A high-frequency, non-blocking telemetry engine designed to monitor multi-tenant resource saturation, loop latency, and connection bandwidth consumption across clustered environments. This module streams real-time system performance insights directly into the CoCreate self-healing autoscaler ecosystem.
For full API references, custom performance metrics, and dashboard ingestion guides, refer to the CoCreate Server Telemetry Documentation.
- Low-Overhead High-Frequency Telemetry Engine
- Why CoCreate Server Telemetry?
- The Metric Profile Plane
- The Saturation Index Calculation
- Non-Blocking Multi-Threaded Streaming
- Configuration
- Installation
- Announcements
- Roadmap
- How to Contribute
- About
Monitoring real-time systems often introduces an instrumentation tax—where the observer itself degrades performance. @cocreate/server-telemetry is engineered using low-level, asynchronous polling loops to monitor internal runtime state with near-zero overhead.
Instead of tracking abstract hypervisor data, this module monitors actual V8 thread starvation by measuring scheduling delay intervals. A precision timer schedules microtask check-ins; deviations reveal when application code is blocking the single thread.
To prevent triggering V8 Garbage Collection (GC) pauses during intense data collection, all raw telemetry samples are held in pre-allocated, fixed-size typed array ring buffers in memory, ensuring consistent application execution.
[Metrics Gatherer] ──► [Pre-Allocated Ring Buffer] ──► [Asynchronous Flush] ──► [Autoscaler Engine]
(Zero GC Overhead)
Standard infrastructure monitoring agents (like Datadog or Prometheus Node Exporter) sample system states at coarse 10 to 60-second intervals and look at machines globally. They completely miss the short, critical spikes that degrade real-time WebSocket experiences—like a single tenant executing a complex query that triggers a 500ms event loop freeze.
@cocreate/server-telemetry isolates metrics down to the individual Organization ID and Socket Connection Instance. It calculates instant health profiles at sub-second intervals, giving the @cocreate/server-autoscaler the granular insight required to gracefully shed or migrate specific tenant workloads before users experience lag.
The telemetry engine continually samples four primary dimensions across the cluster:
| Metric Group | Collection Method | Key Use Case |
|---|---|---|
| V8 Event Loop Lag | Asynchronous Microtask Polling | Detects thread starvation caused by heavy computation or synchronous execution blockages. |
| Memory Profiles | process.memoryUsage.rss() |
Tracks memory growth and leaks within individual worker instances. |
| Socket Density | Active Session Tracking | Measures connection volumes to protect memory limits. |
| Bandwidth Deltas | Network Interface Stream Counters | Monitors tenant-isolated data rates to identify runaway processes or DDoS vectors. |
The absolute core of the CoCreate self-healing cluster is the Saturation Index (
Where the weight constants are tuned by default to prioritize thread fluidity:
-
$\alpha = 0.50$ (Event Loop Fluctuations) -
$\beta = 0.30$ (Memory Saturation) -
$\gamma = 0.20$ (Connection Density)
When
Telemetry data shouldn't compete with application throughput. When configured to stream metrics to a central database or external timeseries sink, @cocreate/server-telemetry offloads data serialization work entirely.
Using Node.js worker_threads, the main application thread offloads raw data arrays to a background thread using zero-copy ArrayBuffer transfers. The background worker serializes and ships the metric payload asynchronously, leaving the primary thread free to process WebSocket packets uninterrupted.
Drop a telemetry.config.json into your server root directory to manage monitoring frequencies and aggregation targets.
{
"samplingIntervalMs": 500,
"flushIntervalMs": 5000,
"retentionPeriodHours": 24,
"limits": {
"maxAllowedV8LagMs": 100,
"highMemoryThresholdPercent": 85
},
"streaming": {
"enabled": true,
"useWorkerThread": true,
"target": "cluster-registry"
}
}npm i @cocreate/server-telemetryyarn add @cocreate/server-telemetryPerformance improvements, kernel tracing updates, and profiling modifications are documented on the CoCreate Server Telemetry GitHub Releases page. Subscribe to stay informed about optimization releases and new features.
Upcoming capabilities for our monitoring plane include:
- eBPF Network Inspections: Low-overhead, kernel-level packet inspection to isolate network throughput anomalies down to precise system sockets.
- GC Execution Visualizer: Deep tracing hooks that flag exactly which tenant code block caused V8 mark-and-sweep garbage collection freezes.
We welcome pull requests targeting performance profiling, adapter additions, and bug fixes. Please read our CONTRIBUTING.md guide for local development workflows.
If you encounter any bugs or wish to request new features, please submit an issue on our GitHub Issues tracker. We want this library to be community-driven, and CoCreate-led. We need your help to shape its future.
For broader system configurations and API guides, please visit our CoCreate Server Telemetry Documentation.
@cocreate/server-telemetry is designed, built, and supported by the CoCreate Developer Experience Team.
Note
For questions regarding telemetry pipelines, custom metric adapters, or deployment profiling, please visit our GitHub Discussions or join our Discord community.
@cocreate/server-telemetry is maintained and funded by CoCreate. The names and logos for CoCreate are trademarks of CoCreate, LLC.