feat(visualizer): add runtime architecture diagram

This commit is contained in:
u1
2026-03-13 22:33:28 +01:00
parent 5a9d61d674
commit a674d40453
12 changed files with 4953 additions and 76 deletions

View File

@@ -0,0 +1,12 @@
<!doctype html>
<html lang="pl">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Trade system diagram</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/diagram-main.tsx"></script>
</body>
</html>

View File

@@ -6,6 +6,7 @@
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@@ -1253,6 +1327,11 @@
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View File

@@ -8,6 +8,7 @@
"preview": "vite preview"
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View File

@@ -0,0 +1,11 @@
import React from 'react';
import ReactDOM from 'react-dom/client';
import '@xyflow/react/dist/style.css';
import './diagram.css';
import { TradeSystemFlowPage } from './diagram/TradeSystemFlowPage';
ReactDOM.createRoot(document.getElementById('root')!).render(
<React.StrictMode>
<TradeSystemFlowPage />
</React.StrictMode>
);

View File

@@ -0,0 +1,535 @@
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align-items: center;
border-radius: 999px;
padding: 5px 8px;
font-size: 11px;
font-weight: 800;
white-space: nowrap;
}
.rfStatus.isOk {
background: rgba(30, 107, 67, 0.11);
color: #185f39;
}
.rfStatus.isWarn {
background: rgba(176, 79, 53, 0.11);
color: #8b3d24;
}
.rfHandle {
width: 10px;
height: 10px;
background: var(--lane-color);
border: 2px solid #fff;
}
.rfHandle.isRouteHandle {
width: 12px;
height: 12px;
border: 2px solid rgba(255, 253, 249, 0.98);
box-shadow: 0 0 0 2px rgba(27, 23, 20, 0.08);
}
.rfZone {
width: 100%;
height: 100%;
border-radius: 26px;
border: 1px solid rgba(110, 101, 91, 0.14);
padding: 12px 14px;
}
.rfZone__title {
display: inline-flex;
align-items: center;
min-height: 28px;
padding: 0 10px;
border-radius: 999px;
background: rgba(255, 251, 244, 0.96);
box-shadow: 0 6px 16px rgba(27, 23, 20, 0.06);
font-size: 0.96rem;
font-weight: 900;
color: var(--rf-ink);
font-family: 'IBM Plex Serif', Georgia, serif;
}
.rfZone__subtitle {
margin-top: 6px;
max-width: 250px;
font-size: 10px;
font-weight: 700;
letter-spacing: 0.06em;
text-transform: uppercase;
color: var(--rf-muted);
line-height: 1.35;
}
.rfZone.is-host {
background:
linear-gradient(180deg, rgba(255, 253, 249, 0.92), rgba(244, 236, 225, 0.66));
box-shadow: inset 0 0 0 1px rgba(255, 255, 255, 0.35);
}
.rfZone.is-namespace {
background:
linear-gradient(180deg, rgba(255, 251, 246, 0.78), rgba(236, 228, 214, 0.52));
border-style: dashed;
border-color: rgba(98, 91, 82, 0.22);
box-shadow: inset 0 0 0 1px rgba(255, 255, 255, 0.22);
}
.rfZone.is-subzone {
background:
linear-gradient(180deg, rgba(255, 254, 250, 0.72), rgba(248, 242, 233, 0.46));
border-color: rgba(98, 91, 82, 0.12);
box-shadow: inset 0 0 0 1px rgba(255, 255, 255, 0.16);
}
.react-flow__renderer {
background:
linear-gradient(rgba(225, 214, 198, 0.22) 1px, transparent 1px),
linear-gradient(90deg, rgba(225, 214, 198, 0.22) 1px, transparent 1px),
linear-gradient(180deg, #fffdf8 0%, #faf4ea 100%);
background-size: 26px 26px, 26px 26px, 100% 100%;
}
.react-flow__nodes {
z-index: 10;
}
.react-flow__edges,
.react-flow__edgelabel-renderer {
z-index: 30 !important;
}
.react-flow__attribution {
display: none;
}
.react-flow__controls,
.react-flow__minimap {
border: 1px solid rgba(99, 91, 82, 0.14);
border-radius: 14px;
overflow: hidden;
box-shadow: 0 12px 24px rgba(27, 23, 20, 0.08);
}
.react-flow__controls button {
background: rgba(255, 252, 246, 0.92);
color: var(--rf-ink);
border-bottom-color: rgba(99, 91, 82, 0.12);
}
.react-flow__edge-text {
font-weight: 700;
}
.rfPage.isUltraWide .rfLayout {
grid-template-columns: minmax(0, 1.4fr) 300px;
}
.rfPage.isUltraWide .rfCanvas {
height: calc(100vh - 118px);
min-height: 820px;
}
code {
font-family: 'IBM Plex Mono', monospace;
background: rgba(27, 23, 20, 0.05);
padding: 2px 6px;
border-radius: 6px;
}
@media (max-width: 1180px) {
.rfPage {
padding: 14px;
}
.rfToolbar {
grid-template-columns: 1fr;
align-items: stretch;
}
.rfToolbar__meta {
justify-content: flex-start;
flex-wrap: wrap;
}
.rfLayout {
grid-template-columns: 1fr;
}
.rfCanvas {
height: 72vh;
min-height: 620px;
}
}

