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29shivam/README.md
Shivam Singh

LinkedIn LeetCode AWS Certified Chicago


I don't think a bio is convincing evidence of anything, so instead of describing myself, here's what I've actually done β€” every row below links to a real diff you can go read right now. Status is honest: merged means it shipped; under review means it's an open PR awaiting maintainer review.

πŸ” Proof, not adjectives

Security is a habit, not a checklist item merged
Root-caused and fixed a CRITICAL Spring Security CVE + 5 others in Vault-Web #267 β€” one dependency bump, six vulnerabilities closed
I finish things, not just propose them merged
Vault-Web #250 β€” chat UI stability fix
Vault-Web #244 β€” JVM/Postgres timezone bug
I can navigate and fix a codebase I don't own, at any scale under review
PR #152712 β€” race-condition fix in snapshot lifecycle retries, in the search engine behind a huge share of the internet
Comfortable across the Kafka ecosystem end-to-end merged under review
clickhouse-kafka-connect #775 β€” NPE fix when writing null into a Nullable(JSON) column, merged by ClickHouse
clickhouse-kafka-connect #790 β€” surface the failing column + types on a conversion error (DLQ/JMX, not just logs), merged by ClickHouse
kafka-ui #1904 β€” reverse-proxy OAuth bug
spring-kafka #4518 β€” the official Spring project
Distributed systems as trade-offs, not diagrams
Built system-design-tradeoffs from scratch β€” every answer is a trade-off matrix, real Spring Boot/Kafka/Redis code, and a production incident

🚧 Currently building

system-design-tradeoffs β€” most interview prep hands you a diagram and calls it the answer. This doesn't: every question is a trade-off matrix, a mock interview transcript showing the real follow-up drilling, a production incident, and buildable Spring Boot/Kafka/Redis/Postgres code behind the chosen approach.

πŸ’Ό Selected production work

  • Trade allocation engine β€” Java, Kafka, Redis, PostgreSQL β€” high-throughput pipeline processing real-time financial transactions
  • Real-time Kafka pipeline β€” AWS MSK, Flink, EKS β€” 40% throughput improvement on event-streaming infrastructure
  • Live MySQL β†’ PostgreSQL migration β€” zero downtime, zero data loss, across live production services
  • Microservices security hardening β€” Spring Boot, JWT, API Gateway β€” auth hardening across a distributed service mesh
  • Book management REST API β€” Spring Boot, PATCH-based versioning β€” clause versioning & metadata endpoints for a document assembly system

πŸ› οΈ Stack

Backend

Java Spring Boot Python Node.js

Cloud & DevOps

AWS Docker Kubernetes GitHub Actions

Data & Messaging

Apache Kafka PostgreSQL Redis MongoDB

Frontend

React

πŸ“ˆ Contribution activity

My GitHub contribution heatmap, animated

Custom-built from my live GitHub data, regenerated daily by a GitHub Action β€” not an off-the-shelf widget.


If you've got an interesting distributed-systems or backend problem, that's the fastest way to get my attention β€” LinkedIn is open.

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