Note All the stats currently exposed via Redis are available via Prometheus as well, if you're building from scratch this would be the better way.
PyHSS's statistics & monitoring rely on Redis.
You can view all the current Diameter peers by running the view_stats.py tool, which will list all active and inactive Diameter peers connected / connected then disconnected from the system.
Different parts of the software have a code snippet like this:
if yaml_config['redis']['enabled'] == True:
try:
self.redis_store.incr('Answer_257_attempt_count')
except:
logging.error("failed to incriment Answer_257_attempt_count")
Which checks to see if Redis is enabled in the config (Example config with Redis enabled at the bottom of this doc), and then attempts to incriment the value of a particular key.
This data can then be read by external Redis clients.
One such example is the view_stats.py tool which simply loops through and prints out the values from Redis.
For integrating into NMS systems we also expose the Redis statistics via SNMP using the SNMP Labs PySNMP.
More info on the design descision to use Redis and PySNMP to expose this information is covered in this blog post.
OIDs are a bit of a problem, as SNMP's OIDs are numerical and our Redis keys are strings. To get around this a very rudimentary solution has been put together in the form of MIB_generator.py which loops through the keys defined in the code and assigns an OID to each.
If you wanted to do away with SNMP alltogether (and I woudln't blame you) and instead use Grafana or something similar, the data can easily be scraped from Redis as required.
Add the following part to the config.yaml
prometheus:
enabled: True
port: 8081
Add the endpoint to Prometheus
A grafana dashboard template is provided Grafana_PyHSS.json