File diff suppressed because it is too large Load Diff

View File

@@ -1,7 +1,7 @@
import fs from 'node:fs';
import path from 'node:path';
import { fileURLToPath } from 'node:url';
import { defineConfig } from 'vite';
import { defineConfig, loadEnv } from 'vite';
import react from '@vitejs/plugin-react';
const DIR = path.dirname(fileURLToPath(import.meta.url));
@@ -14,8 +14,8 @@ function stripTrailingSlashes(p: string): string {
return out || '/';
}
function readApiReadToken(): string | undefined {
if (process.env.API_READ_TOKEN) return process.env.API_READ_TOKEN;
function readApiReadToken(env: Record<string, string | undefined>): string | undefined {
if (env.API_READ_TOKEN) return env.API_READ_TOKEN;
const p = path.join(ROOT, 'tokens', 'read.json');
if (!fs.existsSync(p)) return undefined;
try {
@@ -38,11 +38,11 @@ function parseBasicAuth(value: string | undefined): BasicAuth | undefined {
return { username, password };
}
function readProxyBasicAuth(): BasicAuth | undefined {
const fromEnv = parseBasicAuth(process.env.API_PROXY_BASIC_AUTH);
function readProxyBasicAuth(env: Record<string, string | undefined>): BasicAuth | undefined {
const fromEnv = parseBasicAuth(env.API_PROXY_BASIC_AUTH);
if (fromEnv) return fromEnv;
const fileRaw = String(process.env.API_PROXY_BASIC_AUTH_FILE || '').trim();
const fileRaw = String(env.API_PROXY_BASIC_AUTH_FILE || '').trim();
if (!fileRaw) return undefined;
const p = path.isAbsolute(fileRaw) ? fileRaw : path.join(ROOT, fileRaw);
@@ -59,10 +59,6 @@ function readProxyBasicAuth(): BasicAuth | undefined {
}
}
const apiReadToken = readApiReadToken();
const proxyBasicAuth = readProxyBasicAuth();
const apiProxyTarget = process.env.API_PROXY_TARGET || 'http://localhost:8787';
function parseUrl(v: string): URL | undefined {
try {
return new URL(v);
@@ -71,10 +67,6 @@ function parseUrl(v: string): URL | undefined {
}
}
const apiProxyTargetUrl = parseUrl(apiProxyTarget);
const apiProxyTargetPath = stripTrailingSlashes(apiProxyTargetUrl?.pathname || '/');
const apiProxyTargetEndsWithApi = apiProxyTargetPath.endsWith('/api');
function inferUiProxyTarget(apiTarget: string): string | undefined {
try {
const u = new URL(apiTarget);
@@ -91,15 +83,6 @@ function inferUiProxyTarget(apiTarget: string): string | undefined {
}
}
const uiProxyTarget =
process.env.FRONTEND_PROXY_TARGET ||
process.env.UI_PROXY_TARGET ||
process.env.AUTH_PROXY_TARGET ||
inferUiProxyTarget(apiProxyTarget) ||
(apiProxyTargetUrl && apiProxyTargetPath === '/' ? stripTrailingSlashes(apiProxyTargetUrl.toString()) : undefined);
const graphqlProxyTarget = process.env.GRAPHQL_PROXY_TARGET || process.env.HASURA_PROXY_TARGET || uiProxyTarget;
function applyProxyBasicAuth(proxyReq: any) {
if (!proxyBasicAuth) return false;
const b64 = Buffer.from(`${proxyBasicAuth.username}:${proxyBasicAuth.password}`, 'utf8').toString('base64');
@@ -119,6 +102,33 @@ function rewriteSetCookieForLocalDevHttp(proxyRes: any) {
proxyRes.headers['set-cookie'] = Array.isArray(v) ? v.map(rewrite) : rewrite(String(v));
}
export default defineConfig(({ mode }) => {
const env = { ...process.env, ...loadEnv(mode, DIR, '') } as Record<string, string | undefined>;
const apiReadToken = readApiReadToken(env);
const proxyBasicAuth = readProxyBasicAuth(env);
const apiProxyTarget = env.API_PROXY_TARGET || 'http://localhost:8787';
const apiProxyTargetUrl = parseUrl(apiProxyTarget);
const apiProxyTargetPath = stripTrailingSlashes(apiProxyTargetUrl?.pathname || '/');
const apiProxyTargetEndsWithApi = apiProxyTargetPath.endsWith('/api');
const uiProxyTarget =
env.FRONTEND_PROXY_TARGET ||
env.UI_PROXY_TARGET ||
env.AUTH_PROXY_TARGET ||
inferUiProxyTarget(apiProxyTarget) ||
(apiProxyTargetUrl && apiProxyTargetPath === '/'
? stripTrailingSlashes(apiProxyTargetUrl.toString())
: undefined);
const graphqlProxyTarget = env.GRAPHQL_PROXY_TARGET || env.HASURA_PROXY_TARGET || uiProxyTarget;
const portRaw = env.VITE_DEV_PORT || env.DEV_PORT || '5173';
const port = Number.parseInt(String(portRaw), 10);
function applyProxyBasicAuth(proxyReq: any) {
if (!proxyBasicAuth) return false;
const b64 = Buffer.from(`${proxyBasicAuth.username}:${proxyBasicAuth.password}`, 'utf8').toString('base64');
proxyReq.setHeader('Authorization', `Basic ${b64}`);
return true;
}
const proxy: Record<string, any> = {
'/api': {
target: apiProxyTarget,
@@ -168,11 +178,12 @@ if (uiProxyTarget) {
}
}
export default defineConfig({
return {
plugins: [react()],
server: {
port: 5173,
port: Number.isInteger(port) && port > 0 ? port : 5173,
strictPort: true,
proxy,
},
};
});

