Lookerbot integrates Slack and Looker to put all your data at your fingertips.
With Lookerbot, everyone in your company can easily share data and answer questions instantly. Lookerbot can answer questions, send alerts, and more!
For a free trial of Looker go to looker.com/free-trial.
Detailed information on how to interact with Lookerbot can be found in the Looker Help Center.
s3:PutObjectAcl and s3:PutObject permissions.channels:readchat:write:botfiles:write:userteam:readusers:readcommands (if you plan on configuring slash commands)xoxb-.By default, Slack Apps are internal to your team. Don't "distribute" your Slack App – that will make it available to all Slack users in the world.
[!IMPORTANT] Please note: some of the Environment Variables below have changed. You may need to adjust them in order to keep this working.
The quickest way to deploy the bot is to use Heroku's one-click deploy button, which will provision a server for your bot. This will prompt you to give the app a unique name, add the Slack API key and configure all of the required variables (see "Environment Variables" below).
Once the environment variables have been set and the server has been deployed, the bot should be ready to go! You can also optionally configure slash commands.
Troubleshooting
See dependency issues on heroku? Apply
YARN_PRODUCTION=falseas env. to the deployment. See heroku skip-pruning for more details.
The bot is a simple Node.js application. The application needs to be able to reach both your Looker instance's API and Slack's API. If you have a self-hosted instance of Looker, be sure to open up port 19999 (or your core_port) in order to accesss the Looker API.
The bot is configured entirely via environment variables. You'll want to set up these variables:
SLACK_API_KEY (required) – This is where you'll put the "Bot User OAuth Access Token". You can get in the Slack app under "Install App".
LOOKER_URL (required) – The web url of your Looker instance.
LOOKER_API_BASE_URL (required) – The API endpoint of your Looker instance. In most cases, this will be the web url followed by :19999/api/4.0 (replace 19999 with your core_port if it is different).
LOOKER_API_CLIENT_ID (required) – The API client ID for the user you want the bot to run as. This requires creating an API user or an API key for an existing user in Looker.
LOOKER_API_CLIENT_SECRET (required) – The API client secret for the user you want the bot to run as. This requires creating an API user or an API key for an existing user in Looker.
LOOKER_CUSTOM_COMMAND_FOLDER_ID (optional) – The ID of a Folder that you would like the bot to use to define custom commands. Read about using custom commands in the Looker Help Center.
LOOKER_WEBHOOK_TOKEN (optional) – The webhook validation token found in Looker's admin panel. This is only required if you're using the bot to send scheduled webhooks.
SLACK_SLASH_COMMAND_TOKEN (optional) – If you want to use slash commands or interactive messages with Lookerbot, provide the verification token from the "Basic Information" section of the app settings. This is how the bot will verify the integrity of incoming slash commands.
PORT (optional) – The port that the bot web server will run on to accept slash commands. Defaults to 3333.
If you'd like to put these configuration variables on the filesystem instead, you can place them in a .env file at the root of the project as well. Environment variables will take precedence over .env settings if both are present.
There are a couple environment variables that can be used to tweak behavior:
LOOKER_SLACKBOT_LOADING_MESSAGES – Set this to false to disable posting loading messages.
LOOKERBOT_DATA_ACTIONS_IN_MESSAGES – Set this to false to disable making data action buttons available to Slack users.
SLACKBOT_S3_BUCKET (optional) – If you want to use Lookerbot to post visualization images, provide an Amazon S3 bucket name.
SLACKBOT_S3_BUCKET_REGION (optional) – If you want to use Lookerbot to post visualization images, provide an Amazon S3 bucket region. Defaults to us-east-1.
AWS_ACCESS_KEY_ID (optional) – If you want to use Lookerbot to post visualization images, provide an Amazon S3 access key that can write to the provided bucket.
AWS_SECRET_ACCESS_KEY (optional) – If you want to use Lookerbot to post visualization images, provide an Amazon S3 secret access key that can write to the provided bucket.
AZURE_STORAGE_ACCOUNT (optional) - If you want to use Microsoft Azure Storage to store visualization images posted by Lookerbot, provide the name of your Azure Storage account.
SLACKBOT_AZURE_CONTAINER (optional) - If you want to use Microsoft Azure Storage to store visualization images posted by Lookerbot, provide the name of the container within your Azure Storage account that you wish to use.
AZURE_STORAGE_ACCESS_KEY (optional) - If using Microsoft Azure Storage to store visualization images posted by Lookerbot, provide an access key that can write to the provided Azure Storage account and container.
GOOGLE_CLOUD_BUCKET (optional) - If you want to use Google Cloud to store visualization images posted by Lookerbot, provide the name of your bucket.If Lookerbot is running on Google Compute Engine, no further information should be needed if the approprate API scopes are set up.
Otherwise, you can provide credentials directly:
GOOGLE_CLOUD_PROJECT (optional) - If you want to use Google Cloud to store visualization images posted by Lookerbot, provide the name of your project.
