Vishal Kumar

DevOps Engineer with 4 years of experience in scalable infrastructure development across cloud platforms. Strong programming skills in Python, JavaScript, Go, and Java, with expertise in Kubernetes, Docker, and Terraform. Skilled in creating CI/CD pipelines and implementing infrastructure-as-code for high-availability solutions. Recent focus on Agentic AI systems, leveraging LangChain to automate workflows and enhance decision-making processes.

• Vertica DataHub Connector: Contributed to the official Vertica plugin for DataHub, enabling ingestion of metadata (schemas, tables, projections, lineage) from Vertica databases into the DataHub metadata platform, improving data discovery.
• Vertica SQLAlchemy Dialect: Enhanced the Vertica SQLAlchemy dialect (Python ORM) by adding features and fixes for better compatibility, allowing seamless integration of Vertica with Python applications.
• Vertica Prometheus Exporter: Collaborated on the open-source Vertica Prometheus Exporter, enabling Prometheus to collect performance and usage metrics from Vertica databases for monitoring and alerting.
• Vertica Grafana Datasource Plugin: Contributed code and improvements to the official Vertica Grafana datasource plugin, improving authentication and query capabilities for building dashboards that visualize real-time Vertica data.

• AI Chatbot Agents (MCP Architecture): Developed dynamic LLM agents with user-specific database connectors.
• SimplifyQA AI POCs: Python R&D projects integrating AI into testing and project automation workflows.
• Designed and deployed a secure, scalable, and fully compliant DevOps architecture from the ground up to support the SimplifyQA platform—an enterprise project management and test automation solution. The infrastructure was architected for multi-cloud deployment and production-grade resilience, with built-in support for data protection, system observability, and regulatory compliance (including GDPR).
• Designed and developed custom Grafana and Prometheus plugins using Go (Golang) to provide robust monitoring and visualization capabilities for various database connectors. These plugins enabled real-time data collection, metric aggregation, and dashboard integration, improving observability and performance tracking across multiple database systems. The project involved deep collaboration with open-source communities to ensure compatibility, high code quality, and seamless integration with existing monitoring ecosystems.