charmscaler #2

Supports: xenial


The CharmScaler is an autoscaler for Juju applications. Based on Elastisys' autoscaling engine, it rightsizes your application deployments using sophisticated auto-scaling algorithms to ensure that the application runs cost-efficiently and is responsive at all times, even in the face of sudden load spikes. At times of high anticipated load your charm is reinforced with additional units -- units that are automatically decomissioned as the pressure on your application goes down.


The Elastisys CharmScaler is an autoscaler for Juju applications. It automatically scales your charm by adding units at times of high load and by removing units at times of low load.

The initial edition of the CharmScaler features a simplified version of Elastisys' autoscaling engine (described below), without its predictive capabilities and with limited scaling metric support. Work is underway on a more fully-featured CharmScaler, but no release date has been set yet.

The initial CharmScaler edition scales the number of units of your applications based on the observed CPU usage. These CPU metrics are collected from your application by a telegraf agent, which pushes the metrics into an InfluxDB backend, from where they are consumed by the CharmScaler.

The CharmScaler is available both free-of-charge and as a subscription service. The free version comes with a size restriction which currently limits the size of the scaled application to four units. Subscription users will see no such size restrictions. For more details refer to the Subscription section below.

If you are eager to try out the CharmScaler, head directly to the Quickstart section. If you want to learn more about the Elastisys autoscaler, read on ...

Introducing the Elastisys Autoscaler

User experience is king. You want to offer your users a smooth ride. From a performance perspective, this translates into providing them with a responsive service. As response times increase you will see more and more users leaving, perhaps for competing services.

An application can be tuned in many ways, but one critical aspect is to make sure that it runs on sufficient hardware, capable of bearing the weight that is placed on your system. However, resource planning is notoriously hard and involves a lot of guesswork. A fixed "peak-dimensioned" infrastructure is certain to have you overspending most of the time and, what's worse, you can never be sure that it actually will be able to handle the next load surge. Ideally, you want to run with just the right amount of resources at all times. It is plain to see that such a process involves a lot of planning and manual labor.

Elastisys automates this process with a sophisticated autoscaler. The Elastisys autoscaler uses proactive scaling algorithms based on state-of-the-art research, which, predictively offers just in time capacity. That is, it can provision servers in advance so that the right amount of capacity is available when it is needed, not when you realize that it's needed (by then your application may already be suffering). Research has shown that there is no single scaling algorithm to rule them all. Different workload patterns require different algorithms. The Elastisys autoscaler is armed with a growing collection of such algorithms.

The Elastisys autoscaler already supports a wide range of clouds and platforms. With the addition of the Juju CharmScaler, which can scale any Juju application Charm, integration with your application has never been easier. Whether it’s a Wordpress site, a Hadoop cluster, a Kubernetes cluster, or even OpenStack compute nodes, or your own custom-made application charm, hooking it up to be scaled by the Elastisys autoscaler is really easy.

Read more about Elastisys' cloud automation platform at


The free edition places a constraint on the size of the scaled application to four units. To remove this restriction you need to become a paying subscription user. Juju is currently in beta, and does not yet support commercial charms. Once Juju is officially released, the CharmScaler will be available as a subscription service. Until then, you can contact us and we will help you set up a temporary subscription arrangement.

For upgrading to a premium subscription, for a customized solution, or for general questions or feature requests, feel free to contact Elastisys at


If you can't wait to get started, the following minimal example (relying on configuration defaults) will let you start scaling your charm right away. For a description of the CharmScaler and further details on its configuration, refer to the sections below.

Juju credentials

At the time of writing there is no easy way to give a charm special Juju access levels. Therefore, for the CharmScaler to be able to scale units you need to give it the necessary credentials via the charm config.

Create a user and grant it model write access

juju add-user [username] && juju grant [username] write [model]

To set the password, execute the juju register command line given to you

Get the Juju API address and model UUID

juju show-controller

Minimal config.yaml example

  juju_api_endpoint: "[API address]:17070"
  juju_model_uuid: "[uuid]"
  juju_username: "[username]"
  juju_password: "[password]"


Deploy and relate the charms

juju deploy charmscaler --config=config.yaml
juju deploy cs:~chris.macnaughton/influxdb-7
juju deploy telegraf-2
juju deploy [charm]

juju relate charmscaler:db-api influxdb:query
juju relate telegraf:influxdb-api influxdb:query
juju relate telegraf:juju-info [charm]:juju-info
juju relate charmscaler:juju-info [charm]:juju-info

How the CharmScaler operates

CharmScaler flow

The image above illustrates the flow of the CharmScaler when scaling a Wordpress application. Scaling decisions executed by the CharmScaler are dependent on a load metric. In this case it looks at the CPU usage of machines where Wordpress instances are deployed.

Metrics are collected by the Telegraf agent which is deployed as a subordinate charm attached to the Wordpress application. This means that whenever the Wordpress application is scaled out, another Telegraf collector will be deployed as well and automatically start pushing new metrics to InfluxDB.

The CharmScaler will ask InfluxDB for new metric datapoints at every poll interval (configured using the metric_poll_interval option). From these load metrics the CharmScaler decides how many units are needed by your application.

In the case of Wordpress it is necessary to distribute the load on all of the units using a load balancer. If you haven't already, checkout the Juju documentation page on charm scaling.

Configuration explained

The CharmScaler's configuration is comprised of three main parts: juju, scaling and alerts.


The CharmScaler manages the number of units of the scaled charm via the Juju controller. To be able to do that it needs to authenticate with the controller. Controller authentication credentials are passed to the CharmScaler through options prefixed with juju_.

Note that in a foreseeable future, passing this kind of credentials to the CharmScaler may no longer be necessary. Instead of requiring you to manually type in the authentication details one could envision Juju giving the charm access through relations or something similar.


