The Tool Desk
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Choose the right monitoring method
| Approach | Best for | What it shows | Main caveat |
|---|---|---|---|
| SRS HTTP API summaries | A quick inspection or small custom integration | SRS summary information, including CPU and memory in the documented API | Available fields depend on version and system-statistics configuration. |
| SRS Prometheus exporter | Continuously collected SRS metrics, history and alerting | Metrics scraped and retained by Prometheus; Grafana can visualize them | Confirm exporter support and settings for the installed SRS release. |
| Host exporter alongside SRS | Understanding machine-wide capacity and load | Host metrics collected by node_exporter, separately from SRS metrics |
It complements SRS monitoring; it does not replace the SRS endpoint. |
Use the API when you need an immediate reading. Use the exporter stack when you need to see changes over time or build dashboards and alerts. For capacity decisions, observe both the SRS process and the machine running it: they answer related but different questions.
Check CPU and memory with the SRS HTTP API
1. Confirm the API is enabled and reachable
SRS exposes an HTTP API for system and stream information. The API listener must be configured and reachable from the machine or network where you run the check. The official examples use port 1985; verify the listener and port in your own deployment rather than assuming that every installation uses the same settings.
Do not expose an administrative/API listener directly to the public internet. Run a local check over loopback where appropriate, or restrict access using the network controls available in your environment.
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2. Request the summaries endpoint
curl http://127.0.0.1:1985/api/v1/summaries
The response is a JSON summary. The SRS documentation describes summaries as including process identity information along with CPU and memory, and the broader summary documentation covers network and load usage as well. Field names and availability can vary by release and configuration, so inspect the response from the server you actually run.
3. Query a more focused endpoint if needed
The SRS API reference also lists these endpoints for more specific process, system or memory views:
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/api/v1/rusages/api/v1/self_proc_stats/api/v1/system_proc_stats/api/v1/meminfos
Check that your installed version supports the endpoint and that the relevant statistics are configured before building an integration around it.
Collect ongoing metrics with Prometheus
How the pieces fit together
- SRS exporter: exposes SRS metrics over HTTP.
- Prometheus: scrapes the exporter and stores a time series.
- node_exporter: supplies host-level metrics as a separate target.
- Grafana: can visualize the collected metrics in dashboards.
The SRS exporter guide documents this arrangement with separate Prometheus jobs for SRS and node_exporter. The guide says its described exporter usage requires SRS 5.0.86 or later. Check the documentation for your installed release before applying its configuration.
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Enable the exporter and configure scraping
In the SRS v8 exporter guide, the exporter is off by default, its documented default listener is port 9972, and environment variables can enable and configure it. Follow the guide corresponding to your SRS version for the exact variables and deployment settings; do not assume the v8 defaults apply to an earlier release.
The guide’s sample Prometheus configuration uses separate srs and node scrape jobs and a 5s scrape interval. That is an example from the guide, not a universal recommendation. Choose a collection interval that fits your operational needs and monitoring setup.
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For Docker or a cluster, check that Prometheus can reach the exporter targets. Container addressing, published ports and visibility between host and container differ by deployment, so there is no single target address that works for every setup.
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Separate process statistics from host capacity
An SRS summary or process endpoint describes SRS-related statistics; node_exporter provides a separate view of the machine. Looking at both can help distinguish a resource change associated with SRS from broader host pressure.
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Check configuration and release differences
The v4 API documentation describes a stats configuration for retrieving system statistics, including CPU and memory, and discusses network and disk statistics. It notes that stats.network relates to heartbeat system reporting. The v8 API reference lists the summaries and focused process and memory endpoints above. These versioned documents do not establish that every release exposes identical fields or defaults.
The SRS v8 API reference marks v8 unstable. The v6 introduction includes both a stable label and a development-status note, so verify the status and instructions for the precise release you operate. The SRS v6 documentation describes its HTTP API as an open interface for querying system and stream status.
Establish your own baseline
The cited SRS documentation does not set a universal safe CPU or memory threshold. Record normal readings under your own stream and viewer load, then watch for sustained changes and correlate them with stream quality and host capacity. Treat an isolated percentage or memory value as context, not a standalone pass/fail signal.
Troubleshoot missing or confusing metrics
- The curl request fails to connect: confirm the API listener is enabled, check the configured address and port, and run the request from a network that can reach it. The documented example uses port 1985, but verify your configuration.
- The response lacks a field you expected: check the installed SRS release and its system-statistics configuration. API fields and defaults should not be assumed identical across versions.
- Prometheus shows the SRS target as unavailable: verify that the exporter is enabled, that Prometheus can reach its configured listener, and that the target address and port match your deployment.
- Host metrics are absent: confirm node_exporter is running as a separate target and reachable from Prometheus; the SRS exporter alone is not the host exporter.
- Metrics work on a host but not in Docker or a cluster: review target addressing, port publishing and host/container network visibility for that environment.
- CPU or memory appears high: compare sustained readings with your own baseline and stream conditions, and inspect both SRS and host-level metrics before attributing the cause. The documentation does not provide a universal threshold.
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Conclusion
Use /api/v1/summaries for a quick SRS CPU and memory check. For retained metrics, dashboards and alerting, use the version-appropriate SRS exporter with Prometheus, and add node_exporter when you need machine-wide context. Validate the API, fields and exporter setup against the SRS release and network configuration you actually run.
Quick Recap
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