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Hackernoon logoDocker Centralized Logging with ELK Stack [EXPLAINED] by@sudip-sengupta

Docker Centralized Logging with ELK Stack [EXPLAINED]

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@sudip-senguptaSudip Sengupta

Solution Architect | Technical Content Writer

As your infrastructure grows, it becomes crucial to have robots and a reliable centralized logging system. Log centralization is becoming a key aspect of a variety of IT tasks and provides you with an overview of your entire system.

The best solution is to aggregate the logs from all containers, which is enriched with metadata so that it provides you with better traceability options and comes with awesome community support. This is where ELK Stack comes into the picture. ELK, also known as Elastic stack, is a combination of modern open-source tools like ElasticSearch, Logstash, and Kibana. It is a complete end-to-end log analysis solution you can use for your system.

Each component has its defined role to play: ElasticSearch is best in storing the raw logs, Logstash helps to collect and transform the logs into a consistent format, and Kibana adds a great visualization layer and helps you to manage your system in a user-friendly manner.

In this guide, you will learn how to deploy ELK and start aggregating container logs. Here we are going to combine ELK with Filebeat to aggregate the container logs. For this, we are going to build a custom Docker image.

Step 1 - Configuring Filebeat:

Let’s begin with the Filebeat configuration. First, you have to create a Dockerfile to create an image:

$ mkdir filebeat_docker && cd $_
$ touch Dockerfile && nano Dockerfile

Now, open the 

Dockerfile
 in your preferred text editor, and copy/paste below mentioned lines:

FROM docker.elastic.co/beats/filebeat:7.5.1
 
COPY filebeat.yml /usr/share/filebeat/filebeat.yml
USER root
RUN mkdir /usr/share/filebeat/dockerlogs
RUN chown -R root /usr/share/filebeat/
RUN chmod -R go-w /usr/share/filebeat/

In 

filebeat_docker
 directory, create a filebeat.yml file that contains configuration for Filebeat. For this guide, we are going to use a minimal 
filebeat.yml
 file.

filebeat.inputs:
  - type: docker
    containers:
      path: "/usr/share/dockerlogs/data"
      stream: "stdout"
      ids:
        - "*"
      cri.parse_flags: true
      combine_partial: true
      exclude_files: ['\.gz$']
 
processors:
  - add_docker_metadata:
      host: "unix:///var/run/docker.sock"
 
filebeat.config.modules:
  path: ${path.config}/modules.d/*.yml
  reload.enabled: false
 
output.logstash:
  hosts: ["127.0.0.1:5044"]
 
log files:
logging.level: error
logging.to_files: false
logging.to_syslog: false
loggins.metrice.enabled: false
logging.files:
  path: /var/log/filebeat
  name: filebeat
  keepfiles: 7
  permissions: 0644
ssl.verification_mode: none

Now, it’s time to create the Filebeat Docker image:

$ docker build -t filebeatimage .
Sending build context to Docker daemon  3.584kB
Step 1/6 : FROM docker.elastic.co/beats/filebeat:7.5.1
7.5.1: Pulling from beats/filebeat
c808caf183b6: Already exists 
a07383b84bc8: Pull complete 
a3c8dd4531b4: Pull complete 
5547f4a87d0c: Pull complete 
d68e041d92cd: Pull complete 
7cfb3f76a272: Pull complete 
748d7fe7bf07: Pull complete 
Digest: sha256:68d87ae7e7bb99832187f8ed5931cd253d7a6fd816a4bf6a077519c8553074e4
Status: Downloaded newer image for docker.elastic.co/beats/filebeat:7.5.1
 ---> 00c5b17745d1
Step 2/6 : COPY filebeat.yml /usr/share/filebeat/filebeat.yml
 ---> f6b75829d8d6
Step 3/6 : USER root
 ---> Running in 262c41d7ce58
Removing intermediate container 262c41d7ce58
 ---> 1ffcda8f39cf
Step 4/6 : RUN mkdir /usr/share/filebeat/dockerlogs
 ---> Running in 8612b1895ac7
Removing intermediate container 8612b1895ac7
 ---> 483d29e65dc7
Step 5/6 : RUN chown -R root /usr/share/filebeat/
 ---> Running in 4a6ad8b22705
Removing intermediate container 4a6ad8b22705
 ---> b779a9da7ac9
Step 6/6 : RUN chmod -R go-w /usr/share/filebeat/
 ---> Running in bb9638d12090
Removing intermediate container bb9638d12090
 ---> 85ec125594ee
Successfully built 85ec125594ee
Successfully tagged filebeatimage:latest

