Connect Metrics

This page lists and explains the available Posit Connect metrics.

Each metric is listed with its description, schema, why it matters, and recommended actions. It also includes technical details, including metric type and aggregation strategy.

These metrics are stored in separate folders based on the name of the metric. These folders are located within the configured storage location (/var/lib/posit-chronicle/data by default).

Build / version

connect_build_info

This metric tracks the Connect version installed on your Connect server. It helps administrators ensure that the necessary Connect versions are available for content deployment and execution.

Schema

Attribute Type Description
version string The version number of this Connect installation.
build string The detailed build version of this Connect installation.
os string The operating system running on the host.

Why this metric matters

  • Update planning: Identify when updates should be scheduled to access new functionality
  • Compatibility: Ensure content and packages are compatible with your Connect version
  • Security: Maintain awareness of security patches and critical updates
  • Support eligibility: Monitor if your Connect version is still supported by Posit

connect_feature_usage

This metric provides usage information for all tracked features in Connect.

Schema

Attribute Type Description
name string Name of the feature flag.
used bool Whether or not this feature has been used.

Why this metric matters

  • Feature adoption: Provides visibility into which Connect features are actively being used in your organization
  • ROI assessment: Helps evaluate the return on investment for Connect licensing
  • Training opportunities: Identifies features that may require additional user education or promotion
  • Upgrade planning: Informs decisions about which new features to prioritize when upgrading
  • Workflow optimization: Reveals how your team is using Connect to improve data science workflows

connect_installed_versions_python

This metric tracks the Python versions that are installed and available on your Posit Connect server. It helps administrators ensure that the necessary Python versions are available for content deployment and execution.

Schema

Attribute Type Description
version string The version number of this Python installation.
cluster_name string The cluster that contains this Python installation. A value of Local indicates that the Python installation is local to the Connect server.
image_name string The image that contains this Python installation. A value of Local indicates that the Python installation is local to the Connect server.
api_enabled boolean This value is true only when Python support is enabled in Connect and API hosting is permitted by the product license. It will be false in all other cases.

Why this metric matters

  • Dependency management: Ensure that required Python versions are available for content
  • Version planning: Identify when older versions can be retired or when new versions should be added
  • Environment consistency: Maintain consistent development and deployment environments
  • Security: Track older versions that may have security vulnerabilities

connect_installed_versions_quarto

This metric tracks the Quarto versions that are installed and available on your Connect server. It helps administrators ensure that the necessary Quarto versions are available for content deployment and execution.

Schema

Attribute Type Description
version string The version number of this Quarto installation.
cluster_name string The cluster that contains this Quarto installation. A value of Local indicates that the Quarto installation is local to the Connect server.
image_name string The image that contains this Quarto installation. A value of Local indicates that the Quarto installation is local to the Connect server.

Why this metric matters

  • Dependency management: Ensure that required Quarto versions are available for content
  • Version planning: Identify when older versions can be retired or when new versions should be added
  • Environment consistency: Maintain consistent development and deployment environments
  • Security: Track older versions that may have security vulnerabilities

connect_installed_versions_r

This metric tracks the R versions that are installed and available on your Connect server. It helps administrators ensure that the necessary R versions are available for content deployment and execution.

Schema

Attribute Type Description
version string The version number of this R installation.
cluster_name string The cluster that contains this R installation. A value of Local indicates that the R installation is local to the Connect server.
image_name string The image that contains this R installation. A value of Local indicates that the R installation is local to the Connect server.

Why this metric matters

  • Dependency management: Ensure that required R versions are available for content
  • Version planning: Identify when older versions can be retired or when new versions should be added
  • Environment consistency: Maintain consistent development and deployment environments
  • Security: Track older versions that may have security vulnerabilities

connect_installed_versions_tensorflow

This metric tracks the TensorFlow versions that are installed and available on your Connect server. It helps administrators ensure that the necessary TensorFlow versions are available for content deployment and execution.

Schema

Attribute Type Description
version string The version number of this TensorFlow installation.
cluster_name string The cluster that contains this TensorFlow installation. A value of Local indicates that the TensorFlow installation is local to the Connect server.
image_name string The image that contains this TensorFlow installation. A value of Local indicates that the TensorFlow installation is local to the Connect server.

Why this metric matters

  • Dependency management: Ensure that required TensorFlow versions are available for content
  • Version planning: Identify when older versions can be retired or when new versions should be added
  • Environment consistency: Maintain consistent development and deployment environments
  • Security: Track older versions that may have security vulnerabilities

Content

connect_contents

This metric tracks all content items in Connect.

