Docker方式部署ELK

目录

l     Elasticsearch. 2

Install Elasticsearch with Docker 2

Pulling the image. 2

Starting a single node cluster with Docker 2

Starting a multi-node cluster with Docker Compose. 2

Using the Docker images in production. 6

Configuring Elasticsearch with Docker 9

Next steps. 11

l     Filebeat 12

Pull the image. 12

Run the Filebeat setup. 12

Configure Filebeat on Docker 12

Example configuration file. 13

Volume-mounted configuration. 13

Customize your configuration. 14

Custom image configuration. 14

l     Kibana. 15

Install Kibana with Docker 15

Run Kibana on Docker for development 15

Stop Docker containers. 16

Configure Kibana on Docker 16

l     Logstash. 18

Running Logstash on Docker 18

Pulling the image. 18

Install Elasticsearch with Docker

Elasticsearch is also available as Docker images. The images use centos:8 as the base image.

A list of all published Docker images and tags is available at www.docker.elastic.co. The source files are in Github.

This package contains both free and subscription features. Start a 30-day trial to try out all of the features.

Pulling the image

Obtaining Elasticsearch for Docker is as simple as issuing a docker pull command against the Elastic Docker registry.

docker pull docker.elastic.co/elasticsearch/elasticsearch:7.13.4

Starting a single node cluster with Docker

To start a single-node Elasticsearch cluster for development or testing, specify single-node discovery to bypass the bootstrap checks:

docker run -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.13.4

Starting a multi-node cluster with Docker Compose

To get a three-node Elasticsearch cluster up and running in Docker, you can use Docker Compose:

  1. Create a docker-compose.yml file:
version: '2.2'
services:
  es01:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.13.4
    container_name: es01
    environment:
      - node.name=es01
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es02,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - data01:/usr/share/elasticsearch/data
    ports:
      - 9200:9200
    networks:
      - elastic
  es02:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.13.4
    container_name: es02
    environment:
      - node.name=es02
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es01,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - data02:/usr/share/elasticsearch/data
    networks:
      - elastic
  es03:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.13.4
    container_name: es03
    environment:
      - node.name=es03
      - cluster.name=es-docker-cluster
      - discovery.seed_hosts=es01,es02
      - cluster.initial_master_nodes=es01,es02,es03
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - data03:/usr/share/elasticsearch/data
    networks:
      - elastic
 
volumes:
  data01:
    driver: local
  data02:
    driver: local
  data03:
    driver: local
 
networks:
  elastic:
    driver: bridge

This sample docker-compose.yml file uses the ES_JAVA_OPTS environment variable to manually set the heap size to 512MB. We do not recommend using ES_JAVA_OPTS in production. See Manually set the heap size.

This sample Docker Compose file brings up a three-node Elasticsearch cluster. Node es01 listens on localhost:9200 and es02 and es03 talk to es01 over a Docker network.

Please note that this configuration exposes port 9200 on all network interfaces, and given how Docker manipulates iptables on Linux, this means that your Elasticsearch cluster is publically accessible, potentially ignoring any firewall settings. If you don’t want to expose port 9200 and instead use a reverse proxy, replace 9200:9200 with 127.0.0.1:9200:9200 in the docker-compose.yml file. Elasticsearch will then only be accessible from the host machine itself.

The Docker named volumes data01data02, and data03 store the node data directories so the data persists across restarts. If they don’t already exist, docker-compose creates them when you bring up the cluster.

  1. Make sure Docker Engine is allotted at least 4GiB of memory. In Docker Desktop, you configure resource usage on the Advanced tab in Preference (macOS) or Settings (Windows).

Docker Compose is not pre-installed with Docker on Linux. See docs.docker.com for installation instructions: Install Compose on Linux

  • Run docker-compose to bring up the cluster:
docker-compose up
  • Submit a _cat/nodes request to see that the nodes are up and running、healthy:
curl -X GET "localhost:9200/_cat/nodes?v=true&pretty"
curl -X GET "localhost:9200/_cluster/health?pretty"

Log messages go to the console and are handled by the configured Docker logging driver. By default you can access logs with docker logs. If you would prefer the Elasticsearch container to write logs to disk, set the ES_LOG_STYLE environment variable to file. This causes Elasticsearch to use the same logging configuration as other Elasticsearch distribution formats.