To verify if the image was built successfully:

$ docker images
REPOSITORY      TAG           IMAGE ID            CREATED             SIZE
filebeatimage   latest        85ec125594ee        7 seconds ago       514MB

For 

filebeat_elk
 container, you have created two mounts using the parameter -v;

  • /var/lib/docker/containers:/usr/share/dockerlogs/data
    : You have mapped host machine docker logs which resides in 
    /var/lib/docker/containers
     to 
    /usr/share/dockerlogs/data
     inside the docker container. Note that you have used :ro which denotes that has read-only permission.
  • Whereas, 
    /var/run/docker.sock
     is bind with Filebeat container’s Docker daemon, which allows Filebeat container to gather the Docker’s metadata and container logs entries.

Filebeat installation via DEB:

There is an alternate way to install Filebeat in your host machine. At the time of writing, Filebeat version is 

7.5.1
 you can download the latest version of filebeat from here.

To install the downloaded 

.deb
 file:

$ wget https://artifacts.elastic.co/downloads/beats/filebeat/filebeat-7.5.1-amd64.deb

$ sudo dpkg -i filebeat-7.5.1-amd64.deb

You can find the configuration file in /etc/filebeat/filebeat.yml directory.

Step 2 - Configuring ELK or Elastic Stack

You can either use a remote server to host your ELK stack or can launch containers within your existing system.

Before you get going, make sure that the following ports are listening:

  • Elasticsearch - Port 9200 and Port 9300
  • Logstash - Port 5044
  • Kibana - Port 5601

ElasticSearch:

We are going to use the latest official image of Elasticsearch as of now. So begin by pulling the image from Docker Hub:

$ docker pull docker.elastic.co/elasticsearch/elasticsearch:7.5.1
7.5.1: Pulling from elasticsearch/elasticsearch
c808caf183b6: Already exists 
05ff3f896999: Pull complete 
82fb7fb0a94e: Pull complete 
c4d0024708f4: Pull complete 
136650a16cfe: Pull complete 
968db096c092: Pull complete 
42547e91692f: Pull complete 
Digest: sha256:b0960105e830085acbb1f9c8001f58626506ce118f33816ea5d38c772bfc7e6c
Status: Downloaded newer image for docker.elastic.co/elasticsearch/elasticsearch:7.5.1
docker.elastic.co/elasticsearch/elasticsearch:7.5.1

Now, create a directory name as docker_elk, where all your configuration files and Dockerfile will reside:

$ mkdir docker_elk && cd $_

Inside 

docker_elk
, create another directory for 
elasticsearch
 and create a 
Dockerfile
 and 
elasticsearch.yml
 files:

$ mkdir elasticsearch && cd $_
$ touch Dockerfile && touch elasticsearch.yml

Open 

elasticsearch.yml
 file in your preferred text editor and copy the configuration setting as it is:

---
cluster.name: "docker-cluster"
network.host: 0.0.0.0
 
xpack.license.self_generated.type: basic
xpack.security.enabled: true
xpack.monitoring.collection.enabled: true

Note that you can set 

xpack.license.self_generated.type 
from
basic
to
trial
if you wish to evaluate the commercial feature of x-pack for 30 days.

Open Dockerfile in your preferred text editor and copy the below-mentioned lines and paste it as it is:

FROM docker.elastic.co/elasticsearch/elasticsearch:7.5.1
COPY --chown=elasticsearch:elasticsearch ./elasticsearch.yml /usr/share/elasticsearch/config/

The command 

chown
 is to change the file owner to 
elasticsearch
 as of other files in container.

Kibana:

Now, you are going to setup Dockerfile for Kibana, and again you have to pull the latest image from the Elastic Docker registry:

$ docker pull docker.elastic.co/kibana/kibana:7.5.1
7.5.1: Pulling from kibana/kibana
c808caf183b6: Already exists 
e12a414b7b04: Pull complete 
20714d0b39d8: Pull complete 
393e0a5bccf2: Pull complete 
b142626e938b: Pull complete 
b28e35a143ca: Pull complete 
728725922476: Pull complete 
96692e1a8406: Pull complete 
e4c3cbe1dbbe: Pull complete 
bb6fc46a19d1: Pull complete 
Digest: sha256:12b5e37e0f960108750e84f6b2f8acce409e01399992636b2a47d88bbc7c2611
Status: Downloaded newer image for docker.elastic.co/kibana/kibana:7.5.1
docker.elastic.co/kibana/kibana:7.5.1

