»Capacity and Performance
The maximum capacity and performance of Terraform Enterprise is dependent entirely on the resources provided by the Linux instance it is installed on. There are a few settings that allow Terraform Enterprise's capacity to be adjusted to suit the instance.
»Memory + Concurrency
The amount of memory to allocate to a Terraform run and the number of concurrent runs are the primary elements in understanding capacity above the base services.
By default, Terraform Enterprise allocates 512 MB of memory to each Terraform run, with a default concurrency of 10 parallel runs. Therefore, by default Terraform Enterprise requires 5.2 GB of memory reserved for runs.
After factoring in the memory needed to run the base services that make up the application, the default memory footprint of Terraform Enterprise is approximately 4 GB.
The settings for per-run memory and concurrency are available in the dashboard on port 8800, on the Settings page, under the Capacity section. They can also be set via the application settings JSON file when using the automated install procedure.
To increase the number of concurrent runs, adjust the
capacity_concurrency setting. This setting is not limited by
system checks; it depends on the operator to provide enough memory to the system to accommodate the requested
concurrent capacity. For example, if
capacity_concurrency is set to
100 and the worker memory is set to 512, the instance would require a minimum of 52 GB of memory just for Terraform runs. The rest of the TFE application requires a minimum of 4 GB of memory in addition to the Operating System requirements.
The default memory limit of 512 MB per Terraform run is also configurable. Note that this setting is not limited by system checks; it depends on the operator to provide enough memory to the system to accommodate the requested limits. If the memory limit is adjusted to 1024 MB with the default capacity of 10, the instance would require, at a minimum, 10 GB of memory reserved for Terraform runs.
We do not recommend adjusting the memory limit below 512 MB. Memory is Terraform's primary resource and it becomes easy for it to go above smaller limits and be terminated mid-run by the Linux kernel.
The required CPU resources for an individual Terraform run vary considerably, but in general they are a much more minor factor than memory due to Terraform mostly waiting on IO from APIs to return.
Our rule of thumb is 10 Terraform runs per CPU core, with 2 CPU cores allocated for the base Terraform Enterprise services. So a 4-core instance with 16 GB of memory could comfortably run 20 Terraform runs, if the runs are allocated the default 512 MB each.
As of the
v202109-1 TFE release, you can use the
capacity_cpus Replicated configuration option to set the maximum number of CPU cores that can be allocated to a Terraform run. When
capacity_cpus is set, the configuration places a hard quota on the number of cores that a Terraform operation and underlying provider plugin logic can consume. This can be an effective tool to prevent one expensive workspace from
monopolizing the CPU resources of the host.
The amount of disk storage available to a system plays a small role in the capacity of an instance. A root volume with 200 GB of storage can sustain a capacity well over 100 concurrent runs.
Because of the amount of churn caused by container creation as well as Terraform state management, highly concurrent setups will begin pushing hard on disk I/O. In cloud environments like AWS that limit disk I/O to IOPS that are credited per disk, it's important to provision a minimum number to prevent I/O related stalls. Low disk I/O can create significant performance issues.
This resource is harder to predict than memory or CPU usage because it varies per Terraform module, but we generally recommend a minimum of 50 IOPS per concurrent Terraform run. So if an instance is configured for 10 concurrent runs, the disk should have 500 IOPS allocated. For reference, on AWS, an EBS volume with an allocated size of 250 GB comes with a steady state of 750 IOPS.
We recommend using a disk with a minimum of 500 IOPS, but high load systems should consider increasing this significantly. For example, a production instance with a consistently high level of utilization and a concurrency of 10 should ideally have a disk with about 3,000 IOPS. Internal testing has shown performance increases with additional IOPs up to 8,000. Scaling the disk beyond 8,000 IOPs does not significantly improve performance.