Nrishinghananda Roy

Shipping software is straightforward until the infrastructure becomes a bottleneck. Deployments that break production. Staging environments that drift from reality. Systems that fail on a Friday night with no clear path to recovery. When reliability suffers, it becomes an expensive business problem.

I build and operate the highly reliable infrastructure that stops these problems from reaching your users.

By implementing Infrastructure as Code with Terraform and orchestrating container workloads through Kubernetes, I ensure your environments are immutable, infinitely reproducible, and capable of autonomous scaling.

This means your team ships faster and safer. I automate robust CI/CD pipelines using GitHub Actions and orchestrate GitOps workflows via ArgoCD, making deployments predictable and rollbacks instant.

I don't just string tools together. I write custom automation that eliminates manual toil, and I implement proactive observability with Prometheus and Grafana so I never have to wait for an outage to tell me something is wrong.

If your infrastructure is slowing your product cycle, or if you need a scalable cloud foundation built for absolute reliability from day one, that is exactly what I solve.

A 15x performance improvement on a live system.

At Codefy GmbH in Germany, a third-party Java microservice was adding over 3 seconds of latency to every API request. I read the codebase, understood exactly what it was doing, and rebuilt it from scratch in Rust (Axum) and PostgreSQL. Response times dropped to under 200 milliseconds under production load.

I also built automated document processing pipelines in Rust for their legal workflows, reducing significant manual effort. The harder part was understanding unfamiliar distributed systems well enough to replicate their behavior perfectly without breaking anything downstream.

Cloud Cost Optimization & Scalable AWS Environments.

At Dhiway in India, I provisioned and managed a highly available AWS infrastructure of over 60 EC2 instances utilizing Terraform. I implemented strict resource tagging and instance right-sizing to reduce monthly cloud compute expenditure by 28%.

I also deployed a centralized telemetry and log aggregation pipeline utilizing the Prometheus, Grafana, and Loki stack, configuring targeted alerting matrices that reduced resolution times for critical infrastructure incidents by over 35%.

Linux operations that kept an early platform running.

At Trustforum in France, I managed Linux servers for an early-stage community platform. I automated routine maintenance tasks, log rotation, and system backups using Bash shell scripting. The kind of work that is only noticed when it stops happening.

Most companies discover a security problem after it has already caused damage. A compromised environment, stolen credentials, a breach that nobody noticed for weeks.

I strongly believe that security must be built into infrastructure from day one, not retrofitted after an incident.

Below is a deep-dive into a sophisticated supply-chain attack I recently reverse-engineered, highlighting exactly why securing deployment pipelines and container environments is an absolute baseline requirement for modern startups.

Malware AnalysisJune 13, 2026

The Fake Interview Malware: Reverse Engineering a VS Code Exploit

A technical teardown of a developer supply chain attack. Learn how attackers use fake job interviews and VS Code tasks.json to deploy zero-c…

Read full research →

Rust Clippy

Clippy is the official Rust linter used across the entire Rust ecosystem. I contributed lints directly to the project, which required working through the compiler internals and the review process with the Rust team.

lsmdb

A persistent, crash-safe key-value storage engine built from scratch in Rust on an LSM-Tree architecture. Implements a Write-Ahead Log, Bloom Filters, LRU block cache, and a custom arena-allocated SkipList MemTable. Published on crates.io as a library and CLI binary.

I built this to understand how storage engines fail under pressure. That understanding directly informs how I reason about data tier architecture and I/O latency in production infrastructure.