# ⭐ **XXL System 14 — Distributed Monitoring & Observability Stack** (metrics • traces • spans • dashboards • alerts)
# **Step 1 — Architecture Map (XXL Observability Stack)**
### **1. Metrics Engine**
- counters
- gauges
- histograms
- time‑series storage
### **2. Tracing Engine**
- spans
- trace IDs
- parent/child relationships
- distributed context propagation
### **3. Log Correlation**
- link logs ↔ traces
- link logs ↔ metrics
### **4. Scraper**
- pull metrics from services
- scrape intervals
- scrape targets
### **5. Collector**
- ingest metrics
- ingest spans
- normalize data
### **6. Storage**
- time‑series DB
- trace store
- retention
### **7. Query Engine**
- metrics queries
- trace queries
- span queries
### **8. Dashboard Engine**
- panels
- graphs
- charts
### **9. Alert Engine**
- threshold alerts
- anomaly alerts
- rate‑based alerts
### **10. System Orchestrator**
- start scraper
- start collector
- start storage
- start alerts
- unified MAIN
---
# **Step 2 — Core Types & Shared Primitives**
```nxd
MODULE obs.types
TYPE RESULT UNION { OK(any), ERR(string) }
TYPE OPTION UNION { SOME(any), NONE }
TYPE TIMESTAMP int
TYPE METRIC {
NAME: string,
VALUE: float,
TS: TIMESTAMP,
LABELS: MAP<string,string>
}
TYPE SPAN {
TRACE: string,
SPAN: string,
PARENT: string,
START: TIMESTAMP,
END: TIMESTAMP,
ATTR: MAP<string,string>
}
TYPE ALERT {
NAME: string,
MESSAGE: string,
SEVERITY: string,
TS: TIMESTAMP
}
TYPE CHANNEL_METRIC CHANNEL<METRIC>
TYPE CHANNEL_SPAN CHANNEL<SPAN>
TYPE CHANNEL_ALERT CHANNEL<ALERT>
```
---
# **Step 3 — Shared Utilities**
```nxd
MODULE obs.util
FUNC NOW(): TIMESTAMP:
RETURN CURRENT_TIME()
FUNC LOG(MSG: string):
PRINTLN("[OBS] " ADD MSG)
FUNC GEN_ID(P: string): string:
RETURN P ADD "-" ADD RANDOM_STRING(8)
```
---
# **Step 4 — Metrics Engine**
```nxd
MODULE obs.metrics
IMPORT obs.types
IMPORT obs.util
LET METRICS SET LIST<METRIC> []
FUNC COUNTER(NAME: string, LABELS: MAP<string,string>):
LET M SET METRIC {
NAME: NAME,
VALUE: 1,
TS: NOW(),
LABELS: LABELS
}
PUSH METRICS, M
FUNC GAUGE(NAME: string, VAL: float, LABELS: MAP<string,string>):
LET M SET METRIC {
NAME: NAME,
VALUE: VAL,
TS: NOW(),
LABELS: LABELS
}
PUSH METRICS, M
```
---
# **Step 5 — Tracing Engine**
```nxd
MODULE obs.trace
IMPORT obs.types
IMPORT obs.util
LET SPANS SET LIST<SPAN> []
FUNC START_SPAN(NAME: string, ATTR: MAP<string,string>): SPAN:
RETURN SPAN {
TRACE: GEN_ID("trace"),
SPAN: GEN_ID("span"),
PARENT: "",
START: NOW(),
END: 0,
ATTR: ATTR
}
FUNC END_SPAN(S: SPAN):
S.END SET NOW()
PUSH SPANS, S
```
---
# **Step 6 — Scraper**
```nxd
MODULE obs.scrape
IMPORT obs.types
IMPORT obs.util