344
doc/data-ingest-strategy.md Normal file
View File

@@ -0,0 +1,344 @@
# Data ingest strategy
## Cel
Zachowac niski latency dla logiki tradingowej i read-side, ale rownoczesnie miec trwala persystencje danych do UI, replayu, debugowania i analityki.
Nie robimy modelu `DB-first` jako jedynej sciezki przetwarzania.
## Rekomendowany model
Stosujemy `dual-path`:
1. `hot path`
`Yellowstone gRPC / Agave RPC -> consumer -> Redis / internal state -> strategy / read-side`
2. `durable path`
`ten sam consumer -> Postgres -> UI / Hasura / replay / debug`
Opcjonalnie pozniej:
3. `history / analytics path`
`consumer lub batch exporter -> ClickHouse`
## Dlaczego nie DB-first
Model:
`gRPC / RPC -> DB -> dopiero potem przetwarzanie`
nie jest dobry jako glowna sciezka, bo:
- dodaje latency do kazdego eventu
- uzaleznia ingest od kondycji bazy
- pogarsza odpornosc calego pipeline
- zwieksza write amplification przy duzym wolumenie zdarzen
- utrudnia low-latency strategie i read-side
DB ma byc miejscem persystencji i read modelu, nie bramka przed logika runtime.
## Rola Yellowstone gRPC
Yellowstone ma byc glownym zrodlem `live feed`:
- account updates
- tx updates
- slot updates
- program updates
Sciezka:
`Yellowstone -> consumer -> hot state`
oraz rownolegle:
`Yellowstone -> normalization / persistence -> Postgres`
Yellowstone nie powinien byc uzalezniony od tego, czy Postgres aktualnie pisze szybko.
## Rola Agave RPC
RPC nie jest naturalnym feedem eventowym.
RPC powinno sluzyc glownie do:
- point reads
- bootstrapu klienta
- recovery
- getAccountInfo / getMultipleAccounts
- getHealth / getSlot
- write path dla tx, jesli nie idziemy przez TPU/Jito
RPC nie powinno byc traktowane jak glowny event stream do zrzucania wszystkiego do DB.
## Rola Redis
Redis powinien byc `hot state layer`:
- szybki stan DLOB
- cache
- fanout wewnetrzny
- ewentualnie stream / queue dla workerow
To jest warstwa pod:
- strategy engine
- orderbook read-side
- szybkie projekcje
Nie trzymamy tam historii jako source of truth.
## Rola Postgres
Postgres powinien byc `durable read model`:
- dane dla UI
- dane dla Hasury
- znormalizowane ticki
- pochodne tabele DLOB
- stan aplikacji
- konfiguracja
- historia operacyjna
Postgres jest dobry do:
- frontend
- dashboard
- replay lekkiego zakresu
- audyt aplikacyjny
## Kiedy ClickHouse
ClickHouse dodajemy dopiero, gdy:
- wolumen raw feedu bedzie duzy
- potrzebna bedzie ciezsza analityka historyczna
- bedziemy chcieli trzymac dluzsza historie eventow i tx
Na obecnym etapie nie jest konieczny do uruchomienia runtime.
## Docelowy przeplyw
```text
mevnode_sol
Agave RPC
Yellowstone gRPC
|
v
mevnode_bot
consumer
|\
| +--> Redis -> DLOB/read-side -> strategy/workers
|
+----> Postgres -> Hasura/API -> frontend
```
## Zasada architektoniczna
- `gRPC / RPC` dostarcza dane do runtime
- `Redis` utrzymuje szybki stan operacyjny
- `Postgres` utrzymuje trwaly stan i read model
- `frontend` i `Hasura` czytaja z Postgresa
- `strategy` i `workers` nie czekaja na zapis do DB, aby przetwarzac dane
## Rekomendacja dla projektu
Na teraz:
1. `Yellowstone -> consumer -> Redis`
2. `consumer -> Postgres`
3. `Hasura / API / UI <- Postgres`
4. `strategy / read-side <- Redis`
5. `RPC` zostawic do bootstrapu, point reads i write path
To daje najlepszy kompromis:
- niski latency
- odpornosc runtime
- sensowna persystencja
- dobra baza pod UI i replay
## Ocena obecnego ukladu na k3s
Obecny runtime na `mevnode_bot / trade-staging` jest tylko czesciowo zgodny z docelowym modelem.
### Co jest zgodne
- `postgres` jest postawiony jako `StatefulSet`, wiec nadaje sie na trwały storage
- `dlob-redis` jest osobna lekka usluga i pasuje do roli cache / hot state
- `hasura` i `trade-api` siedza nad `Postgresem`, co jest poprawne dla durable read modelu
- `frontend` korzysta z `API/Hasury`, a nie bezposrednio z `Redis`
### Co nie jest zgodne
- `dlob-publisher` i `dlob-server` nie sa zdrowe, wiec hot path nie jest operacyjnie domkniety
- `dlob-publisher` jest podpiety do `gRPC`, ale nie jest glownym i pewnym writerem do `Postgresa`
- `trade-ingestor` nie ingestuje danych bezposrednio z chain source, tylko polluje dane pochodne z `Hasury`
- persistent path jest wiec dzisiaj czesciowo odwrocony:
- `derived view -> ingest -> Postgres`
- zamiast:
- `chain source -> normalize -> Postgres`
## Plan zmian
### Cel koncowy
Chcemy dojsc do ukladu:
```text
Yellowstone gRPC / Agave RPC
|
v
consumer
|\
| +--> Redis -> hot state / workers / strategy
|
+----> Postgres -> Hasura / API / frontend / replay
```
### Etap 1. Naprawa hot path
Najpierw trzeba przywrocic dzialanie:
- `dlob-publisher`
- `dlob-server`
Bez zdrowego publishera nie ma sensu budowac dalszej warstwy `Redis = hot state`.
Zakres:
- ustabilizowac `Agave RPC` i `Yellowstone`
- doprowadzic `dlob-publisher` do `Ready`
- potwierdzic, ze `Redis` dostaje aktualny stan
- doprowadzic `dlob-server` do `Ready`
### Etap 2. Uczynic publisher glownym consumerem danych chain
Obecnie `trade-ingestor` korzysta z danych pochodnych z `Hasury`.
To trzeba zmienic tak, aby glownym miejscem wejscia danych byl komponent konsumujacy:
- `Yellowstone gRPC`
- `Agave RPC`
Rekomendacja:
- rozszerzyc `dlob-publisher`
- albo wydzielic nowy `market-consumer`
ale w obu przypadkach komponent ma robic:
- odczyt live z `Yellowstone`
- wymagane point reads z `RPC`
- normalizacje danych
- jednoczesny zapis do `Redis` i `Postgresa`
### Etap 3. Ustalic twardy podzial rol Redis / Postgres
#### Redis
Do `Redis` trafia tylko to, co potrzebne jako szybki stan runtime:
- latest DLOB state
- latest L2
- quick cache dla workerow
- fanout do read-side i strategii
- dane z TTL lub dane odtwarzalne
`Redis` nie jest source of truth.
#### Postgres
Do `Postgresa` trafia trwaly model danych:
- znormalizowane ticki
- znormalizowane snapshoty rynku
- pochodne tabele pod `Hasure`
- historia operacyjna
- stan aplikacji
`Postgres` jest source of truth dla aplikacji i UI.
### Etap 4. Przebudowac worker path
Docelowy model dla workerow:
- `Redis in`
- `Postgres out`
To znaczy:
- workery czytaja szybki stan z `Redis`
- licza projekcje
- zapisują wynik do `Postgresa`
Dotyczy to szczegolnie:
- `dlob-worker`
- `dlob-depth-worker`
- `dlob-slippage-worker`
### Etap 5. Wygasic obecny odwrocony ingest
Obecny `trade-ingestor` zapisuje dane do `Postgresa` na podstawie danych juz pochodnych z `Hasury`.
To nie powinno byc glowna sciezka ingestu.
Mozliwe role po zmianie:
- backfill
- sanity check
- fallback
- testowy importer
Ale nie:
- glowny chain ingest
### Etap 6. Utrwalic read model pod UI
Po zmianach:
- `Hasura` czyta tylko z `Postgresa`
- `trade-api` czyta tylko z `Postgresa`
- `frontend` czyta przez `API/Hasure`
Frontend nie powinien zalezec od `Redis`.
### Etap 7. Zostawic RPC w waskiej roli
`Agave RPC` zostawiamy do:
- bootstrapu
- point reads
- recovery
- write path dla tx
Nie robimy z `RPC` glownej magistrali trwałego ingestu.
## Plan wdrozenia krok po kroku
1. Naprawic `dlob-publisher` i `dlob-server`.
2. Potwierdzic, ze `Redis` jest zasilany poprawnym hot state.
3. Rozszerzyc publisher albo dodac nowy consumer tak, aby pisal rownolegle do:
- `Redis`
- `Postgresa`
4. Zdefiniowac schemat tabel normalized data w `Postgresie`.
5. Przepiac workery na model:
- read z `Redis`
- write do `Postgresa`
6. Zostawic `Hasure` i `trade-api` jako warstwe odczytowa nad `Postgresem`.
7. Zdegradowac `trade-ingestor` z roli glownego ingestu do roli pomocniczej albo go usunac z glownej sciezki.
## Rekomendacja praktyczna
Najmniejsza sensowna zmiana to nie budowac od razu nowego systemu od zera, tylko:
1. naprawic obecny `dlob-publisher`
2. dodac mu zapis do `Postgresa`
3. stopniowo wyprowadzac `trade-ingestor` z glownego path
To jest najmniej ryzykowna droga do modelu:
- `Redis = cache / hot state`
- `Postgres = persistent normalized store`

