Distributed-systems engineer building fault-tolerant, horizontally-scalable services — high availability, consensus and coordination across large fleets. Contributor to a live 100-node distributed edge system.

Projects

Leopard Detection System — Distributed & Fault-Tolerant Fleet
100 nodes · live
Engineered high availability, coordination and scaling across a 100-node distributed edge system.
  • High-availability camera failover: heartbeats detect node failure and a nearest-neighbour scheduler re-homes the stream in seconds — no single point of failure.
  • Multi-agent coordination: perception, tracking, alerting and dispatch agents coordinate over a message bus to turn detections into actions.
  • Scaling & load distribution: consistent-hashing-style placement spreads cameras / work evenly and rebalances when nodes join or leave.
  • Orchestration: Kubernetes-style self-healing and zero-downtime rolling updates across the fleet.
  • Messaging backbone: pub/sub topics with partitions & offsets carry telemetry reliably at fleet scale.
high availabilityconsensus / failoverconsistent hashingpub/subzero-downtime rollout

Reliability Engineering

Advanced AI Ecosystem Training

by DeepManthan AI Production AI Ecosystem Program
Intensive program on building & operating production AI systems — containers, orchestration, distributed systems, networking and deep learning.
Containerisation — Docker, images, isolation, OTA rollouts
Orchestration — Kubernetes, self-healing, scaling
Distributed Systems — Raft consensus, consistent hashing
Messaging — pub/sub, topics, partitions, offsets
Concurrency — multi-threading, producer–consumer
Computer Vision — CNNs, convolution, detection
Networking — TCP/IP, SSH, private overlays
Linux & Ops — processes, daemons, systemd

Impact Highlights

100
nodes coordinated
99.95%
availability
Zero
downtime on rollouts
Auto
failover & self-healing
Tip: open in a browser and use Print → Save as PDF. This is the Distributed Systems Engineer variant — personal details are placeholders.