Debangshu Nath
Kolkata, India
Debangshu Nath
Deploy AI Applications on Kubernetes with GitOps
Category : Systems automation
I help deploy AI and backend applications on Kubernetes using production-style DevOps workflows.
Services include:
• Kubernetes cluster deployment
• Dockerization
• ArgoCD GitOps setup
• CI/CD pipelines
• Ingress configuration
• Environment management with Kustomize
• AI inference deployment using llama.cpp / Ollama
• Backend deployment for Node.js / FastAPI apps
I specialize in Kubernetes-native deployment workflows, infrastructure automation, and scalable AI inference systems.
Services include:
• Kubernetes cluster deployment
• Dockerization
• ArgoCD GitOps setup
• CI/CD pipelines
• Ingress configuration
• Environment management with Kustomize
• AI inference deployment using llama.cpp / Ollama
• Backend deployment for Node.js / FastAPI apps
I specialize in Kubernetes-native deployment workflows, infrastructure automation, and scalable AI inference systems.
Portfolio
Working hours
- Monday:08h00 To 18h00
- Tuesday:08h00 To 18h00
- Wednesday:08h00 To 18h00
- Thursday:08h00 To 18h00
- Friday:08h00 To 18h00
- Saturday:Not available
- Sunday:Not available
![I help deploy AI and backend applications on Kubernetes using production-style DevOps workflows.]()
I help deploy AI and backend applications on Kubernetes using production-style DevOps workflows.50 $Services include: • Kubernetes cluster deployment • Dockerization • ArgoCD GitOps setup • CI/CD pipelines • Ingress configuration • Environment management with Kustomize • AI inference deployment usin ...
- Developed autonomous control workflows for mission execution and system coordination using MAVLink-based communication, enabling minimal human intervention.
- Integrated communication protocols and control layers to ensure reliable telemetry handling and system-level coordination across components.
- Built backend pipelines for processing sensor and visual data across inspection and monitoring workflows, from capture to analysis.
- Implemented on-device inference pipelines for real-time detection and response during operation.
- Contributed to system design across autonomy, backend services, and model integration with focus on modularity and reliability.
- Integrated communication protocols and control layers to ensure reliable telemetry handling and system-level coordination across components.
- Built backend pipelines for processing sensor and visual data across inspection and monitoring workflows, from capture to analysis.
- Implemented on-device inference pipelines for real-time detection and response during operation.
- Contributed to system design across autonomy, backend services, and model integration with focus on modularity and reliability.
- 🇬🇧 English
- 🇮🇳 Hindi
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