Schema

Attribute Type Description
guid string The GUID of the content item.
name string Name of the content item.
title string Title of the content item.
created_time date-time When the content was first created.
last_deployed_time datetime The timestamp indicating when this content last had a successful bundle deployment performed.
app_mode string The runtime model for this content. Has a value of unknown before data is deployed to this item. Automatically assigned upon the first successful bundle deployment.
description string A rich description of this content.
access_type string Access type describes how this content manages its viewers. The value all is the most permissive; any visitor to Connect will be able to view this content. The value logged_in indicates that all Connect accounts may view the content. The acl value lets specifically enumerated users and groups view the content. Users configured as collaborators may always view content.
locked boolean Whether or not the content is locked.
locked_message string A custom message that is displayed by the content item when locked.
connection_timeout int Maximum number of seconds allowed without data sent or received across a client connection.
read_timeout int Maximum number of seconds allowed without data received from a client connection.
init_timeout int The maximum number of seconds allowed for an interactive application to start.
idle_timeout int The maximum number of seconds a worker process for an interactive application to remain alive after it goes idle (no active connections).
max_processes int The total number of concurrent processes allowed for a single interactive application per Connect node.
min_processes int The minimum number of concurrent processes allowed for a single interactive application per Connect node.
max_conns_per_process int The maximum number of client connections allowed to an individual process.
load_factor double Controls how aggressively new processes are spawned.
cpu_request double The minimum amount of compute power this content needs when executing or rendering.
cpu_limit double The maximum amount of compute power this content will be allowed to consume when executing or rendering
memory_request int The minimum amount of RAM this content needs when executing or rendering, expressed in bytes.
memory_limit int The maximum amount of RAM this content will be allowed to consume when executing or rendering, expressed in bytes.
amd_gpu_limit int The number of AMD GPUs that will be allocated by Kubernetes to run this content.
nvidia_gpu_limit int The number of NVIDIA GPUs that will be allocated by Kubernetes to run this content.
bundle_id string The identifier for the active deployment bundle.
content_category string Describes the specialization of the content runtime model.
parameterized boolean True when R Markdown rendered content allows parameter configuration
cluster_name string The location where this content runs.
image_name string The name of the container image used to run this content in containerized environments such as Kubernetes.
default_image_name string The default image that will be used when none is defined by the bundle’s manifest.
default_r_environment_management boolean Indicates whether or not Connect should create and manage an R environment (installing required packages) for this content.
default_py_environment_management boolean Indicates whether or not Connect should create and manage a Python environment (installing required packages) for this content.
service_account_name string The name of the Kubernetes service account that is used to run a particular piece of content.
r_version string The version of the R interpreter associated with this content.
r_environment_management boolean Indicates whether or not Connect is managing an R environment and has installed the required packages for this content.
py_version string The version of Python associated with this content.
py_environment_management boolean Indicates whether or not Connect is managing a Python environment and has installed the required packages for this content.
quarto_version string The version of Quarto associated with this content.
run_as string The UNIX user that executes this content.
run_as_current_user boolean Indicates that Connect should run processes for this content item under the Unix account of the user who visits it.
owner_guid string The GUID of the owner of the content item.
content_url string The URL associated with this content.
dashboard_url string The URL within the Connect dashboard where this content can be configured.
app_role string The relationship of the accessing user to this content.
vanity_url string The vanity URL associated with this content item.
tags array ID’s of the tags associated with this content item.
id string The internal numeric identifier of this content item.
extension boolean Whether the content is a Connect Extension. This field is not in use and will always be empty.

Why this metric matters

  • Content management: Provides a comprehensive view of all deployed content in your Connect instance, enabling better organization and maintenance
  • Content lifecycle management: Track creation dates and identify outdated or unused content that may need review or archiving
  • Resource allocation: Understand the distribution of different content types to optimize server resources and improve performance

connect_content_app_sessions_current

This metric tracks the number of currently active sessions for Shiny apps on your Connect server. It helps administrators understand which apps are active.

Schema

Attribute Type Description
content_id string The GUID, in RFC4122 format, of the Shiny application this information pertains to.
user_id string The GUID, in RFC4122 format, of the user that is visiting the application.
value string The number of active sessions for the user and content.

Why this metric matters

  • Server load: Monitor demand on your Connect server
  • Usage patterns: Identify peak usage times and popular applications
  • Capacity planning: Ensure you have adequate resources to handle concurrent users
  • User experience: Correlate session count with performance to optimize the user experience

connect_content_visits

This metric tracks the visits (or “hits”) for all content types including Shiny applications.

Important

The collection of Connect event metrics is disabled by default. To configure the agent to collect these metrics, see the Agent Configuration Appendix.

Schema

Attribute Type Description
value int The number of visits.
content_guid string The GUID of the content this information pertains to.
user_guid string The GUID of the user that visited the content.
bundle_id string The ID of the particular bundle used.
data_version int The data version the record was recorded with.
path string The path requested by the user.
variant_key string The key of the variant the user visited. This will be null for static content.
rendering_id int The ID of the rendering the user visited. This will be null for static content.

