October 2025: Focused on memory safety, performance, and reliability across gem/oq-engine and GEMScienceTools/oq-mbtk. Delivered memory-efficient Starmap with at least 1 GB RAM per thread, improved observability through enhanced logging and monitoring, and tile splitting/refactoring that simplifies and speeds up tiling. Achieved NumPy 2 compatibility fixes and stabilized tests to support numpy 2 migration, introduced concurrency and resource-management improvements (multi-pool execution, OQ_NUM_CORES), and enabled OnnxRuntime as an optional dependency. Included robustness and quality improvements (plotting corrections, test fixes, documentation/CHANGES). Result: higher throughput, easier operation, and smoother upgrades with reduced risk and better diagnostics.

Monthly Summary for Sep 2025 - gem/oq-engine Key features delivered: - H3-based spatial indexing migration: replaced geohash with H3 for hex-based indexing, introduced hex6 usage, and made H3 an optional dependency; improvements to plot_h3 streamline geospatial workflows and reduce coupling to legacy geodata tech. This enables faster, more scalable spatial queries and visualizations across dashboards and reports. - INI-based Jobs Extraction feature: implemented endpoint/jobs_from_inis to extract job definitions from INI configurations, with added tests to ensure reliability; this improves automation of batch calculations and reduces manual configuration errors. - Private calculation run endpoint: added /v1/calc/run_ini to execute remote calculations via a private API path, enabling secure, backend-driven computation workflows without exposing sensitive configs to the client. - DBServer cache configuration and type change: introduced config.dbserver.cache and migrated its type to string, simplifying configuration management and compatibility with existing tooling. - Site labels as dictionary: migrated site_labels to a dictionary for more flexible and accurate mappings, improving UI labeling and downstream data joins. - Override_vs30 logic improvement: refined override_vs30 behavior to increase robustness and predictability of values in edge cases, reducing surprising results in downstream models. - Inference session performance improvements: disabled threading in PicklableInferenceSession and reduced data transfer during inference sessions, delivering faster end-to-end runtimes and lower memory usage in batch processing. Major bugs fixed: - WebUI MIMETYPE handling: ensure MIMETYPE uses application/zip when needed in the WebUI, preventing misinterpretations and downstream errors. - Negative damages fixed: corrected small negative damages due to numeric errors in calculations, improving numeric stability. - Changelog maintenance: updated and fixed changelog entries, including [ci skip] handling, to reflect changes accurately for release notes. - Install script fail-fast: install.py now exits if any required tool is not installed, preventing partial or invalid environments. - MedianSpectrum macOS compatibility: skipped the MedianSpectrum demo on macOS with Python 3.11 to maintain compatibility across CI platforms. - Import fixes and test tolerances: fixed import issues and stabilized test tolerances to reduce flakiness in the CI suite. Overall impact and accomplishments: - Improved reliability, scalability, and maintainability of oq-engine, enabling faster time-to-value for customers relying on accurate geospatial analyses and batch processing. - Delivered automation enhancements (INI-based jobs, private calc endpoint) that reduce manual steps and increase security for sensitive workflows. - Strengthened code quality and developer experience through targeted refactors, cleanup, and CI/test stability improvements. Technologies/skills demonstrated: - Python-centric backend improvements, REST API design, and endpoint development. - Geospatial indexing using H3 and plotting improvements. - Config management enhancements and type migrations for service stability. - Performance and memory optimization in inference workflows. - Test-driven development, CI stabilization, and code quality practices (linting, PEP8, refactors).

