• Created the Kubernetes Orchestration Platform using Node.js v22, TypeScript, and Express to manage containerized applications with essential configurations (service monitors, config maps, secrets, Ingress, NodePorts), enabling real-time performance insights, resource allocation recommendation, and allowing users to perform common DevOps operations on each pod directly via the UI by leveraging the Kubernetes core API, providing a unified platform for multi-level visibility, easy bottleneck detection, and intuitive hands-on management.

• Established pod metric visualization by integrating Prometheus for complex PromQL queries and Chart.js, enabling precise monitoring of critical performance data to drive data-driven decisions and improve operational efficiency.

• Implemented an Istio service mesh with sidecar injection to capture granular, request-level latencies beyond native Kubernetes/Prometheus limits, facilitating quicker identification and mitigation of microservice bottlenecks for improved user experience and higher resilience.

• Engineered a one-command Bash “quickstart” script to provision a Kubernetes environment—installing prerequisites, spinning up a cluster, deploying services and a test app, and generating synthetic traffic—dramatically reducing setup time and easing new-user onboarding.

• Developed a React-based interface using advanced Hooks (useMemo, useRef, useContext, and custom hooks) to manage a wide range of rapidly updating metrics (real-time vs. historical) across multiple pods, delivering intuitive dashboards that facilitate early performance anomaly detection and seamless user interaction.

• Developed the “Core DevOps Management REST API” via an Express server with modular routers and middleware chaining for non-blocking I/O. Facilitated scalable data ingestion from Prometheus and direct Kubernetes pod management, streamlining the monitoring pipeline.

Leveraged Python, Hive SQL, and Superset to build custom dashboards, automate data pipelines, implement A/B testing , and analyze user churn, boosting subscription retention, streamlining customer service, and reducing payment fraud.

Developed Python scripts to enhance kriging algorithms for predicting oil production. By leveraging hybrid geostatistical methods, enabling earlier detection of production shortfalls and more efficient resource allocation.

• Conducted hydraulic modeling and calculations for major refineries and pipelines.

• Designed HF acid Alkylation systems and specified pipes for optimal performance.

• Checked P&IDs to ensure accuracy and efficiency in process design.

• Conducted drilling & completion analysis for 180 Montney shale gas wells in northern British Columbia

• Utilized Accumap and GeoSCOUT database to collect and filter data on oil and gas wells

• Identified key relationships between geological data and drilling performance