolver patterns - JNI/FFI for end-to-end prepared-plan lifecycle (Partial/Final) coordination - Distributed systems patterns for multi-shard aggregation and state management - Test automation and QA scaffolding for REST analytics workloads

Concise monthly summary for 2026-01 focusing on business value and technical achievements for wazuh-indexer.

November 2025 focused on build-system modernization for wazuh-indexer to reduce build complexity and unlock modern Java capabilities. The primary work removed legacy Java version checks in Gradle across modules, enabling future performance features (e.g., Vector API) and cleaner maintenance. No user-facing features released this month; the changes lay groundwork for faster builds and easier adoption of newer JDKs, improving developer productivity and long-term reliability.

October 2025 Monthly Summary focusing on delivering performance enhancements, observability improvements, and a critical bug fix across two OpenSearch-related repositories.

September 2025 monthly summary for wazuh/wazuh-indexer focusing on performance, reliability, and maintainability. Key work includes refactoring the date rounding utility to optimize histogram aggregations, improving efficiency and robustness during time zone transitions. Added observability enhancements with new metrics to track search query failures and star-tree query failures, enabling faster remediation. Extended analytics capabilities with Multi-Terms Aggregation for StarTree through iterator refactors, pre-computation optimizations, and improved validation and tests. Updated repository branding and licensing visibility with README licence and LinkedIn badges. These changes collectively improve query performance, observability, and code quality while maintaining strong test coverage and documentation.

August 2025 was a focused delivery period with performance and correctness improvements across wazuh-indexer and Lucene. Key feature work delivered faster, more scalable search capabilities, and tighter query correctness, driving measurable business value through improved performance, lower GC pressure, and broader IP search support. The work enhanced core query paths, reduced memory churn, and strengthened locale handling for numeric range queries. Overall, the month delivered notable architectural and code-quality gains that position the project for higher throughput and more reliable analytics at scale.

July 2025 Monthly Summary - wazuh/wazuh-indexer Key objective: strengthen observability and reliability of Star-Tree query reporting to drive better index performance decisions and troubleshooting. Highlights: - Delivered Star-Tree Query Statistics and Metrics Reporting, enabling reporting of current values, time spent, and total counts across nodes, indices, and shards. This enhances visibility into Star-Tree query performance and helps identify hotspots and optimization opportunities. - Reworked the implementation with a builder pattern to improve maintainability, readability, and testability of the reporting components. - Expanded test coverage with integration tests that validate accurate reporting across multiple index types, reducing risk of regressions in production environments. - Incremental quality and maintainability improvements captured via commits (including version fixes and small improvements) to support long-term stability. Impact: - Improved business value by providing actionable metrics for performance tuning and capacity planning; faster diagnosis of Star-Tree query issues; stronger confidence in indexer reliability. - Technical achievements include architectural improvement (builder pattern), comprehensive integration testing, and cross-index-type reporting validation.

June 2025 monthly summary for wazuh/wazuh-indexer focused on delivering enhanced analytics capabilities, API robustness, and release-readiness. Key work centers were Star Tree aggregations, and aligned admin/release documentation to improve customer-facing messaging and internal guidance. The work lays groundwork for faster, more scalable queries and clearer release communication for admins and developers.

May 2025 monthly summary for wazuh/wazuh-indexer: Delivered an update to the Code of Conduct governance contact to reflect OpenSearch and clarified reporting channels, with no changes to core policy. The change was implemented with a targeted commit and documented in CODE_OF_CONDUCT.md and README.md.

April 2025 (2025-04) — wazuh/wazuh-indexer: Key feature delivered, major bug fixed, and impact-focused achievements with business value. Summary of work: - Implemented OpenSearch Aggregation Performance Enhancements leveraging Star-tree to accelerate numeric range aggregations and optimized global ordinals loading, reducing redundant data fetches during aggregations. - Fixed critical inefficiency by eliminating redundant global ordinals loading, lowering query latency and improving resource utilization for user-facing searches. Impact: - Faster, more scalable search experiences on large datasets. - Reduced data fetch overhead and lower operational costs due to improved efficiency in the aggregation pipeline. - Strengthened system responsiveness for end users and downstream analytics. Technologies/skills demonstrated: - Star-tree indexing and OpenSearch aggregation optimizations - Performance tuning and efficient data loading strategies - Change management evidenced by targeted commits and focused feature/bug fix work

Monthly work summary for 2025-03 (wazuh/wazuh-indexer): Delivered Star Tree precomputation enhancements to support keyword and numeric term aggregations, enabling faster and more accurate search analytics. Fixed precomputation ordering for min/max aggregators when a point converter is available, ensuring correct leaf max/min values at segment level. Overall impact includes faster data retrieval, more reliable aggregations, and improved analytics confidence for users. Demonstrated technologies and skills include Star Tree precomputation, aggregations, point converters, and robust code contributions in a data indexing pipeline.

February 2025 in wazuh/wazuh-indexer: Delivered a critical correctness fix to the Date Histogram Aggregator by using a dynamically determined date fieldName instead of hard-coded @timestamp. This change ensures accurate bucketing when a custom date field is configured, improving analytics reliability and reducing misclassification of time-based data.

January 2025 monthly summary for wazuh/wazuh-indexer focused on delivering Star Tree-based optimization for time-series analytics. Key feature delivered: Star Tree Indexes for Date Histogram Aggregations, enabling date histograms to leverage Star Tree indexes when combined with metric aggregations to improve query performance. This work validates and leverages Star Tree capabilities for time-series data, aiming to reduce latency on dashboards and analytics queries. Bugs fixed: No major bugs reported or fixed this month. Impact and accomplishments: Enhanced time-series query performance and scalability for wazuh-indexer, enabling faster analytics and more efficient resource usage on dashboards and alerts. The work supports the product’s time-series analytics roadmap and positions the team to continue optimizing star-tree based queries. Technologies/skills demonstrated: Star Tree indexing, date histogram optimization, metric aggregations, performance tuning, commit-driven development (see commit b5234a54db3314d6d7c8ba75966b80f8d03ba61e).