Many services, nodes, configuration files, log files - due to this complexity it can be cumbersome to uniquely identify the root cause for problems in a timely manner. We’re going to look at common problems in OpenStack environments, their root cause, and options for efficient operation.
6. confidential
Resource capacity and utilization
OpenStack service availability/performance
Supporting services
Log analytics
Applications running on top
Real user monitoring, UX affects $
PaaS
18. confidential
Resource capacity and utilization
OpenStack service availability/performance
Supporting services
Log analytics
Applications running on top
Dependencies
Correlation of metrics/events/data
Real user monitoring, UX affects $
PaaS
innovation – applications, containers, k8s – now also Docker is friends with k8s
op efficiency – bosh for CF, now also k8s; or Magnum ...
PayPal, CERN, OICR
LAMP Stack 2.0 !
CF - VW, SAP
OS - BMW, amadeus
k8s – comcast, ebay
also OpenStack vendors think about applications
Monitoring tool landscape
Look at the stack – it’s going to fail!
Let’s say you observe all these things -> lots of data to browse through if anything breaks
CORRELATION TO THE HELP
measurement how to variables fluctuate together
doesn’t imply causation
IF YOU DON'T HAVE CONTEXT YOU MIGHT END UP LIKE THIS GUY
you need something that is easy to deploy, adaptable, and able to handle environments of that size
I think I made my point that it is challenging ...
Now it's up to you - how are you going to deal with those challenges?
if you don't monitor, you never know what you get ...