To stop the cluster, run docker-compose down. The data in the Docker volumes is preserved and loaded when you restart the cluster with docker-compose up. To delete the data volumes when you bring down the cluster, specify the -v option: docker-compose down -v.

Start a multi-node cluster with TLS enabled

See Encrypting communications in an Elasticsearch Docker Container and Run the Elastic Stack in Docker with TLS enabled.

Using the Docker images in production

The following requirements and recommendations apply when running Elasticsearch in Docker in production.

Set vm.max_map_count to at least 262144

The vm.max_map_count kernel setting must be set to at least 262144 for production use.

How you set vm.max_map_count depends on your platform:

  • Linux

The vm.max_map_count setting should be set permanently in /etc/sysctl.conf:

grep vm.max_map_count /etc/sysctl.conf
vm.max_map_count=262144

To apply the setting on a live system, run:

sysctl -w vm.max_map_count=262144

The vm.max_map_count setting must be set within the xhyve virtual machine:

  1. From the command line, run:
screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty
  • Press enter and use`sysctl` to configure vm.max_map_count:
sysctl -w vm.max_map_count=262144
  • To exit the screen session, type Ctrl a d.
  • Windows and macOS with Docker Desktop

The vm.max_map_count setting must be set via docker-machine:

docker-machine ssh
sudo sysctl -w vm.max_map_count=262144

The vm.max_map_count setting must be set in the docker-desktop container:

wsl -d docker-desktop
sysctl -w vm.max_map_count=262144

Configuration files must be readable by the elasticsearch user

By default, Elasticsearch runs inside the container as user elasticsearch using uid:gid 1000:0.

One exception is Openshift, which runs containers using an arbitrarily assigned user ID. Openshift presents persistent volumes with the gid set to 0, which works without any adjustments.

If you are bind-mounting a local directory or file, it must be readable by the elasticsearch user. In addition, this user must have write access to the config, data and log dirs (Elasticsearch needs write access to the config directory so that it can generate a keystore). A good strategy is to grant group access to gid 0 for the local directory.

For example, to prepare a local directory for storing data through a bind-mount:

mkdir esdatadir
chmod g+rwx esdatadir
chgrp 0 esdatadir

You can also run an Elasticsearch container using both a custom UID and GID. Unless you bind-mount each of the config, data` and logs directories, you must pass the command line option --group-add 0 to docker run. This ensures that the user under which Elasticsearch is running is also a member of the root (GID 0) group inside the container.

As a last resort, you can force the container to mutate the ownership of any bind-mounts used for the data and log dirs through the environment variable TAKE_FILE_OWNERSHIP. When you do this, they will be owned by uid:gid 1000:0, which provides the required read/write access to the Elasticsearch process.

Increase ulimits for nofile and nproc

Increased ulimits for nofile and nproc must be available for the Elasticsearch containers. Verify the init system for the Docker daemon sets them to acceptable values.

To check the Docker daemon defaults for ulimits, run:

docker run --rm centos:8 /bin/bash -c 'ulimit -Hn && ulimit -Sn && ulimit -Hu && ulimit -Su'

If needed, adjust them in the Daemon or override them per container. For example, when using docker run, set:

--ulimit nofile=65535:65535

Disable swappingedit

Swapping needs to be disabled for performance and node stability. For information about ways to do this, see Disable swapping.

If you opt for the bootstrap.memory_lock: true approach, you also need to define the memlock: true ulimit in the Docker Daemon, or explicitly set for the container as shown in the sample compose file. When using docker run, you can specify:

-e "bootstrap.memory_lock=true" --ulimit memlock=-1:-1

Randomize published ports

The image exposes TCP ports 9200 and 9300. For production clusters, randomizing the published ports with --publish-all is recommended, unless you are pinning one container per host.

Manually set the heap size

By default, Elasticsearch automatically sizes JVM heap based on a nodes’s roles and the total memory available to the node’s container. We recommend this default sizing for most production environments. If needed, you can override default sizing by manually setting JVM heap size.

To manually set the heap size in production, bind mount a JVM options file under /usr/share/elasticsearch/config/jvm.options.d that includes your desired heap size settings.