July 2025 monthly performance summary for the oq-engine and related tooling. Focus this month was on delivering core feature refinements, stabilizing risk calculations, expanding data management, and improving observability and performance to accelerate multi-site reporting. The work combined deep refactors with practical reliability improvements, enabling faster, more predictable releases and better data quality for customers. Key features delivered and notable improvements: - Refactor and extend extract_aggrisk_tags, including related modules, across three commits to improve maintainability and tagging accuracy. - Data/config restructuring with aggexp_tags.csv and multi-site export support for mean_disagg_by_src, enabling consistent reporting across sites. - Logging enhancements and broader monitoring coverage for event_based_risk to improve observability and faster issue diagnosis. - Extensive testing enhancements, including multi-tag test coverage and stabilization fixes across the test suite. - Performance and resource-management improvements, including removal of time.sleep in event_based_risk, adjustment of max_gmvs_chunk, memory optimizations, and DstoreCache integration to boost throughput and reduce memory footprint. Major bugs fixed and stability improvements: - Stability and correctness fixes in risk tagging, ebr_from_gmfs waiting behavior, and test stability. - Override_vs30, plot_disagg, and vs30=-999 related fixes to ensure consistent risk calculations and reliable visualizations. - CI/test hygiene improvements and test/data workflow fixes to support stable nightly runs. Overall impact and accomplishments: - Increased reliability of risk computations and tagging logic, minimizing false positives/negatives and improving data quality for downstream analytics. - Faster batch processing and reduced memory usage, enabling larger workloads and multi-site reporting with lower infrastructure costs. - Improved observability, error handling, and diagnostics, reducing time-to-resolution for incidents. - Stronger code quality and maintainability through systematic refactoring and test-driven improvements, setting the stage for more rapid, safe feature delivery. Technologies, skills demonstrated: - Python: large-scale refactoring, API surface stabilization, and performance-focused changes (including NumPy/Numba toggles, memory-management tweaks). - Testing and QA: expanded test coverage, test suite stabilization, and CI/test workflow improvements. - Observability: enhanced logging and monitoring hooks across risk components. - Data engineering: data/config restructuring, multi-site export support, and changes to aggregation logic for consistent outcomes. - Performance optimization: reducing sleeps, optimizing batch sizing, and memory footprint reductions.

June 2025 — gem/oq-engine monthly summary highlighting core feature deliveries, bug fixes, and impact across the data pipeline and modeling stack. Key improvements focused on correctness, performance, packaging, and observability, with business value in reliability, faster workflows, and richer analytics. Key deliverables: - Core utilities refactor: gen_poes now returns tau; hazard_curve refactor to improve accuracy and readability. (Commits: 67b2d36c9b609a6dd5efbbe21177e0d2090297c7; f5f9f253f2c1e1b00ed5681a4842b9079ea0f23b) - expo_to_hdf5 memory optimizations and readability improvements: reduced memory footprint, removed gzip, added readability checks; configurable concurrency. (Commits: 448531c42124a044b806061e21acbaa5f092d558; 43f0bcd069084e1b45f30572c57cb8a4635eb232; 49a6ea45ec11519c4817833ce12031c2d3077bc0; 290a4e4882944aeae0cc19d1cc5aaa190e6e362f; 4dcc46729d9b7faed686d296c399f940296c7d02) - Data packaging and analytics enhancements: zip exposures and taxonomy mappings; store assets grouped by country for analytics; improved data transfer workflows. (Commits: 61b740ea60d42942056ff662126081dc1142e130; 4924c20a3162d334a67877629bbdb7cbd95dec48; 513c05dbbaff78c38e765d8e3557fb0f1cae05b8; 753ec206104adaf8e712a8a98c656bf592341ac7) - Data quality and integrity improvements: fix ID_2 handling (strings, no trailing .0), ID_1 aggregation, missing hdf5 checks for nonparametric/fault ruptures, and enhanced error handling for IMTs and ShakeMap. (Commits: 4005eb2750eaf3d0b25e932f5f3b87e51ee1af6b; b07b98cc5d32aeef513a5a2e7714c2c5075c076f; 8bd68c88cfe7d73574cc2567a7f47d60c3781e78; 0a323378806ff40b2492c42b24cb4ddd69aee917; 14981d441611dbe8645753c61f9106ffff1d4873; other related commits) - Testing, CI stability, and reliability: extensive test fixes, AMD-processor compatibility improvements, test infrastructure restoration, and CI cleanup. (Representative commits: 75970f45b96d236657c9ee3e910999a9c5b09c01; ff9bc6bd33dd58296fbd7d7c00935ad489f16431; be33e6629b1acc954ee2e80fee4bb832a8b92f2b; e502ee7e70d39524d35b2d48d2664dba084e00fb; d054588c6d2d1d3bd8a994bc45777436f6c6de2d; 25667feeb5f8b177ae9aeb176759c356b0b047d6) - Observability and documentation: enhanced logging/monitoring, updated REST API docs and changelog, and improved docstrings. (Commits: 9731b26a8b626a15288a0500144f9708bd4f13b9; 57774b3e888922315b700d3525c2d2e585015b48; 5f3783409668f6a32724abe654c846a414c6359b; 5053f0961d1f832f2c2a8d8ca5924c3824615d46; 2592b7650aefa150b1a674a48e177a8e37402364) Top 3-5 achievements: - Core utilities refactor delivering tau output for gen_poes and cleaner hazard_curve logic. - Significant memory and performance gains in expo_to_hdf5, enabling larger workloads with lower memory pressure. - Enhanced data packaging and country-based analytics via assets_by_country and zip packaging for exposures/taxonomy mappings. - Strengthened data integrity (ID_2 handling, ID_1 aggregation, missing HDF5 checks) and improved error handling for ShakeMap workflows. - Improved testing, CI reliability, and observability (monitoring/logging) with updated docs and changelog.

