Docker Cookbook

292 | Chapter 9: Monitoring Containers

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all the running containers, and obtains the statistics for them. For the stats called
cpu_stats
, it writes a 
PUTVAL
string to 
stdout
. This string is understood by Collectd
and sent to the Graphite data store (a.k.a Carbon) for storage and visualization. The
PUTVAL
string follows the Collectd 
exec
plug-in syntax:
#!/usr/bin/env python
import
random
import
json
import
docker
import
sys
cli
=
docker
.
Client
(
base_url
=
'unix://var/run/docker.sock'
)
types
=
[
"gauge-cpu0"
]
for
h
in
cli
.
containers
():
if
not
h
[
"Status"
]
.
startswith
(
"Up"
):
continue
stats
=
json
.
loads
(
cli
.
stats
(
h
[
"Id"
])
.
next
())
for
k
,
v
in
stats
.
items
():
if
k
==
"cpu_stats"
:
print
(
"PUTVAL 
%s
/
%s
/
%s
N:
%s
"
%
(
h
[
'Names'
][
0
]
.
lstrip
(
'/'
),
\
'docker-cpu'
,
types
[
0
],
\
v
[
'cpu_usage'
][
'total_usage'
]))
The example plug-in in this recipe is minimal, and the statistics
need to be processed further. You might want to consider using 
this
Python-based plug-in instead.
See Also
• Collectd 
website
• Collectd Exec 
plug-in
• Graphite 
website
• Logstash 
website
• Collectd Docker 
plug-in
9.9 Using Collectd to Visualize Container Metrics | 293

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9.10 Using cAdvisor to Monitor Resource Usage
in Containers
Problem
Although Logspout (see 
Recipe 9.6
) allows you to stream application logs to remote
endpoints, you need a resource utilization monitoring system.
Solution
Use 
cAdvisor
, created by Google to monitor resource usage and performance of its
lcmtfy
containers. cAdvisor runs as a container on your Docker hosts. By mounting
local volumes, it can monitor the performance of all other running containers on that
same host. It provides a local web UI, exposes an 
API
, and can stream data to
InfluxDB
. Streaming data from running containers to a remote InfluxDB cluster
allows you to aggregate performance metrics for all your containers running in a
cluster.
To get started, let’s use a single host. Download the 
cAdvisor
image as well as 
borja/
unixbench
, an image that enables you to simulate a workload inside a container:
$ docker pull google/cadvisor:latest
$ docker pull borja/unixbench
$ docker run -v /var/run:/var/run:rw\
-v /sys:/sys:ro \
-v /var/lib/docker/:/var/lib/docker:ro \
-p 8080:8080 \
-d \
--name cadvisor \
google/cadvisor:latest
$ docker run -d borja/unixbench
With the two containers running, you can open your browser a:8080">t 
:8080">http://
:8080">:8080
and you will enjoy the cAdvisor UI (see 
Figure 9-4
).
You will be able to browse the running containers and access metrics for each of
them.