Why this metric matters

  • Usage insights: Tracking content visits provides valuable data on which content is most frequently accessed and by whom
  • Resource allocation: Understanding visit patterns helps optimize server resources
  • Content effectiveness: Measuring visits helps evaluate the impact and effectiveness of published content
  • User engagement: Visit metrics reveal how users interact with different content types across your organization

Recommended actions

  • Analyze visit patterns to identify popular content and potential bottlenecks in user workflows
  • Use visit data to prioritize maintenance and updates for frequently accessed content
  • Compare visit trends over time to understand changing user preferences and needs
  • Cross-reference with other metrics like session duration to get a complete picture of app engagement
Technical details
Metric Type gauge
Aggregation Strategy Full Retention

connect_shiny_usage

This metric tracks Shiny application usage in Connect.

Important

The collection of Connect event metrics is disabled by default. To configure the agent to collect these metrics, see the Agent Configuration Appendix.

Note

Usage metrics are timestamped at session end, meaning longer sessions are recorded on the day they ended, rather than started. Durations may be up to 15 seconds longer than actual usage due to Connect’s connection monitoring mechanism.

Schema

Attribute Type Description
duration int The time (in seconds) of the Shiny application usage.
content_guid string The GUID of the Shiny application this information pertains to.
user_guid string The GUID of the user that visited the application.
started date-time The timestamp when the user opened the application.
ended date-time The timestamp when the user left the application.
data_version int The data version from Connect. See the Connect Docs for more details.

Why this metric matters

  • Usage insights: Tracking Shiny app usage provides valuable data on which apps are most frequently accessed and by whom
  • Resource allocation: Understanding usage patterns helps optimize server resources
  • Content effectiveness: Measuring usage helps evaluate the impact and effectiveness of published apps
  • Session length analysis: The duration field reveals whether users engage deeply with apps or quickly bounce, providing insight into app value and usability

connect_tags

This metric provides a list of all tags in Connect.

Schema

Attribute Type Description
id string The ID of the tag.
name string The name of the tag.
parent_id string The ID for the parent tag. If there is no parent_id, the tag is a top-level tag.
created_time date-time The timestamp indicating when the tag was created.
updated_time date-time The timestamp indicating when the tag was last updated.

Why this metric matters

  • Content organization: Tags provide a hierarchical structure to organize content, making it easier to navigate large content libraries
  • Content discovery: Well-implemented tagging improves discoverability, allowing users to find relevant content more efficiently
  • Content auditing: Tracking tag usage helps identify inconsistencies and opportunities to improve content organization

Users

connect_groups

This metric tracks all groups in Connect.

Schema

Attribute Type Description
name string Name of the group.
guid string The GUID of the group.
owner_guid string The GUID of the owner of this group.

Why this metric matters

  • User management: Groups allow organization of users into collections for easier management and access control
  • Collaboration management: Understand team structures within your Connect instance

connect_group_members

This metric tracks all group members in Connect.

Schema

Attribute Type Description
group_id string The GUID of the group.
member_id string The GUID of the user in this group.

Why this metric matters

  • User management: Groups allow organization of users into collections for easier management and access control
  • Collaboration management: Understand team structures within your Connect instance

connect_licensed_active_users

The current number of users consuming license seats in Connect.

Schema

Attribute Type Description
value int The number of active users.

Why this metric matters

  • License utilization: Tracks how many users are actively consuming Connect license seats
  • Cost management: Provides insights into whether your organization is over-provisioned or under-provisioned with licenses, potentially saving costs
  • Growth trends: When tracked over time, reveals user adoption patterns and growth trends that can inform strategic decisions
  • Compliance: Helps ensure your organization remains in compliance with licensing agreements by monitoring active usage against your license limits

connect_license_user_seats

This metric tracks the number of user seats in your Connect license.

Schema

Attribute Type Description
value int The number of license seats.

Why this metric matters

  • License utilization: Tracks the total number of license seats which can be used with this instance of Connect
  • Cost management: Provides insights into whether your organization is over-provisioned or under-provisioned with licenses, potentially saving costs
  • Growth trends: When tracked over time, reveals user adoption patterns and growth trends that can inform strategic decisions
  • Compliance: Helps ensure your organization remains in compliance with licensing agreements by monitoring active usage against your license limits

connect_users

This metric provides detailed information about user accounts in Connect.

Schema

Attribute Type Description
id string The ID of the user.
username string The username of the user (the name they use when logging in).
email string The email address of the user.
first_name string The first name of the user.
last_name string The last name of the user.
user_role string The role of the user (e.g., publisher, viewer).
created_at date-time The timestamp when the user was created.
updated_at date-time The timestamp when the user was most recently updated.
last_active_at date-time The timestamp when the user was most recently active (logged in) in Connect.
locked boolean Whether or not the user is locked.
confirmed boolean When false, the created user must confirm their account through an email. This feature is unique to password authentication.

Why this metric matters

  • Access control and security: Understanding user activity and roles helps ensure proper access control and security
  • License optimization: Identifying inactive users can help optimize license usage and reduce costs
  • Activity insights: Monitoring user activity provides insights into adoption and engagement
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