View File

@@ -0,0 +1,245 @@
# Mevnode Bot Architecture
## Zasada glowna
`mevnode_bot` nigdy nie uruchamia warstwy Solana node:
- bez `agave`
- bez `ledger`
- bez `yellowstone server`
- bez validator stack
`mevnode_sol` pozostaje jedynym hostem node-level:
- `agave-validator`
- `yellowstone geyser plugin`
- `yellowstone gRPC`
- plugin metrics
- lokalny RPC
- opcjonalnie pozniej RPC proxy
## Schemat `mevnode_bot`
```text
+--------------------------------------------------------------+
| mevnode_bot |
| single-node k3s only |
| |
| ingress/web |
| - frontend |
| - api |
| |
| trading/read |
| - yellowstone-consumer |
| - market ingest / parser |
| - dlob-worker |
| |
| trading/core |
| - strategy-engine |
| - risk-manager |
| - order-manager |
| - tx-router |
| |
| tx paths |
| - tpu client |
| - jito client |
| - rpc client / later rpc proxy target on mevnode_sol |
| |
| data |
| - postgres |
| - redis optional |
| - clickhouse later optional |
| |
| ops |
| - prometheus |
| - grafana |
| - loki optional |
| |
| platform |
| - argo/flux |
| - sealed-secrets or sops |
| - internal registry access |
+--------------------------------------------------------------+
```
## Przeplyw danych
```text
Yellowstone on mevnode_sol
|
v
yellowstone-consumer
|
v
parser / ingest / dlob-worker
|
v
strategy-engine
|
v
risk-manager / order-manager
|
v
tx-router
| | |
v v v
TPU Jito RPC
```
## Namespace plan
- `web`
- `trade`
- `data`
- `ops`
- `infra`
## Kolejnosc wdrozenia
1. `web`: `frontend`, `api`
2. `data`: `postgres`
3. `trade`: `yellowstone-consumer`
4. `trade`: `strategy-engine`, `tx-router`
5. `ops`: `prometheus`, `grafana`
## Read i write path
Read path:
- `mevnode_bot -> wg0 -> mevnode_sol:10000`
Metrics path:
- `mevnode_bot -> wg0 -> mevnode_sol:8999`
Write path pozniej:
- `mevnode_bot -> TPU/Jito`
- albo `mevnode_bot -> RPC proxy -> mevnode_sol:127.0.0.1:8899`
## Zasada architektoniczna
- `mevnode_sol` = source of truth dla chain access
- `mevnode_bot` = execution and product node
## K3s object map
### Namespace `web`
- `Deployment` `frontend`
- `Service` `frontend` typu `ClusterIP`
- `Deployment` `api`
- `Service` `api` typu `ClusterIP`
- `Ingress` `web`
Przeznaczenie:
- `frontend` wystawia UI
- `api` wystawia backend HTTP
- `Ingress` publikuje tylko web entrypoint
### Namespace `trade`
- `Deployment` `yellowstone-consumer`
- `Deployment` `dlob-worker`
- `Deployment` `strategy-engine`
- `Deployment` `risk-manager`
- `Deployment` `order-manager`
- `Deployment` `tx-router`
- `Service` `strategy-engine` typu `ClusterIP` jesli inne komponenty maja sie do niego odwolywac
- `Service` `tx-router` typu `ClusterIP` tylko jesli potrzebne bedzie sterowanie po HTTP/gRPC
Przeznaczenie:
- `yellowstone-consumer` czyta stream z `mevnode_sol`
- `dlob-worker` robi ingest i przygotowanie danych
- `strategy-engine` podejmuje decyzje
- `risk-manager` egzekwuje limity
- `order-manager` sklada i nadzoruje lifecycle zlecen
- `tx-router` wybiera `TPU`, `Jito` albo `RPC`
Uwagi:
- `strategy-engine`, `order-manager` i `tx-router` mozna uruchamiac z `hostNetwork: true`, jesli bedzie potrzeba minimalizacji narzutu sieciowego
- `yellowstone-consumer` powinien miec `Secret` z `x-token` i endpointem `10.91.0.1:10000`
### Namespace `data`
- `StatefulSet` `postgres`
- `Service` `postgres` typu `ClusterIP`
- `PersistentVolumeClaim` dla `postgres`
- `StatefulSet` `redis` opcjonalnie
- `Service` `redis` typu `ClusterIP`
- `PersistentVolumeClaim` dla `redis` tylko jesli ma byc trwaly cache
- `StatefulSet` `clickhouse` dopiero pozniej
- `Service` `clickhouse` typu `ClusterIP`
- `PersistentVolumeClaim` dla `clickhouse`
Przeznaczenie:
- `postgres` dla stanu systemu, pozycji, filli, konfiguracji i jobow
- `redis` dla cache, kolejek, lockow i rate limitu
- `clickhouse` dla ciezszej analityki i archiwizacji eventow
### Namespace `ops`
- `StatefulSet` `prometheus`
- `Service` `prometheus` typu `ClusterIP`
- `Deployment` `grafana`
- `Service` `grafana` typu `ClusterIP`
- `Deployment` `promtail` opcjonalnie
- `StatefulSet` albo `Deployment` `loki` opcjonalnie
Przeznaczenie:
- `prometheus` zbiera metryki z `k3s` i z aplikacji
- `grafana` daje dashboardy
- `loki/promtail` sa opcjonalne do logow
### Namespace `infra`
- `Deployment` `argocd-server` albo kontrolery `flux`
- `Deployment` `argocd-repo-server` jesli wybierzemy `Argo CD`
- `Deployment` `sealed-secrets-controller` albo integracja `sops`
- `Secret` / `ExternalSecret` dla tokenow i kluczy
Przeznaczenie:
- GitOps sync z Gitea
- zarzadzanie sekretami
- bootstrap aplikacji i manifestow
## Service exposure rules
- tylko `frontend` i `api` wychodza przez `Ingress`
- `postgres`, `redis`, `clickhouse`, `strategy-engine`, `tx-router` zostaja wewnetrzne jako `ClusterIP`
- bez `LoadBalancer`
- bez publicznego wystawiania komponentow tradingowych
- `yellowstone-consumer` nie potrzebuje publicznego `Service`
## Storage rules
- `postgres` na trwałym wolumenie
- `clickhouse` tylko na szybkim lokalnym storage
- `redis` bez PVC jesli ma byc tylko cache
- aplikacje tradingowe jako stateless `Deployment`, jesli stan trzymamy w `postgres`
## Config and secrets
- `ConfigMap` dla endpointow, feature flags i runtime config
- `Secret` dla:
- tokenu Yellowstone
- kluczy API
- danych do `postgres`
- danych do `Jito`
- kluczy signing/delegate
## Kolejnosc wdrozenia w k3s
1. `infra`: GitOps i secrets
2. `data`: `postgres`
3. `web`: `frontend`, `api`, `Ingress`
4. `trade`: `yellowstone-consumer`
5. `trade`: `strategy-engine`, `risk-manager`, `order-manager`
6. `trade`: `tx-router`
7. `ops`: `prometheus`, `grafana`

