February 2026 performance summary for the openeo-geopyspark-driver. The month focused on expanding Sentinel-1 product support, hardening STAC integration and loading workflows, and extending Sentinel-3 STAC API coverage. These changes improved data availability, reliability, and performance, enabling users to access a broader set of products with fewer manual interventions.

January 2026 performance summary for Open-EO geopyspark-driver and related Apex algorithms. Delivered substantial STAC integration improvements, reliability enhancements, and tooling updates that improve accuracy, maintainability, and CI reliability. Highlights include a refactor of load_stac for clearer preparation vs raster loading, a cellsize_override mechanism with a fallback, propagation of overrides to OpenSearch feature resolution, and initial STAC support extensions for S1 backscatter and Sentinel-3. Added comprehensive STAC testing and filtering improvements for backscatter workflows, as well as performance and dependency upgrades to support numpy 2.x, parallelized CI tests, and benchmark/test controls.

December 2025 monthly summary for Open-EO/openeo-geopyspark-driver. Focused on delivering data fidelity improvements, scalable catalog handling, and robust operational resilience, with concrete commits that enhance Copernicus DEM support, SAT/STAC processing, and job tracking.

Monthly summary for 2025-11 (Open-EO/openeo-geopyspark-driver): Key features delivered, major bugs fixed, and overall impact with a focus on business value and technical achievement.

In October 2025, delivered targeted features and fixes across two Open-EO repositories to improve deployment reliability, data integrity, and test stability, unlocking business value in production-grade workflows. Key outcomes include improved Kubernetes Spark deployment with Yunikorn backend, ensured CatBoost model artifacts are downloaded with correct extensions, stabilized tests for Scala 2.13 and NumPy 2.x, extended backend compatibility for openeo-dev.vito.be, and corrected forest fire mapping reference data usage. These changes reduce deployment risks, improve model asset handling, and increase developer velocity for next releases.

September 2025: Open-EO/openeo-geopyspark-driver delivered a robust, future-ready CI/CD and dependency strategy, enabling reliable Python 3.11 testing, modern NumPy 2.x compatibility, dynamic JAR management, and strengthened unit-test stability. These changes reduce release risk, improve maintainability, and support broader Python/dependency coverage while stabilizing the test suite.

August 2025 — Open-EO/openeo-geopyspark-driver: Delivered core enhancements to ML model lifecycle and batch processing, delivering measurable business value through reliability, security, and storage flexibility. Implemented unified ML model loading/saving via MLModelLoader with a dedicated loader (modelloader.py), enhanced permissions handling with a failsafe, and enabled local filesystem persistence and archiving of ML artifacts. Extended loading support for CatBoost and Random Forest models across URLs, batch jobs, and distributed storage. Batch/Yarn Job Runner was enhanced to parameterize Spark/Hadoop configurations via BatchJobSubmitArgs, make Hadoop options configurable, refine docker_mounts handling, and strengthen test scaffolding for Yarn backend configuration. These changes reduce operational risk, accelerate ML deployment, and enable scalable batch processing in production.

Open-EO geopyspark-driver – July 2025: Reliability and data integrity improvements focusing on Orfeo processing and SPACETIME datacubes. Implemented configurable GDAL HTTP retry for Orfeo processing and fixed temporal dimension integration for GeoPySpark datacubes via a TiledRasterLayer wrapper.

June 2025 monthly summary for Open-EO/openeo-geopyspark-driver. This period focused on hardening batch processing for non-Kubernetes deployments and stabilizing Spark-based batch jobs. Key outcomes include permission and ownership improvements for batch job directories, config-driven ownership controls, and updated documentation to reduce operational friction, along with a reliability enhancement to limit Spark task retries per executor.

May 2025 monthly summary for Open-EO/openeo-geopyspark-driver focused on robustness, memory management simplification, and maintainability improvements. Delivered targeted fixes and refactors that enhance user experience and reduce support burden while easing future enhancements.

April 2025 monthly summary for Open-EO/openeo-geopyspark-driver: Achieved stability and compatibility improvements across geopyspark dependency management, CRS handling, and test infrastructure. Focused on delivering business value through reliable builds, accurate data handling, and improved interoperability for downstream users.

In March 2025, the Open-EO geopyspark driver delivered meaningful reliability and accuracy improvements across core data processing, observability, and test coverage. The work focused on hardening data handling, improving memory efficiency, and strengthening validation and monitoring to support scalable, production-grade geospatial processing.

February 2025 monthly summary for Open-EO/openeo-geopyspark-driver focusing on robustness, testing improvements, and preparatory work for future migrations. Delivered key features and bug fixes with clear business value and technical implications, strengthening data processing reliability and test coverage while paving the way for RetryStacIO timeouts migration.

January 2025: Open-EO/openeo-geopyspark-driver delivered a robust STAC API integration by introducing a custom StacApiIO with timeout and retry support, refactoring to inherit DefaultStacIO, and hardening URL validation and timeout handling. Implemented extensive tests for load_stac and STAC IO, including new mocks (UrllibPoolManagerMocker) and alignment with the new StacApiIO interface. The work reduces reliability risk when querying STAC endpoints, improves resilience under slow networks, and increases maintainability through clearer abstractions. Key commits span feature work and test infrastructure changes, ensuring end-to-end robustness of STAC interactions and compatibility with updated test utilities." ,

For 2024-12, delivered the Flexible Backend Override for Benchmark Testing in ESA-APEx/apex_algorithms. Added a new CLI option --override-backend to test_benchmarks.py to specify an alternative backend URL for benchmarking, enabling testing against different backend environments without editing benchmark JSON files. This change enhances test portability and environment coverage, improving validation of algorithm performance across backends.