Quiet and Wake Sidekiq workers running on AWS
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Snow White

Quiet and resume Sidekiq workers in AWS Elastic Beanstalk environments

Snow White


  • The AWS CLI installed and configured with profiles called staging and production
  • Your AWS IAM user has access to create tasks on AWS Fargate
  • (optional) Your Slack User ID has been associated with your IAM user in AWS

Slack Installation

Within Slack, create a custom emoji called snowwhite using the emoji in the images folder. The Snow White emoji is free use and courtesy of ClipArtMax

Create an incoming Webhook according to the Slack documentation and obtain the URL.

We are using the legacy Slack webhook to post to Slack to channels. This can also DM users via Slackbot but only if the UID is known. The UID needs to be added to a tag called slack_userid on any IAM users that will invoke Snow White.

To obtain the Slack userID, visit Slack in a browser, view a user's profile and hover on Direct Messages. In the status bar of the browser, you will see the UID of the form Uxxxxxxx. It MUST begin with U. Grab this ID and add it to a tag on the user in AWS IAM

Elastic Beanstalk Configuration

Instances that you wish to use Snow White with must be running under a role that allows the SSM agent to run. Generally, just attach the managed policy AmazonEC2RoleForSSM to the role to grant the required permissions.

AWS Installation

The pieces which run in AWS are managed via Cloudformation. Create a stack using the template in the cfn folder. It takes 4 parameters:

  • CfnStackName - the name of the stack you are creating in each region (recommend: snow-white)
  • CfnWakeDocName - the logical name of the wake command (leave as default)
  • QuietCommnadName - the logical name of the quiet command (leave as default)
  • SlackWebhook - the full URL of a Slack incoming webhook
  • SlackChannel - the name of the Slack channel to send notifications to

Helper script Configuration (snow-white.sh)

A small helper script is provided (syntax below) to invoke the Snow White fargate task. Before running for the first time, you will need to set a few variables at the top of the script:

  • ECS_CLUSTER_REGION - the region that contains your ECS cluster (this does not have to be the same as the region your Sidekiq workers are in)
  • ECS_CLUSTER_NAME - name of a pre-existing cluster to spin up Fargate tasks in
  • vpc_id - the ID of a VPC to create Fargate tasks in
  • subnet_id - the ID of a subnet in the VPC to create tasks in
  • sec_group - the ID of a security group to attach to the Fadget tasks (this does not need to allow any inbound ports)


Clone this repo and run the snow-white.sh helper script.

usage: usage: snow-white -a quiet|wake -e <EB env name pattern> -f staging|production -p <EB app name> -r <region>


  • -a designates if we are quieting or waking the workers
  • -e is a filter for beanstalk environment names to match that are running Sidekiq workers (ie. workers)
  • -p is the Elastic beanstalk application name
  • -r is the AWS region (ie. us-east-1)
  • -f is the AWS profile to use

Example: ./snowwhite.sh -a quiet -e workers -p MY-EB-APP -r us-east-1 -f staging

This will submit a task to AWS Fargate which will in turn run an AWS SSM command on each instance of all Sidekiq workers in the EB application whose environment names contain the string workers. The Fargate task will then monitor each worker until the queue is drained and will report back via Slack

Moving Parts

Snow White consists of a few moving parts.

SSM Run Commands

These are contained in the ssm folder of this repo. These are the parts that do the real work to quiet or wake the Sidekiq workers and are referenced in AWS SSM documents in the Cloudformation template. SSM will pull the scripts from this repo at execution time using the aws:downloadContent action in the SSM document.

Fargate container

We need a long running task to actually invoke the SSM command and notify us when it is complete. Ideally, this would be a Lambda but as Sidekiq workers can be busy for hours after reciving the quiet signal, the best solution is a Docket container run on demand in Fargate. This container finds the EC2 instances that are part of the Elastic Beanstalk environments and then invokes the SSM command to quiet or wake the Sidekiq workers on them. It will poll under the command reports complete and then notify via Slack with the final status.