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<html lang="pl">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
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</head>
<body>
<div class="page">
<section class="hero">
<div class="hero-card">
<div class="eyebrow">Topology / mev stack</div>
<h1>mevnode_sol daje chain access. mevnode_bot robi produkt, ingest i execution.</h1>
<p>
Ten układ rozdziela warstwę validatora od warstwy aplikacyjnej. Na <strong>sol</strong>
trzymasz tylko Agave, Yellowstone i lokalne RPC. Na <strong>bot</strong> działa
<strong>single-node k3s</strong> z frontendem, API, DLOB, strategiami i bazami danych.
</p>
</div>
<aside class="legend">
<div class="legend-item"><span class="swatch read"></span> Read path: Yellowstone / live stream</div>
<div class="legend-item"><span class="swatch write"></span> Write path: RPC / TPU / Jito</div>
<div class="legend-item"><span class="swatch ops"></span> Ops path: monitoring, metryki, GitOps</div>
<div class="legend-item"><span class="swatch store"></span> Data path: Postgres, Redis, analityka</div>
<p>
Zasada jest prosta: <strong>na bot nie trafia nigdy Agave ani ledger</strong>.
`mevnode_bot` ma tylko klienty, logikę tradingową i interfejs użytkownika.
</p>
</aside>
</section>
<section class="diagram">
<article class="node">
<div class="node-head">
<h2>mevnode_sol</h2>
<span>bare metal / validator host</span>
</div>
<div class="stack">
<div class="box read">
<h3>Agave validator</h3>
<p>Źródło stanu chaina, snapshotów i lokalnego read/write RPC.</p>
<ul>
<li><code>127.0.0.1:8899</code> RPC</li>
<li><code>10.91.0.1:10000</code> Yellowstone gRPC</li>
<li><code>10.91.0.1:8999</code> Prometheus plugin metrics</li>
</ul>
</div>
<div class="box write">
<h3>Write capability</h3>
<p>Bot może później używać lokalnego RPC przez proxy lub iść bezpośrednio przez TPU/Jito.</p>
</div>
<div class="box ops">
<h3>Node-only responsibilities</h3>
<ul>
<li>snapshot recovery</li>
<li>accounts index</li>
<li>geyser / yellowstone plugin</li>
<li>node metrics</li>
</ul>
</div>
</div>
</article>
<div class="bridge" aria-hidden="true">
<div class="bridge-line"></div>
<div class="bridge-tag">wg0 / yellowstone / rpc / metrics</div>
<div class="bridge-line"></div>
<div class="bridge-tag">low latency read + controlled write</div>
<div class="bridge-line"></div>
</div>
<article class="node">
<div class="node-head">
<h2>mevnode_bot</h2>
<span>single-node k3s / app + execution host</span>
</div>
<div class="stack">
<div class="box read">
<h3>Read plane</h3>
<ul>
<li><strong>yellowstone-consumer</strong>: bierze live stream z <code>10.91.0.1:10000</code></li>
<li><strong>trade-ingestor</strong>: transformuje i dystrybuuje dane aplikacyjne</li>
<li><strong>dlob-publisher</strong>: dociąga stan kont przez RPC i buduje DLOB</li>
<li><strong>dlob-server</strong>: wystawia gotowy widok dla API i UI</li>
</ul>
</div>
<div class="box write">
<h3>Execution plane</h3>
<ul>
<li><strong>strategy-engine</strong>: decyzje tradingowe</li>
<li><strong>risk-manager</strong>: limity i walidacja</li>
<li><strong>order-manager</strong>: lifecycle zleceń</li>
<li><strong>tx-router</strong>: wybiera <code>RPC</code>, <code>TPU</code> albo <code>Jito</code></li>
</ul>
</div>
<div class="box store">
<h3>Data plane</h3>
<ul>
<li><strong>Postgres</strong>: trwały storage, pozycje, historia, config</li>
<li><strong>Hasura</strong>: warstwa GraphQL nad Postgres</li>
<li><strong>Redis</strong>: cache, pub/sub, szybki stan DLOB</li>
<li><strong>ClickHouse</strong>: opcjonalnie później pod cięższą analitykę</li>
</ul>
</div>
<div class="box ops">
<h3>Product and ops</h3>
<ul>
<li><strong>frontend</strong> + <strong>api</strong> + <strong>ingress</strong></li>
<li><strong>Prometheus</strong> + <strong>Grafana</strong></li>
<li><strong>Portainer agent</strong> dla widoczności klastra w Portainerze</li>
<li><strong>GitOps</strong>: Argo lub Flux z Gitea</li>
</ul>
</div>
</div>
</article>
</section>
<section class="strips">
<div class="strip">
<h3>Read path</h3>
<p>
<code>Yellowstone gRPC</code> daje live account updates, sloty i transakcje.
<code>Agave RPC</code> zostaje do odczytów punktowych typu
<code>getAccountInfo</code>, <code>getMultipleAccounts</code>,
<code>getHealth</code> i <code>getLatestBlockhash</code>.
</p>
</div>
<div class="strip">
<h3>Write path</h3>
<p>
Wysyłka transakcji nie idzie przez Yellowstone. To robi
<code>RPC</code>, <code>TPU</code> albo <code>Jito</code>.
Dzięki temu read plane i write plane są od siebie operacyjnie odseparowane.
</p>
</div>
<div class="strip">
<h3>Deployment rule</h3>
<p>
Wszystko aplikacyjne i webowe ląduje na <code>mevnode_bot</code>.
Wszystko validatorowe zostaje na <code>mevnode_sol</code>.
To upraszcza debug, upgrade i kontrolę ryzyka.
</p>
</div>
</section>
<section class="note">
<p>
Docelowy przepływ: <code>mevnode_sol -> wg0 -> yellowstone-consumer / dlob-publisher -> redis / postgres -> api -> frontend</code>.
Osobno działa execution path: <code>strategy-engine -> tx-router -> RPC / TPU / Jito</code>.
</p>
</section>
</div>
</body>
</html>

