real-time
Real-time systems and processing
Quellinformationen
- Repository
- ffsshhttiikk/opencode-agents-skills
- Letzte Quellaktivität
- 28. Februar 2026 um 22:54
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 3
- Forks
- 2
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
SKILL.md wird angezeigt
SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- real-time
- description
- Real-time systems and processing
- license
- MIT
- metadata
- {"audience":"developers","category":"software-development"}
## What I do
- Build real-time data pipelines
- Implement WebSocket communication
- Design streaming architectures
- Handle time-sensitive processing
- Manage event-driven systems
- Optimize latency requirements
## When to use me
When building applications requiring immediate data processing, live updates, or time-critical operations.
## Key Concepts
### Real-Time Classifications
```
Hard Real-Time: Missed deadline = failure
Firm Real-Time: Missed deadline = degraded quality
Soft Real-Time: Missed deadline = performance drop
```
### WebSocket Implementation
```javascript
// Server
const wss = new WebSocket.Server({ port: 8080 });
wss.on('connection', ws => {
ws.on('message', message => {
broadcast(message);
});
});
// Client
const ws = new WebSocket('ws://localhost:8080');
ws.onmessage = (event) => {
updateUI(JSON.parse(event.data));
};
```
### Streaming Architectures
```python
# Apache Kafka + Spark Streaming
from pyspark.streaming import StreamingContext
ssc = StreamingContext(sc, 1)
kafka_stream = KafkaUtils.createDirectStream(
ssc, ['topic'], {'bootstrap.servers': 'localhost:9092'}
)
```
### Latency Optimization
```
Target latencies:
- Hard real-time: < 1ms
- Trading systems: < 10ms
- Gaming: < 50ms
- Web updates: < 100ms
```
### Event-Driven Patterns
```javascript
// Event sourcing
const store = createStore((state, event) => {
switch (event.type) {
case 'USER_UPDATED':
return { ...state, user: event.data };
}
});
// CQRS pattern
Command: writeModel.execute(command)
Query: readModel.query(query)
```
### Technologies
- WebSockets, SSE
- Apache Kafka, RabbitMQ
- Redis Pub/Sub
- gRPC streaming
- WebRTC
- Edge computing
### Monitoring
```python
# Latency tracking
from prometheus_client import Histogram
request_latency = Histogram('request_latency_seconds')
```
Auf GitHub ansehen