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Observability of mainframe metrics in Grafana

The three pillars of observability are traces, logs and metrics. z/IRIS possesses a metric streaming feature that facilitates the integration of mainframe related metrics with popular open-source and enterprise-ready dashboard and reporting software.

z/OS Connect Dashboard in Grafana

Enterprise Performance Management teams and DevOps engineers can monitor and analyze how z/OS Connect servers and mainframe-based service providers perform for REST API requests by monitoring load, latencies and error rates which correlate to the availability and reliability of business applications.

z/OS Infrastructure Dashboard 

Resource Measurement Facility (RMF) is IBM’s strategic performance management product for z/OS. RMF gathers and reports on z/OS resource usage. Mainframe users can configure RMF to store data in SMF records which z/IRIS streams and processes in real-time.

The IBM RMF SMF type 70 records provide interval usage and sampling data for mainframe processors e.g. GCP, zIIPs, zAAPs, etc. and are used to create z/IRIS CPU Activity Metrics.


CPU Activity

Percentage of time the processor was utilized by MVS or the LPAR. Usually, a high CPU usage could potentially mean contention and should be analyzed.

In-Ready Work Unit Queue

Ranged percentage samples of when work units could not be dispatched. This metric always shows the current sample of work unit distribution within your systems. 

CPU Contention 

The sum of the ranges from the In-Ready Work Unit Queue Distribution. A value higher than 60% implies the processor is likely under contention.


with Grafana