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<!doctype html>
<html lang="pl">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Trade system flow</title>
<style>
:root {
--bg: #efe7db;
--paper: rgba(255, 251, 245, 0.94);
--panel: #fffdf9;
--ink: #1c1814;
--muted: #655d53;
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--web: #2a6b8f;
--api: #0f6c72;
--data: #4e5968;
--chain: #b24a32;
--exec: #7b6110;
--ok: #1d6b43;
--warn: #914017;
--shadow: 0 18px 44px rgba(28, 24, 20, 0.10);
--radius: 18px;
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body {
margin: 0;
color: var(--ink);
font-family: "IBM Plex Sans", "Segoe UI", sans-serif;
background:
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}
.page {
max-width: 1540px;
margin: 0 auto;
padding: 28px 18px 42px;
}
.hero,
.card,
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.tabs {
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.hero {
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.eyebrow {
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font-weight: 800;
letter-spacing: 0.08em;
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h1 {
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font-size: clamp(2rem, 4vw, 3.9rem);
line-height: 0.96;
font-family: "IBM Plex Serif", Georgia, serif;
}
p {
margin: 0;
color: var(--muted);
line-height: 1.58;
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.tabs {
display: flex;
gap: 10px;
flex-wrap: wrap;
padding: 12px;
margin-bottom: 18px;
}
.tab {
border: 1px solid var(--line);
background: #fffaf2;
border-radius: 999px;
padding: 10px 14px;
font: inherit;
font-weight: 800;
cursor: pointer;
transition: 150ms ease;
}
.tab.active,
.tab:hover {
transform: translateY(-1px);
box-shadow: 0 10px 22px rgba(28, 24, 20, 0.08);
}
.tab[data-target="overview"].active { color: var(--web); }
.tab[data-target="routes"].active { color: var(--api); }
.tab[data-target="payloads"].active { color: var(--chain); }
.view { display: none; }
.view.active { display: block; }
.lanes {
display: grid;
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line-height: 1.45;
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.stack {
display: grid;
gap: 12px;
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.card {
padding: 14px;
background: var(--panel);
border-left: 6px solid var(--line);
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.card h3 {
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.meta {
font-size: 11px;
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letter-spacing: 0.08em;
color: var(--muted);
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.card.web { border-left-color: var(--web); }
.card.api { border-left-color: var(--api); }
.card.data { border-left-color: var(--data); }
.card.chain { border-left-color: var(--chain); }
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.chips {
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.chip {
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justify-content: center;
font-size: 24px;
color: var(--muted);
font-weight: 700;
}
.table-card {
padding: 14px;
overflow: auto;
}
table {
width: 100%;
border-collapse: collapse;
min-width: 980px;
}
th,
td {
padding: 12px 10px;
border-bottom: 1px solid var(--line);
text-align: left;
vertical-align: top;
line-height: 1.45;
}
th {
font-size: 12px;
text-transform: uppercase;
letter-spacing: 0.08em;
color: var(--muted);
}
code,
pre {
font-family: "IBM Plex Mono", monospace;
}
pre {
margin: 0;
white-space: pre-wrap;
word-break: break-word;
background: rgba(28, 24, 20, 0.04);
border-radius: 12px;
padding: 14px;
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.payload-grid {
display: grid;
grid-template-columns: repeat(2, 1fr);
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.note {
padding: 16px 18px;
margin-top: 18px;
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.status {
display: inline-flex;
align-items: center;
gap: 6px;
font-size: 12px;
font-weight: 800;
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.ok { color: var(--ok); background: rgba(29, 107, 67, 0.10); }
.warn { color: var(--warn); background: rgba(178, 74, 50, 0.10); }
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.lanes,
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.flow-row {
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}
.arrow {
transform: rotate(90deg);
min-height: 32px;
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table { min-width: 720px; }
}
</style>
</head>
<body>
<div class="page">
<section class="hero">
<div class="eyebrow">Trade architecture / runtime map</div>
<h1>Skąd dane trafiają, w jakiej postaci i które endpointy naprawdę wystawiamy</h1>
<p>
Ta strona opisuje faktyczny przepływ runtime dla waszej appki: <strong>browser -> frontend -> API/Hasura -> Postgres/Redis</strong>
oraz zależności od <strong>Agave RPC</strong> i <strong>Yellowstone gRPC</strong>. To nie jest ogólny diagram architektury,
