Logs
Logs from Collaboration Server On-Premises are written to stdout
and stderr
. Most of them are formatted in JSON. They can be used for monitoring or debugging purposes. In production environments, we recommend storing logs to files or using a distributed logging system (like ELK or CloudWatch).
# Docker
Docker has built-in logging mechanisms that capture logs from the output of containers. The default logging driver writes logs to files.
When using this driver, you can use the docker logs
command to show logs from the container. You can add the -f
flag to view logs in real time. Refer to the official Docker documentation for more information about the logs
command.
When the container is running for a long time, logs can take up a lot of space. To avoid this problem, you should make sure that log rotation is enabled. This can be set with the max-size
option.
# PM2
PM2 has a built-in logging mechanism that captures logs from the output of processes and writes them to files. By default, the logs can be found in the ~/.pm2/logs
directory.
You can also use the pm2 logs <app name|id>
command to view logs in real time.
When the container is running for a long time, logs can take up a lot of space. To avoid this problem, you should make sure that log rotation is enabled. Log rotation is available as a PM2 module and can be installed with the pm2 install pm2-logrotate
command. Check the documentation for more information.
# Distributed logging
If you are running more than one instance of Collaboration Server On-Premises, we recommend using a distributed logging system. It allows you to view and analyze logs from all instances in one place.
# AWS CloudWatch and other cloud solutions
If you are running Collaboration Server On-Premises in the cloud, the simplest and recommended way is to use a service which is available at the selected provider. Some of the available services:
- AWS – CloudWatch
- Google Cloud – Cloud Logging
- Azure – Azure Monitor
To use CloudWatch with AWS ECS, you have to create a log group before and change the log driver to awslogs
. When the log driver is configured properly, logs will be streamed directly to CloudWatch.
The logConfiguration
of logging may look similar to this:
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-region": "us-west-2",
"awslogs-group": "cksource",
"awslogs-stream-prefix": "ck-cs-logs"
}
}
Refer to the Using the awslogs Log Driver article for more information.
# On-Premises solutions
If you are using your own infrastructure or for some reason cannot use the service offered by your provider, you can always use some on-premises distributed logging system.
There are a lot of solutions available, among others:
-
ELK + Filebeat
This is a stack built on top of Elasticsearch, Logstash and Kibana. In this configuration, Elasticsearch stores logs, Filebeat reads logs from Docker and sends them to Elasticsearch, and Kibana is used to view them. Logstash is not necessary because logs are already structured. -
Fluentd
It uses a dedicated Docker log driver to send logs. It has a built-in frontend, but can be also integrated with Elasticsearch and Kibana for better filtering. -
Graylog
It uses a dedicated Docker log driver to send logs. It has a built-in frontend and needs Elasticsearch to store logs as well as a MongoDB database to store the configuration.
# Example configuration
The example configuration uses Fluentd, Elasticsearch and Kibana to capture logs from Docker.
Before running Collaboration Server On-Premises, you have to prepare logging services. For the purposes of this example, Docker Compose is used. Create the fluentd
, elasticsearch
and kibana
services inside the docker-compose.yml
file:
version: '3.7'
services:
fluentd:
build: ./fluentd
volumes:
- ./fluentd/fluent.conf:/fluentd/etc/fluent.conf
ports:
- "24224:24224"
- "24224:24224/udp"
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:6.8.5
expose:
- 9200
ports:
- "9200:9200"
kibana:
image: docker.elastic.co/kibana/kibana:6.8.5
environment:
ELASTICSEARCH_HOSTS: "http://elasticsearch:9200"
ports:
- "5601:5601"
To integrate Fluentd with Elasticsearch, you first need to install fluent-plugin-elasticsearch
in the Fluentd image. To do this, create a fluentd/Dockerfile
with the following content:
FROM fluent/fluentd:v1.10-1
USER root
RUN apk add --no-cache --update build-base ruby-dev \
&& gem install fluent-plugin-elasticsearch \
&& gem sources --clear-all
Next, configure the input server and connection to Elasticsearch in the fluentd/fluent.conf
file:
<source>
@type forward
port 24224
bind 0.0.0.0
</source>
<match *.**>
@type copy
<store>
@type elasticsearch
host elasticsearch
port 9200
logstash_format true
logstash_prefix fluentd
logstash_dateformat %Y%m%d
include_tag_key true
type_name access_log
tag_key @log_name
flush_interval 1s
</store>
<store>
@type stdout
</store>
</match>
Now you are ready to run the services:
docker-compose up --build
When the services are ready, you can finally start Collaboration Server On-Premises.
docker run --init -p 8000:8000 \
--log-driver=fluentd \
--log-opt fluentd-address=[Fluentd address]:24224 \
[Your config here] \
docker.cke-cs.com/cs:[version]
Now open Kibana in your browser. It is available at http://localhost:5601/. In the first run, you may be asked about creating an index. Use the fluentd-*
pattern and press the “Create” button. After this step, your logs should appear in the “Discover” tab.