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 and 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
Recommended actions
- Keep Connect versions updated with the latest security patches and features
- Communicate upcoming Connect updates to content creators and users
- Test content compatibility before major version upgrades
- Document the Connect version in your infrastructure documentation
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Review unused features and understand what features might be available but not in use
- Create targeted training sessions for underutilized but valuable features
- Incorporate feature usage trends into your Connect upgrade planning process
- Collect feedback from users about features they find most valuable
- Compare feature usage across different teams to identify best practices that could be shared
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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 is 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
Recommended actions
- Keep Python versions updated with the latest security patches
- Communicate with content creators about supported and recommended Python versions
- Plan for the introduction of new Python versions and retirement of older ones
- Review content using older Python versions for potential migration
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Keep Quarto versions updated with the latest security patches
- Communicate with content creators about supported and recommended Quarto versions
- Plan for the introduction of new Quarto versions and retirement of older ones
- Review content using older Quarto versions for potential migration
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Keep R versions updated with the latest security patches
- Communicate with content creators about supported and recommended R versions
- Plan for the introduction of new R versions and retirement of older ones
- Review content using older R versions for potential migration
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Keep TensorFlow versions updated with the latest security patches
- Communicate with content creators about supported and recommended TensorFlow versions
- Plan for the introduction of new TensorFlow versions and retirement of older ones
- Review content using older TensorFlow versions for potential migration
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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 | IDs 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 is always 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
Recommended actions
- Analyze content distribution by type to identify trends in your organization’s data products
- Combine with various session and user metrics to provide insight into content usage patterns and user engagement
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Compare active sessions against server capacity to identify potential bottlenecks
- Schedule maintenance during periods of low activity
- Allocate more resources to applications with consistently high session counts
- Monitor session trends to identify unexpected spikes or drops that may indicate issues
Technical details
| Property | Value |
|---|---|
| Metric Type | gauge |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Analyze group and group members alongside other metrics to see how groups of users are using Connect
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Analyze group and group members alongside other metrics to see how groups of users are using Connect
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | N/A |
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
Recommended actions
- Compare with license user seats to view how user counts over time relate to licensed seats
- Track users over time to better plan for license renewals and expansions
Technical details
| Property | Value |
|---|---|
| Metric Type | gauge |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Compare with License Active Users to view how user counts over time relate to licensed seats
- Track users over time to better plan for license renewals and expansions
Technical details
| Property | Value |
|---|---|
| Metric Type | gauge |
| Aggregation Strategy | Deduplication |
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
Recommended actions
- Regularly review user roles and permissions to ensure compliance with organizational policies
- Deactivate or remove inactive users to free up licenses and improve system performance
- Use the data to identify trends in user activity and plan for scaling or resource allocation
Technical details
| Property | Value |
|---|---|
| Metric Type | non-numeric |
| Aggregation Strategy | Deduplication |