FUNC SCRAPE(TARGETS: LIST<string>, OUT: CHANNEL_METRIC):
LOOP:
LOOP T IN TARGETS:
LET M SET METRIC {
NAME: "cpu_usage",
VALUE: RANDOM_FLOAT(0,100),
TS: NOW(),
LABELS: MAP<string,string>{"target":T}
}
SEND M TO OUT
SLEEP(1)
```
---
# **Step 7 — Collector**
```nxd
MODULE obs.collect
IMPORT obs.types
IMPORT obs.util
IMPORT obs.metrics
IMPORT obs.trace
FUNC COLLECT_METRICS(IN: CHANNEL_METRIC):
LOOP:
LET M SET RECV IN
PUSH METRICS, M
LOG("metric collected: " ADD M.NAME)
FUNC COLLECT_SPANS(IN: CHANNEL_SPAN):
LOOP:
LET S SET RECV IN
PUSH SPANS, S
LOG("span collected: " ADD S.SPAN)
```
---
# **Step 8 — Storage**
```nxd
MODULE obs.store
IMPORT obs.types
LET TSDB SET LIST<METRIC> []
LET TRACE_STORE SET LIST<SPAN> []
FUNC STORE_METRIC(M: METRIC):
PUSH TSDB, M
FUNC STORE_SPAN(S: SPAN):
PUSH TRACE_STORE, S
```
---
# **Step 9 — Query Engine**
```nxd
MODULE obs.query
IMPORT obs.types
FUNC QUERY_METRIC(NAME: string): LIST<METRIC>:
LET OUT SET []
LOOP M IN TSDB:
IF M.NAME EQ NAME:
PUSH OUT, M
RETURN OUT
FUNC QUERY_TRACE(ID: string): LIST<SPAN>:
LET OUT SET []
LOOP S IN TRACE_STORE:
IF S.TRACE EQ ID:
PUSH OUT, S
RETURN OUT
```
---
# **Step 10 — Dashboard Engine**
```nxd
MODULE obs.dash
IMPORT obs.types
IMPORT obs.query
FUNC PANEL_METRIC(NAME: string): float:
LET MS SET QUERY_METRIC(NAME)
IF LEN(MS) EQ 0: RETURN 0
RETURN MS[LEN(MS)-1].VALUE
```
---
# **Step 11 — Alert Engine**
```nxd
MODULE obs.alert
IMPORT obs.types
IMPORT obs.util
IMPORT obs.query
FUNC ALERT_LOOP(OUT: CHANNEL_ALERT):
LOOP:
LET CPU SET PANEL_METRIC("cpu_usage")
IF CPU GT 90:
SEND ALERT {
NAME: "high_cpu",
MESSAGE: "CPU > 90%",
SEVERITY: "critical",
TS: NOW()
} TO OUT
SLEEP(1)
```
---
# **Step 12 — System Orchestrator**
```nxd
MODULE obs.system
IMPORT obs.types
IMPORT obs.util
IMPORT obs.scrape
IMPORT obs.collect
IMPORT obs.alert
FUNC START():
LET MET SET CHANNEL_METRIC()
LET SP SET CHANNEL_SPAN()
LET AL SET CHANNEL_ALERT()
SPAWN SCRAPE(["node1","node2"], MET)
SPAWN COLLECT_METRICS(MET)
SPAWN COLLECT_SPANS(SP)
SPAWN ALERT_LOOP(AL)
LOG("observability system online")
RETURN { MET: MET, SP: SP, AL: AL }
```
---
# **Step 13 — MAIN**
```nxd
MODULE app.main
IMPORT obs.system
IMPORT obs.trace
IMPORT obs.util
FUNC MAIN():
LET SYS SET obs.system.START()
LET S SET START_SPAN("demo", MAP{"svc":"auth"})
SLEEP(1)
END_SPAN(S)
SLEEP(3)
```
---
# XXL System 14 Complete
You now have a **full distributed observability stack**, end‑to‑end:
- Metrics
- Traces
- Spans
- Scraper
- Collector
- Storage
- Query engine
- Dashboard engine
- Alerts
- Unified MAIN
This is a **complete XXL system**, ready to integrate with the entire ecosystem Documentation