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One of the great challenges of of monitoring any large cluster is how much data to collect and how often to collect it. Those responsible for managing the cloud infrastructure want to see everything collected centrally which places limits on how much and how often. Developers on the other hand want to see as much detail as they can at as high a frequency as reasonable without impacting the overall cloud performance.
To address what seems to be conflicting requirements, we've chosen a hybrid model at HP. Like many others, we have a centralized monitoring system that records a set of key system metrics for all servers at the granularity of 1 minute, but at the same time we do fine-grained local monitoring on each server of hundreds of metrics every second so when there are problems that need more details than are available centrally, one can go to the servers in question to see exactly what was going on at any specific time.The tool of choice for this fine-grained monitoring is the open source tool collectl, which additionally has an extensible api. This talk will briefly introduce the audience to collectl's capabilities but more importantly show how it's used to augment any existing centralized monitoring infrastructure.