Kafka
You can export statistics to a Kafka
server.
The connection should be defined in the Glances configuration file as
following:
[kafka]
host=localhost
port=9092
topic=glances
#compression=gzip
# Tags will be added for all events
#tags=foo:bar,spam:eggs
# You can also use dynamic values
#tags=hostname:`hostname -f`
Note: you can enable the compression but it consume CPU on your host.
and run Glances with:
$ glances --export kafka
Stats are sent in native JSON
format to the topic:
key
: plugin namevalue
: JSON dict
Example of record for the memory plugin:
ConsumerRecord(topic=u'glances', partition=0, offset=1305, timestamp=1490460592248, timestamp_type=0, key='mem', value=u'{"available": 2094710784, "used": 5777428480, "cached": 2513543168, "mem_careful": 50.0, "percent": 73.4, "free": 2094710784, "mem_critical": 90.0, "inactive": 2361626624, "shared": 475504640, "history_size": 28800.0, "mem_warning": 70.0, "total": 7872139264, "active": 4834361344, "buffers": 160112640}', checksum=214895201, serialized_key_size=3, serialized_value_size=303)
Python code example to consume Kafka Glances plugin:
from kafka import KafkaConsumer
import json
consumer = KafkaConsumer('glances', value_deserializer=json.loads)
for s in consumer:
print(s)