Metrics collection agent for the Numenta Rogue showcase application and consists of two primary components: A long-running metric collection agent, which periodically polls various metrics and records the results to a local database, and a separate process for forwarding metrics to a Grok server for analysis.

Each metric collection agent is executed in a continuously-running gevent Greenlet, with a pre-determined wait interval between samples. Each sample is cached locally in a dedicated RRDTool database. Individual metrics are implemented as subclasses of avogadro.agent.AvogadroAgent(), and must implement a collect() method, which returns the metric value.

The rogue-forward process fetches metric data from the individual RRDTool databases using the rrdtool fetch command, and sends the metric data using the Grok Custom Metric API. Each time the rogue-forward process is executed, the most recent timestamp is cached locally, and is used as a starting point for subsequent requests.

Install RRDTool:

brew install rrdtool

Install in development mode:

python setup.py develop --install-dir=... --script-dir=...

Start key-counter with nohup:

nohup rogue-keycounter > rogue-keys.stdout 2> rogue-keys.stderr < /dev/null &

Make sure that iTerm/Terminal is allowed in System Prefrences > Security & Privacy > Privacy > Accessibility!

Start metric collection agent with nohup:

nohup rogue-agent --prefix=var/db/ --interval=300 --hearbeat=600 > rogue-agent.stdout 2> rogue-agent.stderr < /dev/null &

Forward pending metric data to Grok once:

rogue-forward --server=https://localhost --prefix=var/db

Sample crontab entry:

* * * * * PATH=$PATH:/usr/local/bin PYTHONPATH=... .../rogue-forward --server=... --prefix=... > .../rogue-forward.stdout 2> .../rogue-forward.stderr < /dev/null

All metric data is written to a local round-robin database, which only retains the two most recent weeks of data at any given moment in time. Should you want the data exported to CSV, use the rogue-export utility:

rogue-export --prefix=var/db

The exporter keeps track of the position of a given metric, so you can run rogue-export as frequently as you like, and the .csv files in var/db/, will be updated accordingly. i.e. you can periodically sync the round-robin database to a csv file in var/db/

Total CPU utilization as a percentage, as reported by psutil.cpu_percent().

The percentage memory usage calculated as (total - available) / total * 100, as reported by psutil.virtual_memory().percent

Number of bytes read (total), as reported by psutil.disk_io_counters.read_bytes

DiskWriteBytes ~~~~~~~~~~~~~

Number of bytes written (total), as reported by psutil.disk_io_counters.write_bytes

Time spent reading from disk (in milliseconds), as reported by psutil.disk_io_counters.read_time

Time spent writing to disk (in milliseconds), as reported by psutil.disk_io_counters.write_time

Number of bytes sent, as reported by psutil.net_io_counters.bytes_sent()

Number of bytes received, as reported by psutil.net_io_counters.bytes_recv()

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you may not use this file except in compliance with the License.
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