Dec 11, 2018 # MacOS $ mv rkedarwin-amd64 rke # Linux $ mv rkelinux-amd64 rke # Windows PowerShell mv rkewindows-amd64.exe rke.exe make executable $ chmod +x rke double check via checkin rke version $./rke -version c. Run RKE $ rke up -config./rancher-cluster.yml After installation doen you should be able to see kubeconfigrancher-cluster.yml.

There are two easy ways to create a cluster.yml: Using our minimal cluster.yml and updating it based on the node that you will be using. Using rke config to query for all the information needed. Using rke config. Run rke config to create a new cluster.yml in the current directory. This command will prompt you for all the information needed to build a cluster. When you have made changes to rancher-cluster.yml, you will have to run rke remove -config rancher-cluster.yml to clean the nodes, so it cannot conflict with previous configuration errors. Failed to deploy addon execute job rke-user-includes-addons: Failed to get job complete status.

This is an unsupported scenario, see https://github.com/rancher/rancher/issues/14731 when there is an official solution.

When cattle-cluster-agent and/or cattle-node-agent are accidentally deleted, or when server-url/cacerts are changed.

Generate definitions

• Generate API token in the UI (user -> API & Keys) and save the Bearer token
• Find the clusterid in the Rancher UI (format is c-xxxxx), its in the address bar when the cluster is selected
• Generate agent definitions (needs curl, jq)

Apply definitions

The generated command needs to be executed using kubectl configured with a kubeconfig to talk to the cluster. See the gists below to retrieve the kubeconfig:

• Get kubeconfig for custom cluster in Rancher 2.x: https://gist.github.com/superseb/f6cd637a7ad556124132ca39961789a4
• Retrieve kubeconfig from RKE v0.1.x or Rancher v2.0.x/v2.1.x custom cluster controlplane node: https://gist.github.com/superseb/3d8de6092ebc4b1581185197583f472a
• Retrieve kubeconfig from RKE v0.2.x or Rancher v2.2.x custom cluster controlplane node: https://gist.github.com/superseb/b14ed3b5535f621ad3d2aa6a4cd6443b

1. Generate kubeconfig on node with controlplane role

2. Apply definitions (replace with the command returned from generating the definitions)

Elasticsearch is also available as Docker images.The images use centos:7 as the base image.

A list of all published Docker images and tags is available atwww.docker.elastic.co. The source filesare inGithub.

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

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

Alternatively, you can download other Docker images that contain only featuresavailable under the Apache 2.0 license. To download the images, go towww.docker.elastic.co.

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

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

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 howDocker 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 usea 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 volumesdata01, data02, 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

2. Run docker-compose to bring up the cluster:

3. Submit a _cat/nodes request to see that the nodes are up and running:

Log messages go to the console and are handled by the configured Docker logging driver.By default you can access logs with docker logs.

To stop the cluster, run docker-compose down.The data in the Docker volumes is preserved and loadedwhen 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.

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

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

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:

  To apply the setting on a live system, run:

• macOS with Docker for Mac

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

  1. From the command line, run:

  2. Press enter and use`sysctl` to configure vm.max_map_count:

  3. 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:

By default, Elasticsearch runs inside the container as user elasticsearch usinguid: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 data and log dirs.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:

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

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

To check the Docker daemon defaults for ulimits, run:

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

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 theDocker Daemon,or explicitly set for the container as shown in the sample compose file.When using docker run, you can specify:

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

To configure the heap size, you can bind mount a JVM optionsfile under /usr/share/elasticsearch/config/jvm.options.d that includes yourdesired heap size settings. Note that while the default rootjvm.options file sets a default heap of 1 GB, any value you set in abind-mounted JVM options file will override it.

While setting the heap size via bind-mounted JVM options is the recommendedmethod, you can also configure this by using the ES_JAVA_OPTS environmentvariable to set the heap size. For example, to use 16 GB, specify-e ES_JAVA_OPTS='-Xms16g -Xmx16g' with docker run. Note that while thedefault root jvm.options file sets a default heap of 1 GB, any value you setin ES_JAVA_OPTS will override it. The docker-compose.yml file above sets the heap size to 512 MB.

You must configure the heap size even if you arelimitingmemory access to the container.

Pin your deployments to a specific version of the Elasticsearch Docker image. Forexample docker.elastic.co/elasticsearch/elasticsearch:7.8.0.

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 advancedDocker volume plugins

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

Consider centralizing your logs by using a differentlogging driver. Alsonote that the default json-file logging driver is not ideally suited forproduction use.

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 filesover the configuration files in the image.

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

To use the contents of a file to set an environment variable, suffix the environmentvariable name with _FILE. This is useful for passing secrets such as passwords to Elasticsearchwithout specifying them directly.

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

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

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

Rke Standalone For Macos Cluster.yml Windows 7

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:

The container runs Elasticsearch as user elasticsearch usinguid: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.

Rke Standalone For Macos Cluster.yml Download

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

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

You could then build and run the image with:

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

Rke Standalone For Macos Cluster.yml 1

• 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 managementfor more information.

You now have a test Elasticsearch environment set up. Before you startserious development or go into production with Elasticsearch, you must do some additionalsetup:

• Learn how to configure Elasticsearch.
• Configure important Elasticsearch settings.
• Configure important system settings.