Administrative Variables, Monitoring, and Logging

This document describes setting enviornment variables for installed Builders, metrics for monitoring your CircleCI installation, and logging integration in the following sections:

Setting Environment Variables

Several aspects of CircleCI Builder behavior can be customized by passing environment variables into the builder process.

If you are using the trial installation option on a single VM, then you can create a file called /etc/circle-installation-customizations with entries like export CIRCLE_OPTION_A=foo to set environment variables.


Enable the Cloudwatch by going to Replicated Admin > Settings > Monitoring > Enable Cloudwatch. Note: CloudWatch does not support monitoring of macOS containers.

CloudWatch already monitors the health and basic checks for the EC2 instances, for example, CPU, memory, disk space, and basic counts with alerts. Consider upgrading machine types for the Services instance or decrease the number of containers per container if CPU or memory become a bottleneck.

There is a blog post series wherein CircleCI engineering spent time running simulations of cost savings for the purpose of developing a general set of best practices for Auto Scaling. Consider the following best practices when setting up AWS Auto Scaling:

  1. In general, size your build cluster large enough to avoid queueing builds. That is, less than one second of queuing for most workloads and less than 10 seconds for workloads run on expensive hardware or at highest parallellism. Sizing to reduce queuing to zero is best practice because of the high cost of developer time, it is difficult to create a model in which developer time is cheap enough for under-provisioning to be cost-effective.

  2. Create an Auto Scaling group with a Step Scaling policy that scales up during the normal working hours of the majority of developers and scales back down at night. Scaling up during the weekday normal working hours and back down at night is the best practice to keep queue times down during peak development without over provisioning at night when traffic is low. Looking at millions of builds over time, a bell curve during normal working hour emerges for most data sets.

This is in contrast to auto scaling throughout the day based on traffic fluctuations because modeling revealed that boot times are actually too long to prevent queuing in real time. Use Amazon’s Step Policy instructions to set this up along with Cloudwatch Alarms.

Health Monitoring Metrics

CloudWatch integration enables the following custom metrics for health monitoring:

  • ContainersReserved gives you a view of usage over time for capacity planning and budget estimation.
  • ContainersLeaked should be 0 or close to 0, an increase indicates a potential infrastructure issue.
  • ContainersAvailable is used for Auto Scaling. If the value is too high, consider shutting some machines down, if the value is too low, consider starting up machines.

  • and expresses the degree to which the system is under-provisioned and number of queued builds that are not running. Ideally, the ASG will account for this as well. Values that are too high may indicate an outage or incident.

  • circle.state.running-builds provides a general insight into current usage.

  • Note that circle.state.num-masters includes the web server host in the Services machine that does not run any builds. That means the following:
    • If the value is 0, there is an outage or system is in maintenance. Risk of dropping some github hooks.
    • If the value is 1, there are no Builders, so web traffic and GitHub hooks are accepted, but not run.
    • If the value is 1 + n, there are n builders running and visible to the system. If this is less than the total number of builders launched through AWS, your builders are most likely not launching correctly. If builds are queueing, but this number says you have builders available to the system, you may need to launch more builders.


Collecting and centralizing logs is an essential component of monitoring. The logs provide audit trails as well as debugging information for infrastructure failures. This document describes how you can integrate CircleCI with your logging solution in the following sections:

Installing Logging Appliance Agents

CircleCI 1.0 Builders store logs in /var/log/**/*.log except for Docker, which stores logs in /var/lib/docker/containers/**/*-json.log.

Logging appliances generally require installation of a custom agent on each machine and configuration that collects logs and forwards them to a service, for example Logstash, Splunk, Graylog, and Amazon Cloudwatch Logs.

Configure the agent according to the environment, the authentication mechanisms, and centralized logging service discovery mechanism. You can reuse your current practices for setting up the agent and configuration.

If you are using CircleCI Terraform/CloudFormation templates, you can modify the launch configuration to add the hook to install the agent and run it as follows:


#### Log configuration - using Amazon CloudWatch as an example

# Install the agent, using Amazon CloudWatch as an example

# Configure agent
cat <<EOF >/root/awslogs.conf
state_file = /var/awslogs/state/agent-state

datetime_format = %Y/%m/%d %H:%M:%S
file = /var/log/circle-builder/circle.log
buffer_duration = 5000
log_stream_name = {instance_id}
initial_position = end_of_file
log_group_name = /var/log/circle-builder/circle.log

## Run agent
python ./ --region us-west-2 --non-interactive --configfile=/root/awslogs.conf

#### Run CircleCI Builder as typical

curl | \
    SERVICES_PRIVATE_IP=<private ip address of services box> \
    CIRCLE_SECRET_PASSPHRASE=<passphrase entered on system console (services box port 8800) settings> \

If you are using an orchestration tool, for example Chef, Puppet, or SaltStack, it is possible to apply the appropriate recipe or cookbook to the builder instances.

Integrating With Syslog

CircleCI 1.0 Builders integrate with the syslog facility. Syslog is a widely used standard for logging, and most agents integrate with it seamlessly. Configure the builder machines to emit logs to the syslog facility by setting CIRCLE_LOG_TO_SYSLOG to true in the launch configuration:

curl | \
    SERVICES_PRIVATE_IP=<private ip address of services box> \
    CIRCLE_SECRET_PASSPHRASE=<passphrase entered on system console (services box port 8800) settings> \

Then, configure syslog to forward logging to a centralized rsyslog server, or configure a local logging agent to monitor the syslog rather than monitor files.

The Services machine uses Docker. It is possible to customize the Docker daemon to route logs to your desired supported destination, see the Docker documentation on logging drivers for details.

Note: Many tools default to file-based logging, and using the syslog facility as the only mode of logging may accidentally ignore important logging info. Configuring custom agents to watch all of /var/log/**/* will result in capturing most logging files including syslog.