This page lists and explains the available Posit Workbench 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
pwb_build_info
This metric tracks the Workbench version that is installed on your Workbench server. It helps administrators ensure that the necessary Workbench versions are available for content deployment and execution.
Schema
version |
string |
The version number of this Workbench installation. |
release_name |
string |
The name of the release for this Workbench 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
- Security: Maintain awareness of security patches and critical updates
- Support eligibility: Monitor if Posit still supports your Workbench version
Recommended actions
- Keep Workbench versions updated with the latest security patches and features
- Communicate upcoming Workbench updates to content creators and users
- Document the Workbench version in your infrastructure documentation
Technical details
| Metric Type |
non-numeric |
| Aggregation Strategy |
Deduplication |
Sessions
pwb_active_user_sessions
This metric tracks the number of active user login sessions from this server.
Schema
value |
int |
The number of active Workbench user sessions. |
Why this metric matters
- Resource utilization: Tracks how many concurrent sessions are running, helping assess server load and resource consumption
- Performance monitoring: High session counts may indicate potential performance bottlenecks or the need for infrastructure scaling
- User behavior: Reveals usage patterns and peak activity times that can inform capacity planning and maintenance scheduling
- Session management: Helps identify if users are leaving sessions idle, which could impact system performance and resource allocation
Recommended actions
- Monitor session counts during peak hours to identify potential capacity constraints
- Compare with total licensed users to understand session-to-user ratios
- Track session patterns over time to optimize resource allocation and server configuration
- Use this data to inform decisions about session timeout policies and resource limits
Technical details
| Metric Type |
gauge |
| Aggregation Strategy |
Deduplication |
pwb_jobs_launched_total
This metric tracks the total number of jobs launched on Workbench.
Schema
job_type |
string |
The type of job (e.g., r) launched. |
value |
string |
A running total of the number of jobs launched. If Workbench is restarted, these values will reset. |
Why this metric matters
- Resource utilization: Understand the compute demands from background jobs on your Workbench installation
- User activity: Gain insight into how frequently users leverage background jobs for data processing
- Infrastructure planning: Identify growth trends in job usage to inform capacity planning decisions
Recommended actions
- Monitor job launch patterns to optimize scheduling and resource allocation
- Identify periods of high job volume to ensure adequate system resources
- Analyze job usage across different teams to understand varying computational needs
Technical details
| Metric Type |
sum |
| Aggregation Strategy |
Delta |
pwb_sessions_launched_total
This metric tracks the number of sessions that have been launched on your Workbench server. It helps administrators ensure that the necessary computing resources are available for session execution.
Schema
session_type |
string |
The type of session launched. |
value |
int |
The count of sessions launched since the previous value. |
user_guid |
string |
The user associated with the session count. |
Why this metric matters
- Resource planning: Track session volume to ensure adequate computing resources are available
- Capacity management: Monitor growth trends to plan infrastructure scaling
- Usage patterns: Identify peak usage times to optimize server availability
- License utilization: Ensure your Workbench license aligns with actual usage
- User adoption: Measure the uptake of Workbench across your organization
Recommended actions
- Review session growth trends to anticipate future infrastructure needs
- Analyze session types to understand which development environments are most popular
- Consider load balancing or additional resources if approaching capacity limits
- Schedule maintenance during identified low-usage periods
- Compare session metrics with user counts to identify adoption opportunities
Technical details
| Metric Type |
sum |
| Aggregation Strategy |
Delta |
pwb_session_startup_duration_seconds_bucket
This metric tracks the startup time (in seconds) for Workbench sessions.
Schema
session_type |
string |
The type of session launched. |
value |
int |
The number of sessions started up in a duration less than or equal to the limit, and greater than the next smallest limit. If Workbench is restarted, these values reset. |
limit |
int |
The time (in seconds) that is the upper-bound of the associated bucket and the lower-bound of the associated bucket with the next limit value. |
Why this metric matters
- Performance monitoring: Identifying slow startup durations helps in diagnosing performance bottlenecks
- Resource optimization: Understanding session startup patterns can guide resource allocation and scaling decisions
Recommended actions
- Monitor and analyze session startup durations to identify trends and anomalies
- Optimize server configurations and resource allocation to reduce startup times
- Investigate and address any recurring issues causing slow session startups
Technical details
| Metric Type |
histogram |
| Aggregation Strategy |
N/A |
pwb_session_startup_duration_seconds_sum
This metric tracks the running total of all session startup time (in seconds) in Workbench.
Schema
session_type |
string |
The type of session launched. |
value |
float |
A running total of all session startup time (in seconds) in Workbench. If Workbench is restarted this value will reset. |
Why this metric matters
- System performance monitoring: Provides a cumulative view of system performance regarding session startup times
- Load pattern analysis: Helps identify periods of high load that may affect session startup performance
- User experience impact: Long startup durations directly affect user productivity
Recommended actions
- Monitor the sum metric over time to identify trends
- Investigate spikes in the sum metric, which may indicate system-wide performance issues
Technical details
| Metric Type |
sum |
| Aggregation Strategy |
N/A |
pwb_session_startup_duration_seconds_count
This metric tracks the running total of the number of sessions launched in Workbench.
Schema
session_type |
string |
The type of session launched. |
value |
int |
A running total of all sessions launched in Workbench. If Workbench is restarted, this value resets. |
Why this metric matters
- Usage tracking: Provides a clear count of session startups, helping track overall Workbench usage over time
- Trend analysis: Tracking session counts helps identify usage patterns and predict future growth
Recommended actions
- Monitor daily, weekly, and monthly trends in session counts to understand usage patterns
- Compare session counts across different session types to identify user preferences
- Cross-reference with other metrics like startup duration to get a complete picture of system health
Technical details
| Metric Type |
sum |
| Aggregation Strategy |
N/A |
Users
pwb_license_active_users
This metric provides detailed information about user accounts in Workbench.
Schema
value |
int |
The number of users consuming a license seat. |
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
| Metric Type |
gauge |
| Aggregation Strategy |
Deduplication |
pwb_license_user_seats
The total number of licensed seats allowed in Workbench.
Schema
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 Workbench
- 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
| Metric Type |
gauge |
| Aggregation Strategy |
Deduplication |
pwb_users
This metric provides detailed information about user accounts in Posit Workbench.
Schema
id |
string |
The ID of the user. |
guid |
string |
The internal unique ID of the user. |
username |
string |
The Username of the Workbench user. |
email |
string |
The email of the user. This may be blank based on configuration of Workbench user provisioning. |
status |
string |
Contains the user’s license status. (Locked, Active, Inactive) |
is_admin |
boolean |
True if the Workbench user is an Administrator. |
is_super_admin |
boolean |
True if the Workbench user is an Administrator Superuser. |
role |
string |
The role of the Workbench user (User, Administrator, Superuser). This field is calculated by Chronicle based on the values of is_admin and is_super_admin. |
last_active_at |
date-time |
Timestamp of the Workbench user’s last sign in. |
created_at |
date-time |
Timestamp when the Workbench user was created. |
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
| Metric Type |
non-numeric |
| Aggregation Strategy |
Deduplication |
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