tylko mapa wejść, wyjść, formatów danych i tras HTTP/WS używanych przez produkt.
</p>
</section>
<section class="tabs">
<button class="tab active" data-target="overview">Overview</button>
<button class="tab" data-target="routes">Routes / APIs</button>
<button class="tab" data-target="payloads">Payloads / shapes</button>
</section>
<section class="view active" id="overview">
<div class="lanes">
<article class="lane">
<h2>Public web surface</h2>
<small>To widzi użytkownik i to jest jedyny realny entrypoint produktu na zewnątrz.</small>
<div class="stack">
<div class="card web">
<div class="meta">NodePort / browser entry</div>
<h3>trade-frontend</h3>
<p>Serwuje SPA, obsługuje logowanie, robi proxy do API i Hasury.</p>
<div class="chips">
<span class="chip">NodePort 30081</span>
<span class="chip">service 8081</span>
<span class="chip">/api/*</span>
<span class="chip">/graphql</span>
</div>
</div>
<div class="card web">
<div class="meta">Browser calls</div>
<h3>Frontend SPA</h3>
<p>Wykres bierze REST JSON. DLOB live bierze GraphQL WebSocket. Auth idzie przez sesję cookie.</p>
<div class="chips">
<span class="chip">GET /whoami</span>
<span class="chip">POST /auth/login</span>
<span class="chip">GET /api/v1/chart</span>
<span class="chip">WS /graphql</span>
</div>
</div>
</div>
</article>
<article class="lane">
<h2>App services in k3s</h2>
<small>Wewnętrzne usługi aplikacyjne. Tylko frontend jest dziś wystawiony na zewnątrz jako NodePort.</small>
<div class="stack">
<div class="card api">
<div class="meta">ClusterIP / app logic</div>
<h3>trade-api</h3>
<p>REST backend. Zwraca candles, przyjmuje tick ingest, zarządza tokenami.</p>
<div class="chips">
<span class="chip">ClusterIP 8787</span>
<span class="chip">/v1/chart</span>
<span class="chip">/v1/ticks</span>
<span class="chip">/v1/ingest/tick</span>
</div>
</div>
<div class="card data">
<div class="meta">ClusterIP / query plane</div>
<h3>Hasura + Postgres</h3>
<p>Frontend subskrybuje Hasurę po GraphQL WS. API czyta i zapisuje przez GraphQL do Hasury.</p>
<div class="chips">
<span class="chip">Hasura 8080</span>
<span class="chip">Postgres 5432</span>
<span class="chip">GraphQL</span>
<span class="chip">subscriptions</span>
</div>
</div>
<div class="card data">
<div class="meta">Redis-backed read side</div>
<h3>DLOB stack</h3>
<p><span class="status warn">publisher 0/1</span> <span class="status warn">server 0/1</span> bo bootstrapping zależy od zdrowego Agave RPC.</p>
<div class="chips">
<span class="chip">Redis 6379</span>
<span class="chip">dlob-server 6969</span>
<span class="chip">workers</span>
</div>
</div>
</div>
</article>
<article class="lane">
<h2>Chain and execution plane</h2>
<small>To nie jest wystawiane użytkownikowi końcowemu. To feed i write side dla botów.</small>
<div class="stack">
<div class="card chain">
<div class="meta">mevnode_sol / source of truth</div>
<h3>Agave RPC</h3>
<p>Punktowe odczyty: <code>getAccountInfo</code>, <code>getMultipleAccounts</code>, <code>getSlot</code>, <code>getHealth</code>.</p>
<div class="chips">
<span class="chip">127.0.0.1:8899</span>
<span class="chip">RPC only</span>
</div>
</div>
<div class="card chain">
<div class="meta">mevnode_sol / live feed</div>
<h3>Yellowstone gRPC</h3>
<p>Pushowy stream kont, slotów i transakcji po <code>wg0</code>.</p>
<div class="chips">
<span class="chip">10.91.0.1:10000</span>
<span class="chip">token auth</span>
</div>
</div>
<div class="card exec">
<div class="meta">future execution split</div>
<h3>tx-router / TPU / Jito</h3>
<p>To jest write path. Nie mylić z Yellowstone, który jest tylko read streamem.</p>
</div>
</div>
</article>
</div>
<div class="table-card">
<div class="meta">End-to-end runtime flow</div>
<div class="flow">
<div class="flow-row">
<div class="flow-node"><strong>1. Browser</strong>Użytkownik otwiera SPA i trzyma sesję cookie.</div>
<div class="arrow"></div>
<div class="flow-node"><strong>2. trade-frontend</strong>Serwuje UI i robi reverse proxy do <code>/api</code> i <code>/graphql</code>.</div>
<div class="arrow"></div>
<div class="flow-node"><strong>3. trade-api / Hasura</strong>REST dla chartów, GraphQL WS dla live DLOB.</div>
</div>
<div class="flow-row">
<div class="flow-node"><strong>4. Postgres / Redis</strong>Trwały stan i szybki stan pośredni.</div>
<div class="arrow"></div>
<div class="flow-node"><strong>5. DLOB workers</strong>Przeliczają depth, slippage, orderbook views.</div>
<div class="arrow"></div>
<div class="flow-node"><strong>6. Agave / Yellowstone</strong>RPC do odczytów punktowych, gRPC do streamu live.</div>
</div>
</div>
</div>
<div class="note">
<p>
Najważniejszy podział: <strong>chart path = REST JSON przez trade-api</strong>, a <strong>DLOB live = GraphQL WS przez Hasurę</strong>.
To oznacza, że nie cały frontend jedzie jednym typem transportu. Produkt ma dwa równoległe read pathy.
</p>
</div>
</section>
<section class="view" id="routes">
<div class="table-card">
<table>
<thead>
<tr>
<th>Surface</th>