The CharmScaler has a number of config options that control the autoscaler's behavior. Those options are prefixed with either scaling_ or metric_. metric_ options control the way metrics are fetched and processed while the scaling_ options control when and how the charm units are scaled.

The scaling algorithm available in this edition of the CharmScaler is a rule-based one that looks at CPU usage. At each iteration (configured using the scaling_interval option) the following rules are considered by the autoscaler before making a scaling decision:

  1. scaling_cooldown - Has enough time passed since the last scale-event (scale in or out) occured?
  2. scaling_cpu_[max/min] - Is the CPU usage above/below the set limit?
  3. scaling_period_[up/down]scale - Has the CPU usage been above/below scaling_cpu_[max/min] for a long enough period of time?

If all three rules above are satisifed either a scale-out or a scale-in occurs and the scaled charm will automatically add or remove a unit.

Note that configuring the scaling algorithm is a balancing act -- one always needs to balance the need to scale "quickly enough" against the need to avoid "jumpy behavior". Too frequent scale-ups/scale-downs could have a negative impact on overall performance/system stability.

The default behavior adds a new unit when the average CPU usage (over all charm units) has exceeded 80% for at least one minute. If you want to make the CharmScaler quicker to respond to changes, you can, for example, lower the threshold to 60% and the evaluation period to 30 seconds:

juju config charmscaler scaling_cpu_max=60
juju config charmscaler scaling_period_upscale=30

Similarly, the default behavior removes a new unit when the average CPU usage has been under 20% (scaling_cpu_min) for at least two minutes (scaling_period_downscale). Typically, it is preferable to allow the application to be overprovisioned for some time to prevent situations where we are too quick to scale down, only to realize that the load dip was only temporary and that we need to scale back up again. We can, for instance, set the evaluation period preceding scale-downs a bit longer (five minutes) via:

juju config charmscaler scaling_period_downscale=300

Finally, changing the amount of time required between two scaling decisions can be done via:

juju config charmscaler scaling_cooldown=300

This parameter should, however, be kept long enough to give scaling decisions a chance to take effect, before a new scaling decision is triggered.


Lastly, the options with the alert_ prefix are used to enable CharmScaler alerts (these are turned off by default).

Alerts are used to notify the outside world (such as the charm owner) of noteable scaling events or error conditions. Alerts are, for example, sent (with severity-level ERROR) if there are problems to reach the Juju controller. Alerts are also sent (with severity-level INFO) when a scaling decision has been made.

This edition of the CharmScaler includes email alerts which are configured by entering the SMTP server details which the autoscaler is supposed to send the alert email messages to.

Known limitations

When deploying on LXD provider

Due to missing support for the Docker LXC profile in Juju you need to apply it manually.


By using the Elastisys CharmScaler, you agree to its license and privacy statement.


(boolean) Toggle e-mail alerts on/off
(string) Alert levels that should trigger alert mails to be sent out
(string) Space separated list of e-mail addresses that should recieve alerts
(string) E-mail address that alert mails should be sent from
(string) SMTP hostname
(string) Password to auth with the SMTP server
(int) SMTP port
(boolean) Use SSL when connecting to SMTP host
(string) Username to auth with the SMTP server
(string) URL to the Charmpool component. By default both the autoscaler and the pool is run in the same Docker network and will reach eachother by their local hostnames.
(string) Extra options to pass to the docker daemon. e.g. --insecure-registry
(boolean) Enable GRUB cgroup overrides cgroup_enable=memory swapaccount=1. WARNING changing this option will reboot the host - use with caution on production services
(string) URL to use for HTTP_PROXY to be used by Docker. Only useful in closed environments where a proxy is the only option for routing to the registry to pull images
(string) URL to use for HTTPS_PROXY to be used by Docker. Only useful in closed environments where a proxy is the only option for routing to the registry to pull images
(boolean) Toggle installation from ubuntu archive vs the docker PPA
(string) Juju controller API endpoint
(string) Juju model UUID
(string) Juju account password
(int) How often the charmscaler should sync against the Juju model.
(string) Juju account username
(int) The minimum age (in seconds) of requested data points. When requesting recent aggregate metric data points, there is always a risk of seeing partial/incomplete results before metric values from all sources have been registered. The value to set for this field depends on the reporting frequency of monitoring agents, but as a general rule-of-thumb, this value can be set to be about 1.5 times the length of the reporting-interval for monitoring agents.
(int) Seconds between polls for new metric values
(string) Used by the nrpe subordinate charms. A string that will be prepended to instance name to set the host name in nagios. So for instance the hostname would be something like: juju-myservice-0 If you're running multiple environments with the same services in them this allows you to differentiate between them.
(string) A comma-separated list of nagios servicegroups. If left empty, the nagios_context will be used as the servicegroup
(string) The name of the service - mainly shows up in the alert e-mails Also useful to distinguish between multiple CharmScaler charms
(string) Comma-separated list of destinations (either domain names or IP addresses) that should be directly accessed, by opposition of going through the proxy defined above.
(int) Port which the Autoscaler API should be served on.
(int) Time (in seconds) before making another scaling decision from the time of the last up- or downscale. This is useful to prevent extra resizes due to slow teardowns or, in perticular, upstarts.
(int) CPU usage threshold at which the number of units should be scaled up.
(int) CPU threshold where the load is considered low enough to scale down the number of units.
(int) Seconds between each scaling decision
(int) Number of seconds that the CPU usage needs to be lower than the threshold before scaling down.
(int) Number of seconds that the CPU usage needs to be higher than the threshold before scaling up.
(int) Maximum amount of units to keep in pool
(int) Minimum amount of units to keep in pool