Collecting Operating System Resources Metrics
Cluster Health Monitor (CHM) and System Health Monitor (SHM) are both high-performance, lightweight daemons that collect, analyze, aggregate, and store a large set of operating system metrics to help you diagnose and troubleshoot system issues.
Why CHM or SHM is unique
| CHM or SHM | Typical OS Collector |
|---|---|
| Last man standing - daemon runs memory locked, RT scheduling class ensuring consistent data collection under system load. | Inconsistent data dropouts due to scheduling delays under system load. |
| High fidelity data sampling rate, 5 seconds. Very low resource usage profile at 5-second sampling rates. | Running multiple utilities creates additional overhead on the system being monitored, and worsens with higher sampling rates. |
| High Availability daemon, collated data collections across multiple resource categories. Highly optimized collector (data read directly from the operating system, same source as utilities). | Set of scripts/command-line utilities, for example, top, ps, vmstat, iostat, and so on re-directing their output to one or more files for every collection sample. |
| Collected data is collated into a system snapshot overview ( Nodeview ) on every sample, Nodeview also contains additional summarization and analysis of the collected data across multiple resource categories. | System snapshot overviews across different resource categories are very tedious to collate. |
| Significant inline analysis and summarization during data collection and collation into the Nodeview greatly reduces tedious, manual, time-consuming analysis to drive meaningful insights. | The analysis is time-consuming and processing-intensive as the output of various utilities across multiple files needs to be collated, parsed, interpreted, and then analyzed for meaningful insights. |
| Performs Clusterware-aware specific metrics collection (Process Aggregates, ASM/OCR/VD disk tagging, Private/Public NIC tagging). Also provides an extensive toolset for in-depth data analysis and visualization. | None |