For testing, you can also manually set the heap size using the ES_JAVA_OPTS environment variable. For example, to use 16GB, specify -e ES_JAVA_OPTS="-Xms16g -Xmx16g" with docker run. The ES_JAVA_OPTS variable overrides all other JVM options. The ES_JAVA_OPTS variable overrides all other JVM options. We do not recommend using ES_JAVA_OPTS in production. The docker-compose.yml file above sets the heap size to 512MB.

Pin deployments to a specific image version

Pin your deployments to a specific version of the Elasticsearch Docker image. For example docker.elastic.co/elasticsearch/elasticsearch:7.13.4.

Always bind data volumes

You should use a volume bound on /usr/share/elasticsearch/data for the following reasons:

  1. The data of your Elasticsearch node won’t be lost if the container is killed
  2. Elasticsearch is I/O sensitive and the Docker storage driver is not ideal for fast I/O
  3. It allows the use of advanced Docker volume plugins

Avoid using loop-lvm mode

If you are using the devicemapper storage driver, do not use the default loop-lvm mode. Configure docker-engine to use direct-lvm.

Centralize your logs

Consider centralizing your logs by using a different logging driver. Also note that the default json-file logging driver is not ideally suited for production use.

Configuring Elasticsearch with Docker

When you run in Docker, the Elasticsearch configuration files are loaded from /usr/share/elasticsearch/config/.

To use custom configuration files, you bind-mount the files over the configuration files in the image.

You can set individual Elasticsearch configuration parameters using Docker environment variables. The sample compose file and the single-node example use this method.

To use the contents of a file to set an environment variable, suffix the environment variable name with _FILE. This is useful for passing secrets such as passwords to Elasticsearch without specifying them directly.

For example, to set the Elasticsearch bootstrap password from a file, you can bind mount the file and set the ELASTIC_PASSWORD_FILE environment variable to the mount location. If you mount the password file to /run/secrets/bootstrapPassword.txt, specify:

-e ELASTIC_PASSWORD_FILE=/run/secrets/bootstrapPassword.txt

You can also override the default command for the image to pass Elasticsearch configuration parameters as command line options. For example:

docker run <various parameters> bin/elasticsearch -Ecluster.name=mynewclustername

While bind-mounting your configuration files is usually the preferred method in production, you can also create a custom Docker image that contains your configuration.

Mounting Elasticsearch configuration files

Create custom config files and bind-mount them over the corresponding files in the Docker image. For example, to bind-mount custom_elasticsearch.yml with docker run, specify:

-v full_path_to/custom_elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml

The container runs Elasticsearch as user elasticsearch using uid:gid 1000:0. Bind mounted host directories and files must be accessible by this user, and the data and log directories must be writable by this user.

Mounting an Elasticsearch keystore

By default, Elasticsearch will auto-generate a keystore file for secure settings. This file is obfuscated but not encrypted. If you want to encrypt your secure settings with a password, you must use the elasticsearch-keystore utility to create a password-protected keystore and bind-mount it to the container as /usr/share/elasticsearch/config/elasticsearch.keystore. In order to provide the Docker container with the password at startup, set the Docker environment value KEYSTORE_PASSWORD to the value of your password. For example, a docker run command might have the following options:

-v full_path_to/elasticsearch.keystore:/usr/share/elasticsearch/config/elasticsearch.keystore
-E KEYSTORE_PASSWORD=mypassword

Using custom Docker images

In some environments, it might make more sense to prepare a custom image that contains your configuration. A Dockerfile to achieve this might be as simple as:

FROM docker.elastic.co/elasticsearch/elasticsearch:7.13.4
COPY --chown=elasticsearch:elasticsearch elasticsearch.yml /usr/share/elasticsearch/config/

You could then build and run the image with:

docker build --tag=elasticsearch-custom .
docker run -ti -v /usr/share/elasticsearch/data elasticsearch-custom

Some plugins require additional security permissions. You must explicitly accept them either by:

  • Attaching a tty when you run the Docker image and allowing the permissions when prompted.
  • Inspecting the security permissions and accepting them (if appropriate) by adding the --batch flag to the plugin install command.

See Plugin management for more information.

