Introduction
The Project
This project proposes extensions to the fault management architecture (FMA) to support a sensor abstraction layer for the collection and analysis of sensor based telemetry that can be used in fault and resource management.
The Problem
How do we manage raw telemetry data kept, maintained and exported by disparate sources for the purposes of fault, resource management and budgeting? Today, there are a number of sensor collection mechanisms exported by the hardware and software. For the most part, the information they export is hap-haphazardly presented and accessed according to ad-hoc operating system interfaces, per-platform methods or per-subsystem industry standards (SMBus, SMART and IPMI). Using this data for fault or resource management is clumsy and typically requires low-level system knowledge baked into higher-level management applications.
Key Objectives
As part of an overall sensor abstraction layer based on our current fault management architecture, we can solve this problem and provide a better understanding of the overall health and usage of a system through more sophisticated diagnosis technologies and fine-grained observability of sensor data via common access methods. A sensor abstraction layer must posses:
- the ability to alert the administrator to conditions observed by platform sensors that may impact the operational state of the platform.
2. the ability to alert the administrator to conditions that resolve themselves as observed by platform sensors.
3. the ability to watch one or more sensors and correlate the data for predictive fault analysis or resource management.
4. the ability to continuously record sensor data and retrieve it from systems for offline analysis, future system design or development of more advanced diagnosis algorithms.
5. the ability for administrators and service personnel to manually inspect sensor values without having to understand the exact implementation (e.g. IPMI or SMBus).
6. the ability to connect sensor data to higher-level diagnosis (e.g. SMART disk data to SCSI and ZFS diagnosis engines).
7. the ability to understand and observe performance and power budgets based on raw sensor data.
Documents
- Draft Design Document
- Portfolio for libtopo enumeration of fans and power supplies via IPMI
- Portfolio for Extending HC FMRI scheme to represent sensors/indicators
- Portfolio for Reflecting Fan/PSU Fault Diagnosis in Solaris
- PSARC One-pager for Extending libnvpair for type double
- PSARC One-pager for Extending hc-scheme FMRIs for Facility Nodes