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Clustering Looker

This tutorial explains the recommended method of creating a clustered Looker configuration.


The Looker application can run single-node or clustered:

There are two primary reasons an organization would want to run Looker as a cluster:

Depending on the scaling issues, a clustered Looker may not provide the solution. For example, if a small number of large queries are using up the system memory, the only solution is to increase the available memory for the Looker process.

Load balancing alternatives

Before load balancing Looker, consider increasing the memory and possibly the CPU count of a single server that runs Looker. Looker recommends setting up detailed performance monitoring for memory and CPU utilization to ensure that the Looker server is properly sized for its workload.

Large queries need more memory for better performance. Clustering can provide performance gains when many users are running small queries.

For configurations with up to 50 users who use Looker lightly, Looker recommends running a single server at the equivalent of a large sized AWS EC2 instance (M4.large: 8GB of RAM, 2 CPU cores). For configurations with more users or many active power users, watch whether the CPU spikes or if users notice slowness in the application. If so, move Looker to a larger server or run a clustered Looker configuration.

Improved availability/failover

Running Looker in a clustered environment can mitigate downtime in the case of an outage. High availability is especially important if the Looker API is used in core business systems or if Looker is embedded into customer-facing products.

In a clustered Looker configuration, a proxy server or load balancer will reroute traffic when it determines that one node is down. Looker automatically handles nodes leaving and joining the cluster.

Required components

The following components are required for a clustered Looker configuration:

The following diagram illustrates how the components interact:

MySQL application database

Looker uses an application database (often called an internal database) to hold application data. When running Looker as a single-node application, Looker normally uses an in-memory HyperSQL database.

In a clustered Looker configuration, each node’s Looker must point at a shared transactional database (the shared application or internal database). Support for the application database for clustered Lookers is as follows:

Looker does not manage the maintenance and backups of that database. However, since the database hosts almost all the Looker application configuration data, it should be provisioned as a high-availability database and backed up at least daily.

Looker nodes

Each node is a server with the Looker Java process running on it. The servers in the Looker cluster need to be able to reach each other and the Looker application database. The default ports are listed later in this page.

Load balancer

To balance the load or redirect requests to available nodes, a load balancer or proxy server (e.g. NGINX or AWS ELB) is required to direct traffic to each Looker node. The load balancer handles health checks. In the event of a node failure, the load balancer must be configured to reroute traffic to the remaining healthy nodes.

When choosing and configuring the load balancer, ensure that it can be configured to operate as Layer 4 only. The Amazon Classic ELB is one such example. In addition, the load balancer should have a long timeout (3600 seconds) to prevent queries from being killed.

Shared file system

You must use a POSIX-compliant shared file system (such as NFS, AWS EFS, Gluster, BeeGFS, Lustre, or many others). Looker uses the shared file system as a repository for various pieces of information used by all the nodes in the cluster.

Installing applications and tools from the Looker Marketplace requires the use of a shared (network) file system.

Looker application (JAR executable)

You must use a Looker application JAR file that is Looker 3.56 or higher.

Starting in Looker 6.18, the Looker JAR file has been split into two separate JAR files: the Looker core JAR file and a Looker dependencies JAR file. If you are installing or updating to Looker 6.18 or later, be sure to download both JAR files.

Looker strongly recommends that each node in a cluster run the same Looker release and patch version, as discussed later in this page.

Setting up the cluster

The following tasks are required:

  1. Install Looker
  2. Set up a MySQL application database
  3. Set up the shared file system
  4. Share the SSH key repository (depending on your situation)
  5. Open the ports for the nodes to communicate
  6. Start Looker on the nodes

Installing Looker

Ensure that you have Looker installed on each node, using the Looker application JAR files and the directions on the Customer-Hosted Installation Steps page.

Setting up a MySQL application database

For a clustered Looker configuration, the application database must be a MySQL database. If you have an existing non-clustered Looker instance that is using HyperSQL for the application database, you must migrate the application data from the HyperSQL data to your new shared MySQL application database.

Make sure to back up your Looker directory. The migration process can only go from a HyperSQL database to a MySQL database, not in reverse.

See the Migrating to MySQL documentation page for information about backing up Looker and then migrating the application database from HyperSQL to MySQL.

Setting up the shared file system

Only specific file types — model files, deploy keys, plugins, and potentially application manifest files — belong in the shared file system. To set up the shared file system:

  1. On the server that will store the shared file system, verify that you have access to another account that can su to the Looker user account.
  2. On the server for the shared file system, log in to the Looker user account.
  3. If Looker is currently running, shut down your Looker configuration.
  4. If you were previously clustering using inotify Linux scripts then stop those scripts, remove them from cron, and delete them.
  5. Create a network share and mount it on each node in the cluster. Make sure that it is configured to automount on each node, and that the Looker user has the ability to read and write to it. For this example, we will call the network share /mnt/looker-share.
  6. On one node, move your deploy keys, plugins, and the looker/models and looker/models-user-* directories, which store your model files, to your network share. For example:

    mv looker/models /mnt/looker-share/
    mv looker/models-user-* /mnt/looker-share/
  7. For each node, add the --shared-storage-dir setting to the LOOKERARGS. Specify the network share, as shown in this example:

    --shared-storage-dir /mnt/looker-share

    LOOKERARGS should be added to $HOME/looker/lookerstart.cfg so that the settings are not affected by updates. If your LOOKERARGS are not listed in that file, then someone may have added them directly to the $HOME/looker/looker shell script.

