When analyzing FICON channels, it is normally not possible to draw conclusions based on their utilization alone: 60% may or may not be a good value; it really depends on the type of work being done. With FICON being a multiplexing technology, a measure that is more indicative of how well the FICON channel is dealing with individual I/O requests is the effective channel rate, i.e. how much time does the channel need to transfer a given amount of data. A low effective data rate indicates that there is much demand for the channel, which causes connect time elongation and thereby increases I/O service time. IntelliMagic Vision computes and charts FICON Effective Channel Data Rate and rates whether the value is good or too low.
Another way to evaluate FICON performance is by monitoring the number of open exchanges: i.e. how many I/Os are being served at the same time by the FICON channel.
FICON and ISL
IntelliMagic Vision for z/OS can be used for the sizing and monitoring of FICON configurations, including those with inter-switch links (ISL). With IntelliMagic Vision you can determine the throughput on any channel, and you can easily determine how much bandwidth is needed for each disk subsystem. Once directors are installed, you can report FICON director statistics including those on the ISL links with IntelliMagic Vision. Planning ISLs can be difficult, because you need to know the load from each LPAR for your Storage Systems. IntelliMagic Vision provides this information for a particular point in time or for an extended period.
Front-End (Host) Adapter Utilization
Often times the aggregate throughput of a storage system’s front end adapter (Host Adapter) is less than the sum of the individual parts. Unfortunately, most tools do not report the cumulative throughput or I/O rates for an entire host adapter. IntelliMagic Vision automatically computes the sum of the key metrics for all ports on a given host adapter to provide an easy means to interpret the utilization of the host adapters.
Health Insights and Change Detection
To help enhance the value you can derive from that SMF data, IntelliMagic Vision provides two complementary types of automated anomaly detection: health insights and change detection.
CICS Max Tasks: Automated Change Detection Use Case 7
Change Detection and Health Assessments (based on pre-defined best practice conditions) play complementary roles, but there can be scenarios where they both flag issues. This use case with CICS Max Tasks is one such example.
Batch Job Elapsed Time: Automated Change Detection Use Case 6
Elapsed and CPU times can be of interest for batch jobs, especially those on the critical path for key business job cycles. This use case reflects an abnormally long run time for a daily batch job, and illustrates how potential causes might be investigated.