May 2025 performance summary for gem/oq-engine and GEMScienceTools/oq-mbtk. Delivered key features, strengthened reliability, and advanced data delivery capabilities across hazard modeling pipelines. Notable outcomes include expanded seismogenic depth handling and uncertainties, hardened source-model/build robustness, and API/data-model modernization, accompanied by broader test coverage and performance improvements. These changes improve hazard calculation accuracy, reduce build/test fragility, accelerate release readiness, and enhance maintainability across the codebase.

April 2025 (2025-04) for gem/oq-engine: Delivered a set of high-impact features and stability improvements across the risk modeling stack. Key features include GSIM aliases implemented as thunks, robust taxonomy mapping validation with tests and CSV updates, Volcanic peril support via a new SecondaryPeril subclass and storage changes, and a performance-oriented distance matrix implementation stored in shared memory using a 32-bit representation. Additional feature work included multi-risk support, AELO/GMM enhancements (MacedoEtAl2019SInter) with broader testing, and utility/functionality additions (get_ruptures). Infrastructure reliability was strengthened through demo fixes and test stabilization for InfrastructureMultiPeril, along with targeted documentation and changelog updates. The combination of data quality, performance, and broader risk coverage drives faster, more reliable risk assessment and reporting for customers.

2025-03 monthly summary for gem/oq-engine: Delivered high-value features and stabilization work across core OQ workflows, improving data visibility, risk assessment outputs, and system reliability. Key features extend exposure data tooling, multifault handling, configurable aggregations, and expanded OQImpact outputs, while performance improvements and code quality initiatives enhanced maintainability and execution efficiency. The month also reinforced testing infrastructure and documentation to sustain release confidence.

February 2025 – Delivered cross-repo features and stability improvements across gem/oq-engine and GEMScienceTools/oq-mbtk, driving clearer governance, stronger data quality, and release readiness for engine-3.23. The work emphasizes business value: more accurate risk calculations, reliable CI, and maintainable code with scalable infrastructure changes.

January 2025 for gem/oq-engine delivered targeted features and reliability improvements across performance, compatibility, and maintainability. Key outcomes include refined weight calculation with CI-skip refinement and parameter tuning, introduction of minimum_engine_version to enforce compatibility, faster CPS preclassical path, site-model integration via ruptures.hdf5, and extension of rupture_dict to include msr and aspect_ratio. These changes improve calculation fidelity, portability, and maintainability. Significant bug fixes and stability work reduced log noise and improved reliability, supporting smoother operation in production.

December 2024 monthly summary for gem/oq-engine focused on QA stability and cross-platform reliability. No new feature work was delivered this month; the primary activity was a targeted bug fix to stabilize tests in the reinsurance-risk_by_event export workflow. The change increases the tolerance for floating-point comparisons to accommodate platform variations, improving test reproducibility and CI reliability.