Episode 21 "Fits and Starts"
Mainframe, Performance, Topics Podcast - En podcast af Marna Walle
Kategorier:
Here are the show notes for Episode 21 “Fits and Starts”. The show is called this because we talk about fitness devices, and the Performance topic that had work submitted after a one minute hiatus.
Mainframe: SMF Recording of APF Modifications
Post-IPL dynamic APF changes are reflected in SMF 90 Subtype 37. A lot of the function is in z/OS V2.2, with these fields in the SMF record:
Function:
- Add, Delete, DynFormat, StatFormat
Was the update via SETPROG, SET PROG, CSVAPF
Parmlib member suffix for the SET PROG case, ... - Triggers when post-IPL APF changes dynamically: PROGxx: APF ADD …or APF DELETE … SETPROG APF,ADD,… or SETPROG APF,DELETE,…
- Ensure to collect by setting in SMFPRMxx type 90 subtype 37 record
- Presumably there’s not much overhead, as it will be produced when changes happen (which is probablyl not often).
- Auditors will probably want this
Performance: An interesting Db2 DDF case
Central to Martin’s DDF work is some analysis code to process SMF 101 DB2 Accounting Trace.
A customer complained their DDF application stopped dead one evening – for 1 minute. It was an application serviced by a 3-way Datasharing group. The customer sent SMF 101 data from all 3 members for 3 hours around the stoppage, and for 3 hours the previous evening for a presumably “good behaviour”.
Martin plotted application statistics at a one second interval level. It showed a 40-second stoppage the evening they hadn’t complained, making the 1 minute threshold interesting as a number.
Martin “zoomed in” to a much shorter time range . When transactions started again they were elongated, and it that was due to the clustered arrivals in clearing the backlog.
The best theory is something external stopped transactions arriving.
Further he thought there could be “near misses” many times, just short of the 1 minute mark. After transactions started coming again there were spikes in transactions arriving every minute. The speculation is this might be the middle tier doing something on a 1 minute basis: Maybe retries of some sort?
Topics: Fitness Tracking
- Marna uses a Fitbit Charge 2.
Key features: sleep analysis, step counts, heart rate.
Fitbit app for the Android: calculates floors, miles, calories, sleep analysis, across timescales – day, month, overall, etc and compares with age bracket. - Martin uses an Apple Watch, and used to have a Fitbit. He wanted the Watch for other reasons: for health a few months ago, and all of the above – except for sleep tracking.
- Marna gets employer incentives, to help with health care cost reduction.
- Martin has been successful, as he hasn’t failed to close his rings for 3 months, for the Apple Watch. This makes him obsessive. Uses iOS Overcast podcast player to send podcast episodes to the watch. Runs with just the watch and AirPods. Listening to podcasts keeps me going – whether running or walking. He has lost a considerable amount of weight! Cardiac situation much better, lowered resting heart rate, faster recovery from exercise, and clothes fit better.
Contacting Us
You can reach Marna on Twitter as mwalle and by email.
You can reach Martin on Twitter as martinpacker and by email and blogs at blog.