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
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()
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.