Managing Disk Space
Posit Connect can consume significant disk space as users deploy content over time. This page describes the main sources of disk usage and the configuration settings available to manage them.
Most disk usage accumulates in the Connect data directory (Server.DataDir, which defaults to /var/lib/rstudio-connect). You can check the current usage with:
Terminal
du -sh /var/lib/rstudio-connectBundle retention
Each deployment creates a new bundle on disk. By default, all previous bundles are retained indefinitely, which can consume significant space.
To limit the number of bundles retained per content item, set Applications.BundleRetentionLimit:
/etc/rstudio-connect/rstudio-connect.gcfg
[Applications]
BundleRetentionLimit = 3Older bundles are deleted periodically, which runs on the interval defined by Applications.BundleReapFrequency (default: 24h).
Rendering output retention
Rendered content produces output each time it runs. Two settings control automatic cleanup of old renderings:
Applications.RenderingSweepLimit— Maximum renderings retained per content item. Default:30.Applications.RenderingSweepAge— Maximum age of a rendering. Default:30d.
The cleanup frequency is controlled by Applications.RenderingSweepFrequency (default: 1h).
Python environment cleanup
Python content uses virtual environments stored on disk. Connect removes unused environments automatically. For details on how environment caching works, see Environment caching.
The cleanup interval is controlled by Applications.PythonEnvironmentReapFrequency (default: 24h). To disable cleanup, set Applications.PythonEnvironmentReaping to false.
Job history cleanup
Connect stores metadata and output for completed jobs on disk. Two settings control automatic cleanup:
Jobs.MaxCompleted— Maximum completed jobs retained per content item. Default:1000.Jobs.OldestCompleted— Maximum age of a completed job. Default:30d.
A job is removed if either limit is exceeded.
Runtime caches
R and Python package caches are not automatically deleted when content is removed. See the Runtime Caches documentation for details on viewing and deleting these caches.
Applying changes
After updating the configuration file, restart Connect for the changes to take effect:
Terminal
sudo systemctl restart rstudio-connectSummary of space-saving settings
The following table summarizes all settings that help manage disk space:
| Setting | Default | Description |
|---|---|---|
Jobs.MaxCompleted |
1000 | Maximum completed jobs per application |
Jobs.OldestCompleted |
30d | Maximum age of completed jobs |
Applications.RenderingSweepLimit |
30 | Maximum renderings per application |
Applications.RenderingSweepAge |
30d | Maximum age of renderings |
Applications.RenderingSweepFrequency |
1h | Rendering cleanup frequency |
Applications.BundleRetentionLimit |
0 | Maximum bundles per application (0 = unlimited) |
Applications.BundleReapFrequency |
24h | Bundle cleanup frequency |
Applications.PythonEnvironmentReaping |
true | Enable Python environment cleanup |
Applications.PythonEnvironmentReapFrequency |
24h | Python environment cleanup frequency |
Recommended configuration for constrained environments
For environments with limited disk space, consider this configuration:
/etc/rstudio-connect/rstudio-connect.gcfg
[Jobs]
MaxCompleted = 100
OldestCompleted = 7d
[Applications]
RenderingSweepLimit = 10
RenderingSweepAge = 14d
RenderingSweepFrequency = 30m
BundleRetentionLimit = 3
BundleReapFrequency = 6h
PythonEnvironmentReaping = true
PythonEnvironmentReapFrequency = 6h