
Over eight months, K. Peña developed and maintained data analysis pipelines and operational documentation for the lsst-sitcom/notebooks_vandv and lsst-ts/observatory-ops-docs repositories. Peña built Jupyter Notebooks in Python and Pandas for alarm analytics and temperature sensor modeling, applying machine learning and time series analysis to support observatory campaigns. They refactored code for maintainability and reproducibility, improving onboarding and review efficiency. In parallel, Peña enhanced documentation for Kubernetes access, subsystem recovery, and calibration procedures, using technical writing and DevOps skills to standardize workflows. The work demonstrated depth in both engineering and documentation, addressing operational clarity and data-driven decision-making for observatory teams.

September 2025 monthly summary for lsst-ts/observatory-ops-docs: Delivered consolidated recovery procedure and troubleshooting documentation enhancements across OSS, M2, and LATISS camera recovery guides, standardizing troubleshooting steps, connection/access instructions, and contributor acknowledgments. The updates improve operator onboarding, reduce mean time to recovery, and strengthen cross-team operational readiness.
September 2025 monthly summary for lsst-ts/observatory-ops-docs: Delivered consolidated recovery procedure and troubleshooting documentation enhancements across OSS, M2, and LATISS camera recovery guides, standardizing troubleshooting steps, connection/access instructions, and contributor acknowledgments. The updates improve operator onboarding, reduce mean time to recovery, and strengthen cross-team operational readiness.
Monthly summary for 2025-08: Documentation enhancements across the observatory-ops-docs repository to streamline access to critical subsystems (Kubernetes, MT M2 EUI) and recovery procedures. These updates improve onboarding, reduce operational friction, and standardize runbooks for on-call engineers and developers.
Monthly summary for 2025-08: Documentation enhancements across the observatory-ops-docs repository to streamline access to critical subsystems (Kubernetes, MT M2 EUI) and recovery procedures. These updates improve onboarding, reduce operational friction, and standardize runbooks for on-call engineers and developers.
July 2025: Delivered Lag Feature Target Sensor Update in notebooks_vandv, updating the target sensor from ESS_113_Dome to ESS_112_M2. This change affected LagFeatureTransformer initialization and the related notebook narrative, and aligns feature relationship analysis with final remarks to improve analysis fidelity and reproducibility. The work was completed with reviewer feedback addressed as SITCOM-2079, ensuring clarity and alignment with project goals. Overall, this enhances the reliability of lag-feature based analyses and supports downstream decisions in notebook-driven workflows.
July 2025: Delivered Lag Feature Target Sensor Update in notebooks_vandv, updating the target sensor from ESS_113_Dome to ESS_112_M2. This change affected LagFeatureTransformer initialization and the related notebook narrative, and aligns feature relationship analysis with final remarks to improve analysis fidelity and reproducibility. The work was completed with reviewer feedback addressed as SITCOM-2079, ensuring clarity and alignment with project goals. Overall, this enhances the reliability of lag-feature based analyses and supports downstream decisions in notebook-driven workflows.
June 2025 monthly summary for the lsst-sitcom/notebooks_vandv repository focused on code quality improvements. Delivered a notebook refactor to improve readability and maintainability by cleaning imports and metadata and removing redundant execution-related data. No critical bugs reported in this scope. The changes align with ongoing efforts to reduce maintenance overhead and speed future enhancements.
June 2025 monthly summary for the lsst-sitcom/notebooks_vandv repository focused on code quality improvements. Delivered a notebook refactor to improve readability and maintainability by cleaning imports and metadata and removing redundant execution-related data. No critical bugs reported in this scope. The changes align with ongoing efforts to reduce maintenance overhead and speed future enhancements.
May 2025 highlights for lsst-sitcom/notebooks_vandv: Delivered a comprehensive ComCam Temperature Sensor Data Analysis and Predictive Modeling pipeline, including data retrieval, visualization, rolling-window PCA, and a multiple linear regression model to predict dome air temperature. This enables deeper understanding of thermal conditions and sensor relationships during the campaign and supports proactive thermal management.
May 2025 highlights for lsst-sitcom/notebooks_vandv: Delivered a comprehensive ComCam Temperature Sensor Data Analysis and Predictive Modeling pipeline, including data retrieval, visualization, rolling-window PCA, and a multiple linear regression model to predict dome air temperature. This enables deeper understanding of thermal conditions and sensor relationships during the campaign and supports proactive thermal management.
April 2025 performance summary: Key feature delivered: Alarm Analysis Notebook for ComCam Sky Campaign in lsst-sitcom/notebooks_vandv. Implemented end-to-end alarm analytics workflow using LSST EFD client; produced visualizations and time-series analyses for alarm frequencies, reasons, and acknowledgment status; refined filtering to focus on meaningful, non-muted alarms and to exclude 'Enabled' and 'ScriptFailed' statuses; severity filter (severity > 1) surface critical events. This enables faster triage and improved monitoring during campaigns.
April 2025 performance summary: Key feature delivered: Alarm Analysis Notebook for ComCam Sky Campaign in lsst-sitcom/notebooks_vandv. Implemented end-to-end alarm analytics workflow using LSST EFD client; produced visualizations and time-series analyses for alarm frequencies, reasons, and acknowledgment status; refined filtering to focus on meaningful, non-muted alarms and to exclude 'Enabled' and 'ScriptFailed' statuses; severity filter (severity > 1) surface critical events. This enables faster triage and improved monitoring during campaigns.
February 2025 – Highlights: LATISS Daytime Calibration Documentation Improvements delivered in lsst-ts/observatory-ops-docs. Updated documentation clarifying daytime calibration procedures, warnings, calibration data interpretation, and operational guidelines. The work involved two commits linked to SITCOM-1793 (comment updates). No major bugs fixed this month. Business impact: clearer, safer LATISS daytime operations, improved data interpretation, and faster onboarding for new team members. Technologies/skills demonstrated: technical writing, documentation governance, Git version control, SITCOM workflow, and cross-team collaboration.
February 2025 – Highlights: LATISS Daytime Calibration Documentation Improvements delivered in lsst-ts/observatory-ops-docs. Updated documentation clarifying daytime calibration procedures, warnings, calibration data interpretation, and operational guidelines. The work involved two commits linked to SITCOM-1793 (comment updates). No major bugs fixed this month. Business impact: clearer, safer LATISS daytime operations, improved data interpretation, and faster onboarding for new team members. Technologies/skills demonstrated: technical writing, documentation governance, Git version control, SITCOM workflow, and cross-team collaboration.
January 2025: Delivered Calibration Procedures Documentation Update for lsst-ts/observatory-ops-docs. Clarified daytime calibration conditions and removed a WREB temperature check step, providing clearer operational guidelines for calibration image acquisition. The change enhances operational predictability and supports safer, faster daytime calibrations, aligning with SITCOM-1793.
January 2025: Delivered Calibration Procedures Documentation Update for lsst-ts/observatory-ops-docs. Clarified daytime calibration conditions and removed a WREB temperature check step, providing clearer operational guidelines for calibration image acquisition. The change enhances operational predictability and supports safer, faster daytime calibrations, aligning with SITCOM-1793.
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