Gatehold
High-demand ticket drop system — claims seats safely under concurrency, keeps group bookings atomic, and refunds cancelled events exactly once. Serverless on AWS with Lambda, DynamoDB, and Step Functions.
Software Engineer
I am passionate about building scalable, high-performance systems and continuously exploring new technologies. I enjoy solving complex technical problems, diving deep into system internals, and turning ideas into efficient, production-ready solutions.
Get in TouchHi, I’m Kareem Ashraf — a software engineer who cares about how systems behave under pressure. I dig into database internals, system performance, and distributed design so the software I ship stays fast, lean, and dependable in production. From building dynamic SQL engines and optimizing memory-heavy production workloads, to shipping queues, Graph RAG tooling, and APIs with real observability — I focus on measurable impact, not just features. I’m always looking for harder problems worth solving.
Bachelor's Degree, Computer Science
2020 — 2024 · GPA 3.57Back End Developer
Jun 2026 — Present · Remote / HybridBack End Developer
2026 — Present · Remote / HybridSoftware Engineer
Dec 2023 — Jun 2026Joined the engineering team as a backend intern, contributing to production services and learning large-scale Node.js system design.
High-demand ticket drop system — claims seats safely under concurrency, keeps group bookings atomic, and refunds cancelled events exactly once. Serverless on AWS with Lambda, DynamoDB, and Step Functions.
Graph RAG knowledge base for research papers — models papers, authors, concepts, and citations in Neo4j and exposes them to AI assistants via MCP tools.
Production NestJS API with Postgres 18, Redis cache-aside, stampede control, Docker orchestration, CI/CD, and k6 load testing.
A draft on database internals — written while learning, published as I go.
Storage, memory, and the log underneath the query
Working notes on what the database is actually doing underneath the query — storage, memory, indexes, and the log.
21 of ~40 topics written
53%
Chapters
Next: Query Execution Internals, Vacuum & Autovacuum
Notes I wrote and love to share on backends, databases, performance, and systems that hold up in production.
Follow on Hashnode
Sep 12, 2026
A deep dive into Kafka partitions, consumer groups, Avro contracts, Redis GEO, and real-time WebSocket delivery — through the lens of a ride-sharing…
Read articleA hands-on path through columnar storage, Parquet, star schemas, and DuckDB — using Formula 1 data.
Most teams get the communication layer right and the design layer completely wrong. Here's the mental model that fixes that.
An end-to-end path from SLIs and error budgets to k6, the knee of the curve, headroom, N+1, and autoscaling.
A practical guide to hot partitions: key salting, custom partitioners, and tenant tiering
Retries, idempotency, DLQs, reconciliation, and why every team ends up with the same design.
Distributed state, keys, Redis — and a decision model for all five algorithms
A field guide to job queues, pub/sub, event streaming, and event buses — sorted by what actually makes them different, not by vendor name.
How a recursive CTE turns 2M-row DISTINCT into a handful of index seeks
Git Internals and Branching Strategies: A Complete Guide
From ACID transactions to Sagas, Outbox, and CQRS — a journey through the patterns that keep distributed systems consistent
How Latency and Throughput Affect Each Other
Open to interesting backend and systems problems, collaborations, and conversations about performance, databases, and production software.