GOOGLE_CLOUD_CREDENTIALS_JSON (optional) - If using Google Cloud to store visualization images posted by Lookerbot, provide the content of the credentials JSON file you got from the Google Cloud website.
If your Looker instance uses a self-signed certificate, Lookerbot will refuse to connect to it by default.
Setting the NODE_TLS_REJECT_UNAUTHORIZED environment variable to 0 will instruct Lookerbot to accept connections with invalid certificates. Please ensure you have thoroughly evaluated the security implications of this action for your infrastructure before setting this variable.
This should only impact on-premise deployments of Looker. Do not set this environment variable if Looker hosts your instance.
If you would like the bot to connect to multiple instances of Looker, then you can configure the bot with the LOOKERS environment variable. This variable should be JSON array of JSON objects, each representing a Looker instance and its authentication information.
The JSON objects should have the following keys:
url should be the web url of the instanceapiBaseUrl should be the API endpointclientID should be the API client ID for the user you want the bot to run asclientSecret should be the secret for that API keycustomCommandFolderId is an optional parameter, representing a Folder that you would like the bot to use to define custom commands.webhookToken is an optional parameter. It's the webhook validation token found in Looker's admin panel. This is only required if you're using the bot to send scheduled webhooks.Here's an example JSON that connects to two Looker instances:
[{"url": "https://me.looker.com", "apiBaseUrl": "https://me.looker.com:19999/api/4.0", "clientId": "abcdefghjkl", "clientSecret": "abcdefghjkl"},{"url": "https://me-staging.looker.com", "apiBaseUrl": "https://me-staging.looker.com:19999/api/4.0", "clientId": "abcdefghjkl", "clientSecret": "abcdefghjkl"}]
The LOOKER_URL, LOOKER_API_BASE_URL, LOOKER_API_CLIENT_ID, LOOKER_API_CLIENT_SECRET, LOOKER_WEBHOOK_TOKEN, and LOOKER_CUSTOM_COMMAND_FOLDER_ID variables are ignored when LOOKERS is set.
To run the server:
yarn install to install dependenciesyarn start to start the bot server. The server will run until you type Ctrl+C to stop it.The included Procfile will also allow you to run the app using foreman or node-foreman. These libraries also provide easy ways of creating scripts for use with upstart, supervisord, and systemd.
Slash commands are not required to interact with the bot. You can DM the bot directly or mention the bot like:
@looker help
and use all the functionality.
However, Slash commands are a bit friendlier to use and allow Slack to auto-complete so you'll probably want to set those up.
/slack/receive, so if your server is at https://example.com, the URL would be https://example.com/slack/receive.SLACK_SLASH_COMMAND_TOKEN environment variable.You can use the bot to send scheduled Looks to Slack.
/slack/post/channel/my-channel-name
/slack/post/group/my-channel-name
/slack/post/dm/myusernameThese URLs are prefixed with the URL of your server. (If you used the Heroku deployment, this will be the unique app name you chose). So, if your server is at https://example.com and you want to post to a channel called data-science, the URL would be https://example.com/slack/post/channel/data-science.
LOOKER_WEBHOOK_TOKEN environment variable is properly set to the same verification token found in the Looker admin panel.By default, simple data actions will appear in Slack for single value visualizations. Data actions that have forms are not currently supported.
This can be disabled on a per-action basis by using Liquid templating in the action definition to restrict access to certain users. Alternately, the action buttons can be disabled entirely with the bot configuration variable LOOKERBOT_DATA_ACTIONS_IN_MESSAGES.
There's a quick additional configuration that's needed to use Data Actions from Slack:
/slack/action, so if your server is at https://example.com, the Request URL would be https://example.com/slack/action.The bot server also implements endpoints to allow you to easily send Data Actions to Slack.
Here's an example of a few data actions you could implement in your LookML. (Replace https://example.com with your bot's hostname.)
To make use of this, you'll need to make sure that the LOOKER_WEBHOOK_TOKEN environment variable is properly set to the same verification token found in the Looker admin panel, just like with scheduling data.
dimension: value { sql: CONCAT(${first_name}, ' ', ${last_name}) ;; # Let user choose a Slack channel to send to action: { label: "Send to Slack Channel" url: "https://example.com/data_actions" form_url: "https://example.com/data_actions/form" param: { name: "message" value: ":signal_strength: I sent a value from Slack: {{rendered_value}}" } } # Send to a particular Slack channel with a preset message action: { label: "Ping Channel" url: "https://example.com/data_actions" param: { name: "message" value: ":signal_strength: I sent a value from Slack: {{rendered_value}}" } param: { name: "channel" value: "#alerts" } } # Ask the user for a message to send to a particular channel action: { label: "Ask a Question" url: "https://example.com/data_actions" form_param: { name: "message" default: "Something seems wrong... (add details)" } param: { name: "channel" value: "#alerts" } } }
We suggest creating a Looker API user specifically for Lookerbot, and using that user's API credentials. It's worth remembering that everyone who can talk to your Lookerbot has the permissions of this user. If there's data you don't want people to access via Slack, ensure that user cannot access it using Looker's permissioning


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