<th>Endpoint</th>
<th>Transport</th>
<th>Input</th>
<th>Output</th>
<th>Where it goes</th>
</tr>
</thead>
<tbody>
<tr>
<td>Frontend</td>
<td><code>GET /whoami</code></td>
<td>HTTP JSON</td>
<td>cookie session</td>
<td><code>{ ok, user, mode }</code></td>
<td>handled directly by <code>trade-frontend</code></td>
</tr>
<tr>
<td>Frontend</td>
<td><code>POST /auth/login</code></td>
<td>HTTP JSON/form</td>
<td><code>username</code>, <code>password</code></td>
<td><code>{ ok, user }</code> + session cookie</td>
<td>handled directly by <code>trade-frontend</code></td>
</tr>
<tr>
<td>Frontend</td>
<td><code>POST /auth/logout</code></td>
<td>HTTP JSON</td>
<td>session cookie</td>
<td><code>{ ok: true }</code></td>
<td>handled directly by <code>trade-frontend</code></td>
</tr>
<tr>
<td>Frontend proxy</td>
<td><code>/api/*</code></td>
<td>HTTP</td>
<td>browser request, frontend injects read token</td>
<td>proxied API response</td>
<td><code>trade-api:8787</code></td>
</tr>
<tr>
<td>Frontend proxy</td>
<td><code>/graphql</code></td>
<td>HTTP GraphQL</td>
<td>GraphQL query/mutation</td>
<td>GraphQL response</td>
<td><code>hasura:8080/v1/graphql</code></td>
</tr>
<tr>
<td>Frontend proxy</td>
<td><code>WS /graphql</code></td>
<td>GraphQL WebSocket</td>
<td>subscription payload</td>
<td>live subscription frames</td>
<td><code>hasura:8080/v1/graphql</code></td>
</tr>
<tr>
<td>API</td>
<td><code>GET /v1/chart</code></td>
<td>HTTP JSON</td>
<td><code>symbol</code>, <code>tf</code>, <code>limit</code>, optional <code>source</code></td>
<td>candles + indicators + flow rows</td>
<td>Hasura function <code>get_drift_candles</code> + table <code>drift_ticks</code></td>
</tr>
<tr>
<td>API</td>
<td><code>POST /v1/ingest/tick</code></td>
<td>HTTP JSON</td>
<td>tick payload</td>
<td><code>{ ok, id }</code></td>
<td>writes tick through Hasura into DB</td>
</tr>
<tr>
<td>API</td>
<td><code>GET /v1/ticks</code></td>
<td>HTTP JSON</td>
<td><code>symbol</code>, optional <code>source</code>, <code>limit</code>, <code>from</code>, <code>to</code></td>
<td>tick list</td>
<td>reads <code>drift_ticks</code> through Hasura</td>
</tr>
<tr>
<td>API admin</td>
<td><code>POST /v1/admin/tokens</code></td>
<td>HTTP JSON</td>
<td>name, scopes</td>
<td>new API token</td>
<td>stored in DB via Hasura</td>
</tr>
<tr>
<td>API admin</td>
<td><code>POST /v1/admin/tokens/revoke</code></td>
<td>HTTP JSON</td>
<td>token id</td>
<td>revocation status</td>
<td>updates token row in DB</td>
</tr>
<tr>
<td>Chain read</td>
<td><code>Agave RPC</code></td>
<td>JSON-RPC</td>
<td>account/state requests</td>
<td>point reads</td>
<td><code>mevnode_sol</code></td>
</tr>
<tr>
<td>Chain live</td>
<td><code>Yellowstone gRPC</code></td>
<td>gRPC streaming</td>
<td>subscription config + token</td>
<td>account/slot/tx stream</td>
<td><code>mevnode_sol</code></td>
</tr>
</tbody>
</table>
</div>
</section>
<section class="view" id="payloads">
<div class="payload-grid">
<div class="table-card">
<div class="meta">Chart response</div>
<pre>{
"ok": true,
"symbol": "SOL-PERP",
"tf": "1m",
"bucketSeconds": 60,
"candles": [
{
"time": 1710000000,
"open": 132.1,
"high": 133.2,
"low": 131.8,
"close": 132.9,
"volume": 412,
"oracle": 132.7,
"flow": { "up": 0.46, "down": 0.41, "flat": 0.13 },
"flowRows": [1, 1, 0, -1],
"flowMoves": [0.2, 0.1, 0, 0.3]
}
],
"indicators": {
"sma20": [{ "time": 1710000000, "value": 131.4 }],
"ema20": [{ "time": 1710000000, "value": 131.8 }],
"bb20": { "upper": [], "lower": [], "mid": [] },
"rsi14": [],
"macd": { "macd": [], "signal": [] }
}
}</pre>
</div>
<div class="table-card">
<div class="meta">Tick ingest body</div>
<pre>{
"ts": "2026-03-13T11:20:00.000Z",
"market_index": 0,
"symbol": "SOL-PERP",
"oracle_price": "132.70",
"mark_price": "132.91",
"oracle_slot": 406125100,
"source": "drift",
"raw": {
"provider": "internal"
}
}</pre>
</div>
<div class="table-card">
<div class="meta">GraphQL DLOB subscriptions</div>
<pre>subscription DlobStats($market: String!) {
dlob_stats_latest(where: {market_name: {_eq: $market}}, limit: 1) {
market_name
mark_price
oracle_price
best_bid_price
best_ask_price
mid_price
spread_abs
spread_bps
depth_bid_usd
depth_ask_usd
imbalance
updated_at
}
}</pre>
</div>
<div class="table-card">
<div class="meta">L2 payload shape</div>
<pre>{
"market_name": "SOL-PERP",
"bids": [
{ "price": 132910000, "size": 2500000000 }
],
"asks": [
{ "price": 132930000, "size": 1700000000 }
],
"updated_at": "2026-03-13T11:20:01.000Z"
}
Frontend przelicza to przez:
- pricePrecision = 1_000_000
- basePrecision = 1_000_000_000</pre>
</div>
</div>
<div class="note">
<p>
Krytyczne rozróżnienie: <strong>DLOB live nie idzie z REST API</strong>. DLOB do UI idzie przez <strong>Hasura GraphQL subscriptions</strong>,
a chart przez <strong>REST JSON</strong> z <code>trade-api</code>. To są dwa osobne transporty, dwa osobne modele danych i dwa osobne źródła opóźnień.
</p>
</div>
</section>
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