    Each node in the cluster must write to a unique /log directory — or at least a unique log file.

Sharing the SSH key repository

The following procedure requires modifying the Looker user’s $HOME/.ssh directory. This can make it difficult to log in and fix something if there are errors in the config. Make sure you have access to another account that can su to the looker user account before you perform these steps.

Set up the SSH key repository to be shared:

  1. On the shared file server, create a directory called ssh-share. For example: /mnt/looker-share/ssh-share.

    Make sure the ssh-share directory is owned by the Looker user and the permissions are 700. Also, make sure that directories above the ssh-share directory (like /mnt and /mnt/looker-share) are not world-writable or group-writable.

  2. On one node, copy the contents of $HOME/.ssh to the new ssh-share directory. For example:

    cp $HOME/.ssh/* /mnt/looker-share/ssh-share

  3. For each node, make a backup of the existing SSH file and create a symlink to the ssh-share directory. For example:

    cd $HOME
    mv .ssh .ssh_bak
    ln -s /mnt/looker-share/ssh-share .ssh

    Be sure to do this step for every node.

Opening the ports for the nodes to communicate

Clustered Looker nodes communicate to each other over HTTPS with self-signed certificates and an additional authentication scheme based on rotating secrets in the application database.

The default ports that must be open between cluster nodes are 1551 and 61616. These ports are configurable by using the startup flags listed here. We highly recommend restricting network access to these ports to allow traffic only between the cluster hosts.

Starting Looker on the nodes

Restart the server on each node with the required startup flags.

Each node in a cluster must run the same release and patch version.

Available startup flags

The following table shows available startup flags, including the flags that are required to start or join a cluster:

Flag Required? Values Purpose
--clustered Yes Add flag to specify that this node is running in clustered mode.
-H or --hostname Yes The hostname that other nodes use to contact this node, such as the node’s IP address or its system hostname. Must be different from the hostnames of all other nodes in the cluster.
-n No 1551 The port for inter-node communication. The default is 1551. All nodes must use the same port number for inter-node communication.
-q No 61616 The port for queueing cluster-wide events. The default is 61616.
-d Yes /path/to/looker-db.yml The path to the file that holds the credentials for the Looker application database.
--shared-storage-dir Yes /path/to/mounted/shared/storage The option should point to the shared directory setup earlier on this page that holds the looker/model and looker/models-user-* directories.

Your --clustered startup flag should not include a value.

Example of LOOKERARGS and specifying database credentials

Place the Looker startup flags in a lookerstart.cfg file, located in the same directory as the Looker JAR files.

For example, you might want to tell Looker:

You would specify:

LOOKERARGS="-d looker-db.yml --clustered -H"

Be sure to specify the correct IP address for your node.

The looker-db.yml file would contain the database credentials, such as:

host: your.db.hostname.com username: db_user database: looker dialect: mysql port: 3306 password: secretPassword

And, if your MySQL database requires an SSL connection, the looker-db.yml file also requires the following:

ssl: true

Follow best practice security considerations when saving credentials to a file. Ideally, set the looker-db.yml file permissions to 600, owned by the Linux “user” account under which the Looker application is executed. This file should never be checked into a Git repository.

If you do not want to store the configuration in the looker-db.yml file on disk, you can configure the environment variable LOOKER_DB to contain a list of keys/values for each line in the looker-db.yml file. For example:

export LOOKER_DB="dialect=mysql&host=localhost&username=root&password=&database=looker&port=3306"

Finding your Git SSH deploy keys

Where Looker stores Git SSH deploy keys depends on the release in which the project was created:

Modifying a Looker cluster

After creating a Looker cluster, you can add or remove nodes without making changes to the other clustered nodes.

Updating a cluster to a new Looker release

Updates may involve schema changes to Looker’s internal database that would not be compatible with previous versions of Looker. To update Looker, there are two methods.

Safer method

  1. Create a backup of the application database.
  2. Stop all of the cluster’s nodes.
  3. Replace the JAR files on each server.
  4. Start each node one at a time.

Faster method

This method decreases downtime but will lose any changes made between creating the replica and pointing the proxy server to the new nodes. For example, if someone adds users or creates Looks during the transition, those changes might not be captured in the new application database.

To update using this faster but less complete method:

  1. Create a replica of Looker’s application database.
  2. Start a new cluster pointed at the replica.
  3. Point the proxy server or load balancer to the new nodes, after which you can stop the old nodes.