Krishnendu Sukumar

Call Log processing pipeline: Created a centralized call-log processing pipeline for a critical pharma use case using Kubernetes, Ansible, and event-driven AWS services, enabling automated log collection, transformation, and storage across containerized microservices environments. Human-in-loop automation: Reduced manual operational effort from 2,500+ hours to nearly 1 hour by automating log extraction, infrastructure provisioning, deployment workflows, and configuration management, significantly improving operational reliability and efficiency. Developed a Highly Available Distributed Architecture on Kubernetes handling 10k+ daily transactions by configuring deployments, services, Liveness & Readiness Probes, and Horizontal Pod Autoscaler (HPA); optimized Docker image builds and rollout strategies to reduce deployment time by 40%, earning client recognition.

DevOps Engineer at Infosys (2024-11 – Present)

• Call Log processing pipeline: Created a centralized call-log processing pipeline for a critical pharma use case using Kubernetes, Ansible, and event-driven AWS services, enabling automated log collection, transformation, and storage across containerized microservices environments.
• Human-in-loop automation: Reduced manual operational effort from 2,500+ hours to nearly 1 hour by automating log extraction, infrastructure provisioning, deployment workflows, and configuration management, significantly improving operational reliability and efficiency.
• Developed a Highly Available Distributed Architecture on Kubernetes handling 10k+ daily transactions by configuring deployments, services, Liveness & Readiness Probes, and Horizontal Pod Autoscaler (HPA); optimized Docker image builds and rollout strategies to reduce deployment time by 40%, earning client recognition.
• Implemented CI/CD pipelines and used Terraform for infrastructure provisioning, Docker image builds, configuration rollout, and Kubernetes deployments.

Research Fellow & Fullstack Associate at CSIR-CSIO & DRDO (2023-12 – 2024-11)

• Worked with bare-metal Linux servers hosting ML workloads and scientific research pipelines for government R&D projects.
• Built internal fullstack interfaces using Next.js and Python to visualize scientific datasets, model outputs, and research insights.
• Contributed to snow avalanche detection research initiatives under DRDO by supporting data processing workflows and scientific computing environments.

B.Tech in Computer Science & Engineering – KIET, AKTU (2019-07 – 2023-07)