Category: Кто я
Личная ОС + творческое портфолио
Самостоятельно собранная «личная операционная система»: планер, трекер, 3D-граф знаний — и витрина-портфолио как публичное лицо. Всё self-hosted, приватное ядро под /login.
Tags: personal-os, self-hosted, портфолио
Yaroslav Vlasov|Software engineer|Personal OS and portfolio
The interactive 3D scene did not start: this browser has no WebGL, or JavaScript is turned off. Everything it shows is below as text — who I am, what I build, selected work and contacts.
Yaroslav Vlasov — Software engineer. Saint Petersburg State University · Faculty of Mathematics and Computer Science · Modern Software Engineering, year 2. Saint Petersburg.
I build systems end to end — from the database schema and the deployment to the shaders. The site you are scrolling right now is the proof: every line of it is mine, from docker-compose to the last line of GLSL.
A personal OS on my own server: planner, exam mode, knowledge graph, tree of goals.
Next.js 16, PostgreSQL, Docker
Works out whether you will make your deadlines, and says plainly what to move.
TypeScript, algorithms, tests
A renderer for knowledge on bare R3F — the same one that drew this page.
three.js, WebGL, shaders
Built: Next.js 16 + PostgreSQL + Docker Compose + Caddy with automatic HTTPS, layered data access (zod → repository → service).
Learned: Defence in depth: a proxy redirect is UX, not a security boundary; the real check is the first line of every server action.
Built: pg_dump → gzip → gpg in a single pipeline, with no plaintext ever touching the disk; optional off-site upload of the encrypted dump.
Learned: A backup without a tested restore is not a backup. And one intermediate file on disk undoes all of the encryption.
Built: A priority engine and an EDF scheduler: it works out whether the deadlines are reachable and names what has to move. All of it under tests.
Learned: An algorithm is worth exactly as much as it is trusted. So the scheduler does not just hand over a plan — it explains why a task ended up on top.
Built: A timer and real minutes tracking; size estimates adjust to how the work actually goes.
Learned: Feeding reality back into the model is the cheapest way to make a system more accurate without adding a single new form.
Built: A 0–5 mastery model on top of the subject catalogue, separate calculation engines, import of a preparation plan.
Learned: A mastery scale beats a “learned it” checkbox: it shows where you actually are, and where to go next.
Built: The knowledge graph as a projection layer over the data; the Tree of Goals in separate tables, with AES-256-GCM encryption of its contents.
Learned: Secrecy holds better in architecture than in a filter: the private zone is simply never imported by the public one, and a guard test keeps it that way.
Built: A whitelisted snapshot of the graph for the outside world, plus a separate showcase editor: draft, publish as a snapshot, roll back.
Learned: Splitting “draft” from “published” costs one table and removes the one real fear — showing something by accident.
Built: This scroll experience on bare React Three Fiber: a crystal skull, a knowledge graph inside the brain, a descent along the skeleton, custom dust and nebula shaders.
Learned: In 3D almost every visible defect is not a wrong parameter but a wrong model. The jittery dust was not fixed by tuning — it was fixed by simulating velocities.