Next steps

You now have a test Elasticsearch environment set up. Before you start serious development or go into production with Elasticsearch, you must do some additional setup:

Pull the image

Obtaining Filebeat for Docker is as simple as issuing a docker pull command against the Elastic Docker registry.

docker pull docker.elastic.co/beats/filebeat:7.13.4

Alternatively, you can download other Docker images that contain only features available under the Apache 2.0 license. To download the images, go to www.docker.elastic.co.

Run the Filebeat setup

Running Filebeat with the setup command will create the index pattern and load visualizations , dashboards, and machine learning jobs. Run this command:

docker run \

docker.elastic.co/beats/filebeat:7.13.4 \

setup -E setup.kibana.host=kibana:5601 \

-E output.elasticsearch.hosts=[“elasticsearch:9200”] 

Substitute your Kibana and Elasticsearch hosts and ports.
If you are using the hosted Elasticsearch Service in Elastic Cloud, replace the -E output.elasticsearch.hosts line with the Cloud ID and elastic password using this syntax:

-E cloud.id=<Cloud ID from Elasticsearch Service> \

-E cloud.auth=elastic:<elastic password>

Configure Filebeat on Docker

The Docker image provides several methods for configuring Filebeat. The conventional approach is to provide a configuration file via a volume mount, but it’s also possible to create a custom image with your configuration included.

Example configuration file

Download this example configuration file as a starting point:

curl -L -O https://raw.githubusercontent.com/elastic/beats/7.13/deploy/docker/filebeat.docker.yml

Volume-mounted configuration

One way to configure Filebeat on Docker is to provide filebeat.docker.yml via a volume mount. With docker run, the volume mount can be specified like this.

docker run -d \

  –name=filebeat \

  –user=root \

  –volume=”$(pwd)/filebeat.docker.yml:/usr/share/filebeat/filebeat.yml:ro” \

  –volume=”/var/lib/docker/containers:/var/lib/docker/containers:ro” \

  –volume=”/var/run/docker.sock:/var/run/docker.sock:ro” \

  docker.elastic.co/beats/filebeat:7.13.4 filebeat -e -strict.perms=false \

  -E output.elasticsearch.hosts=[“elasticsearch:9200”] 

Substitute your Elasticsearch hosts and ports.
If you are using the hosted Elasticsearch Service in Elastic Cloud, replace the -E output.elasticsearch.hosts line with the Cloud ID and elastic password using the syntax shown earlier.

Customize your configuration

The filebeat.docker.yml file you downloaded earlier is configured to deploy Beats modules based on the Docker labels applied to your containers. See Hints based autodiscover for more details. Add labels to your application Docker containers, and they will be picked up by the Beats autodiscover feature when they are deployed. Here is an example command for an Apache HTTP Server container with labels to configure the Filebeat and Metricbeat modules for the Apache HTTP Server:

docker run \

  –label co.elastic.logs/module=apache2 \

  –label co.elastic.logs/fileset.stdout=access \

  –label co.elastic.logs/fileset.stderr=error \

  –label co.elastic.metrics/module=apache \

  –label co.elastic.metrics/metricsets=status \

  –label co.elastic.metrics/hosts=’${data.host}:${data.port}’ \

  –detach=true \

  –name my-apache-app \

  -p 8080:80 \

  httpd:2.4

Custom image configuration

It’s possible to embed your Filebeat configuration in a custom image. Here is an example Dockerfile to achieve this:

FROM docker.elastic.co/beats/filebeat:7.13.4

COPY filebeat.yml /usr/share/filebeat/filebeat.yml

USER root

RUN chown root:filebeat /usr/share/filebeat/filebeat.yml

USER filebeat

Final,

–user     run as root;

–volume      mapping local path;

docker run -it –name filebeat –user=root –net root_elastic –volume=”/root/filebeat/filebeat.docker.yml:/usr/share/filebeat/filebeat.yml:ro” –volume=”/var/log/nginx/:/var/log/nginx/” –volume=”/var/lib/docker/containers:/var/lib/docker/containers:ro” –volume=”/var/run/docker.sock:/var/run/docker.sock:ro” docker.elastic.co/beats/filebeat:7.13.4

Install Kibana with Docker

Docker images for Kibana are available from the Elastic Docker registry. The base image is centos:7.