Inside your 

docker_elk
, create a directory, and inside of it, you have to create a 
Dockerfile
 and 
kibana.yml
 files:

$ mkdir kibana && cd $_
$ touch Dockerfile && touch kibana.yml

kibana.yml 
will consist of follow configurations. Note that you have to change the values of 
elasticsearch.user
and 
elasticsearch.password
:

---
server.name: kibana
server.host: "0"
elasticsearch.hosts: [ "http://elasticsearch:9200" ]
xpack.monitoring.ui.container.elasticsearch.enabled: true
 
elasticsearch.username: elastic
elasticsearch.password: yourstrongpasswordhere

Whereas, in 

Dockerfile
, will look something like this:

FROM docker.elastic.co/kibana/kibana:7.5.1
COPY ./kibana.yml /usr/share/kibana/config/

Logstash:

Container image for Logstash is available from the Elastic Docker registry. Again at the time of writing current version is 7.5.1, you can find latest version of Logstash here.

$ docker pull docker.elastic.co/logstash/logstash:7.5.1
7.5.1: Pulling from logstash/logstash
c808caf183b6: Already exists 
7c07521065ed: Pull complete 
d0d212a3b734: Pull complete 
418bd04a229b: Pull complete 
b22f374f97b1: Pull complete 
b65908943591: Pull complete 
2ee12bfc6e9c: Pull complete 
309701bd1d88: Pull complete 
b3555469618d: Pull complete 
2834c4c48906: Pull complete 
bae432e5da20: Pull complete 
Digest: sha256:5bc89224f65459072931bc782943a931f13b92a1a060261741897e724996ac1a
Status: Downloaded newer image for docker.elastic.co/logstash/logstash:7.5.1
docker.elastic.co/logstash/logstash:7.5.1

Now, create a directory for Logstash inside 

docker_elk
 and add necessary files as shown below:

$ mkdir logstash && cd $_
$ touch Dockerfile && touch logstash.yml

Copy below mentioned line into logstash.yml. Make sure that you enter the right username and password in 

xpack.monitoring.elasticsearch.username
 and 
xpack.monitoring.elasticsearch.password
 respectively:

---
http.host: "0.0.0.0"
xpack.monitoring.elasticsearch.hosts: [ "http://elasticsearch:9200" ]
 
xpack.monitoring.enabled: true
xpack.monitoring.elasticsearch.username: elastic
xpack.monitoring.elasticsearch.password: yourstrongpasswordhere

Now, add following lines into your 

Dockerfile
:

FROM docker.elastic.co/logstash/logstash:7.5.1
COPY ./logstash.yml /usr/share/logstash/config/
COPY ./logstash.conf /usr/share/logstash/pipeline/

Apart from this, you have to create a 

logstash.conf
file. Here in elasticsearch reference you will find 
host
user
 and 
password
, make sure you change the values as per your system:

input {
    tcp {
    port => 5000
    codec => json
  }
}
output {
  elasticsearch {
    hosts => "elasticsearch:9200"
    user => elastic
    password => yourstrongpasswordhere
  }
}

As you are through with the setup of your stack's components, the directory structure of your project should should look something like this:

.
├── elasticsearch
│   ├── Dockerfile
│   └── elasticsearch.yml
├── kibana
│   ├── Dockerfile
│   └── kibana.yml
└── logstash
    ├── Dockerfile
    ├── logstash.conf
    └── logstash.yml
 
3 directories, 7 files

Now, it’s time to create a Docker Compose file, which will let you run the stack.

Step 3 - Docker Compose

Create a 

docker-compose.yml
 file in the 
docker_elk
 directory. Here you are going to define and run your multi-container application consist of Elasticsearch, Kibana, and Logstash.

You can copy the below-mentioned context in your docker-compose.yml file. Please make sure that you change the 

ELASTIC_PASSWORD
 and 
ES_JAVA_OPTS
 values. For this guide, 
ES_JAVA_OPTS
 is set to 256 MB, but in real world scenarios you might want to increase the heap size as per requirement.

version: '3.2'
 
services:
 elasticsearch:
   build:
     context: elasticsearch/
   volumes:
     - type: volume
       source: elasticsearch
       target: /usr/share/elasticsearch/data
   ports:
     - "9200:9200"
     - "9300:9300"
   environment:
     ES_JAVA_OPTS: "-Xmx256m -Xms256m"
     ELASTIC_PASSWORD: yourstrongpasswordhere
     discovery.type: single-node
   networks:
     - elk_stack
 
 logstash:
   build:
     context: logstash/
   ports:
     - "5000:5000"
     - "9600:9600"
   environment:
     LS_JAVA_OPTS: "-Xmx256m -Xms256m"
   networks:
     - elk_stack
   depends_on:
     - elasticsearch
 
 kibana:
   build:
     context: kibana/
   ports:
     - "5601:5601"
   networks:
     - elk_stack
   depends_on:
     - elasticsearch
 
networks:
 elk_stack:
   driver: bridge
 
volumes:
 elasticsearch:

Now, to build the ELK stack, you have to run the following command in your 

docker_elk
 directory:

$ docker-compose up -d
Starting elastic_elk ... done
Starting kibana_elk   ... done
Starting logstash_elk ... done

To ensure that the pipeline is working all fine, run the following command to see the Elasticsearch indices:

$ curl 'localhost:9200/_cat/indices?v' -u elastic:yourstrongpasswordhere

health status index                             uuid                   pri rep docs.count docs.deleted store.size pri.store.size
green  open   .triggered_watches                m-l01yMmT7y2PYU4mZ6-RA   1   0          0            0      6.5kb          6.5kb
green  open   .watcher-history-10-2020.01.10    SX3iYGedRKKCC6JLx_W8fA   1   0       1523            0        2mb            2mb
green  open   .management-beats                 ThHV2q9iSfiYo__s2rouIw   1   0          6            1     40.5kb         40.5kb
green  open   .ml-annotations-6                 PwK7Zuw7RjytoWFuCCulJg   1   0          0            0       283b           283b
green  open   .monitoring-kibana-7-2020.01.10   8xVnx0ksTHShds7yDlHQvw   1   0       1006            0    385.4kb        385.4kb
green  open   .monitoring-es-7-2020.01.10       CZd89LiNS7q-RepP5ZWhEQ   1   0      36412          340     16.4mb         16.4mb
green  open   .apm-agent-configuration          e7PRBda_QdGrWtV6KECsMA   1   0          0            0       283b           283b
green  open   .ml-anomalies-shared              MddTZQ7-QBaHNTSmOtUqiQ   1   0          1            0      5.5kb          5.5kb
green  open   .kibana_1                         akgBeG32QcS7AhjBOed3LA   1   0       1105           28    687.1kb        687.1kb
green  open   .ml-config                        CTLI-eNdTkyBmgLj3JVrEA   1   0         22            0     56.6kb         56.6kb
green  open   .ml-state                         gKx28CMGQiuZyx82bNUoYg   1   0          0            0       283b           283b
green  open   .security-7                       krH4NlJeThyQRA-hwhPXEA   1   0         36            0     83.6kb         83.6kb
green  open   .logstash                         7wxswFtbR3eepuWZHEIR9w   1   0          0            0       281b           281b
green  open   .kibana_task_manager_1            ft60q2R8R8-nviAyc0caoQ   1   0          2            1     16.2kb         16.2kb
yellow open   filebeat-7.5.1-2020.01.10-000001  1-RGhyG9Tf-wGcepQ49mmg   1   1          0            0       283b           283b
green  open   .monitoring-alerts-7              TLxewhFyTKycI9IsjX0iVg   1   0          6            0     40.9kb         40.9kb
green  open   .monitoring-logstash-7-2020.01.10 dc_S5BhsRNuukwTxbrxvLw   1   0       4774            0      1.1mb          1.1mb
green  open   .watches                          x7QAcAQZTrab-pQuvonXpg   1   0          6            6    120.2kb        120.2kb
green  open   .ml-notifications-000001          vFYzmHorTVKZplMuW7VSmw   1   0         52            0     81.6kb         81.6kb

Now, it is time to pay a visit to our Kibana dashboard. Open your browser and enter the URL 

http://your-ip-addr-here:5601
. Now enter the predefined username and password; in our case, it is 
elastic
 and 
yourstrongpasswordhere
, respectively.

In your Kibana dashboard, go to the Management tab, and under Kibana, click on Index Patterns. In the first row, you will find the 

filebeat-*
 index, which already has been identified by Kibana.

Now, go to the Discover tag on the Kibana dashboard and view your container logs along with the metadata under the selected index pattern, which could look something like this:

Conclusion:

You have now installed and configured the ELK Stack on your host machine, which is going to collect the raw log from your Docker into the stack that later can be analyzed or can be used to debug applications.

About the author - Sudip is a Solution Architect with more than 15 years of working experience, and is the founder of Javelynn. He likes sharing his knowledge by regularly writing for HackernoonDZoneAppfleet and many more. And while he is not doing that, he must be fishing or playing chess.

Previously posted at https://appfleet.com/.





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