A list of all published Docker images and tags is available at www.docker.elastic.co. The source code is in GitHub.

These images contain both free and subscription features. Start a 30-day trial to try out all of the features.

Run Kibana on Docker for development

To start an Elasticsearch container for development or testing, run:

docker network create elastic
docker pull docker.elastic.co/elasticsearch/elasticsearch:7.13.4
docker run --name es01-test --net elastic -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.13.4

To start Kibana and connect it to your Elasticsearch container, run the following commands in a new terminal session:

docker pull docker.elastic.co/kibana/kibana:7.13.4
docker run --name kib01-test --net elastic -p 5601:5601 -e "ELASTICSEARCH_HOSTS=http://es01-test:9200" docker.elastic.co/kibana/kibana:7.13.4

To access Kibana, go to http://localhost:5601.

Stop Docker containers

To stop your containers, run:

docker stop es01-test
docker stop kib01-test

To remove the containers and their network, run:

docker network rm elastic
docker rm es01-test
docker rm kib01-test

Configure Kibana on Docker

The Docker images provide several methods for configuring Kibana. The conventional approach is to provide a kibana.yml file as described in Configuring Kibana, but it’s also possible to use environment variables to define settings.

Bind-mounted configuration

One way to configure Kibana on Docker is to provide kibana.yml via bind-mounting. With docker-compose, the bind-mount can be specified like this:

version: '2'
services:
  kibana:
    image: docker.elastic.co/kibana/kibana:7.13.4
    volumes:
      - ./kibana.yml:/usr/share/kibana/config/kibana.yml

Environment variable configuration

Under Docker, Kibana can be configured via environment variables. When the container starts, a helper process checks the environment for variables that can be mapped to Kibana command-line arguments.

For compatibility with container orchestration systems, these environment variables are written in all capitals, with underscores as word separators. The helper translates these names to valid Kibana setting names.

All information that you include in environment variables is visible through the ps command, including sensitive information.

Some example translations are shown here:

Table 1. Example Docker Environment Variables

Environment VariableKibana Setting
SERVER_NAMEserver.name
SERVER_BASEPATHserver.basePath
MONITORING_ENABLEDmonitoring.enabled

In general, any setting listed in Configure Kibana can be configured with this technique.

These variables can be set with docker-compose like this:

version: '2'
services:
  kibana:
    image: docker.elastic.co/kibana/kibana:7.13.4
    environment:
      SERVER_NAME: kibana.example.org
      ELASTICSEARCH_HOSTS: http://elasticsearch.example.org

Since environment variables are translated to CLI arguments, they take precedence over settings configured in kibana.yml.

Docker defaults

The following settings have different default values when using the Docker images:

server.host"0"
elasticsearch.hostshttp://elasticsearch:9200
monitoring.ui.container.elasticsearch.enabledtrue

These settings are defined in the default kibana.yml. They can be overridden with a custom kibana.yml or via environment variables.

Final,

docker run -dit --name kibana-out --net root_elastic -p 5601:5601 -e "ELASTICSEARCH_HOSTS=http://172.20.0.2:9200" docker.elastic.co/kibana/kibana:7.13.4

Running Logstash on Docker

Docker images for Logstash are available from the Elastic Docker registry. The base image is centos:7.

A list of all published Docker images and tags is available at www.docker.elastic.co. The source code is in GitHub.

These images are free to use under the Elastic license. They contain open source and free commercial features and access to paid commercial features. Start a 30-day trial to try out all of the paid commercial features. See the Subscriptions page for information about Elastic license levels.

Pulling the image

Obtaining Logstash for Docker is as simple as issuing a docker pull command against the Elastic Docker registry.

docker pull docker.elastic.co/logstash/logstash:7.13.4

Alternatively, you can download other Docker images that contain only features available under the Apache 2.0 license. To download the images, go to www.docker.elastic.co.

Final,

docker run -dit -p 5044:5044 –name logstash –net root_elastic -v ~/logstash/logstash.yml:/usr/share/logstash/config/logstash.yml -v ~/logstash/conf.d/:/usr/share/logstash/conf.d/ docker.elastic.co/logstash/logstash:7.13.4

参考链接https://www.cnblogs.com/fbtop/p/11005469.html

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