Server stats and errors
Last updated
Last updated
The Server Stats and Errors section provides administrators with valuable insights into server performance, user activity, and error monitoring. By offering real-time data and logs, it helps in diagnosing issues, optimizing server usage, and improving overall operational.
The Server Stats module is designed to:
Monitor user activity: Track signups, active users, and retention metrics over specific time periods.
Analyze team and workspace growth: View trends in team creation and workspace usage.
Optimize resource usage: Gain insights into server usage to plan resource allocation.
Users:
Total Count: Displays the total number of registered users on the server. Useful for understanding the overall user base size.
Signups: Indicates the number of new accounts created within the selected time period. Helps track user growth.
Signups (Confirmed): Tracks confirmed user registrations. Useful for analyzing verified user onboarding.
Signups (Social): Reflects new signups via social platforms. Shows adoption from integrated social channels.
Fresh Domains: Represents signups from unique email domains. Useful for monitoring diversity in user registrations.
Active: Counts users who performed at least one action (e.g., labeling, running tasks) during the selected period. Key metric for user engagement.
Retained: Represents users who registered earlier and performed actions during the selected period. Measures long-term engagement.
Teams & Workspaces:
Created Teams: Displays the total number of new teams created on the server. Useful for tracking team activity and collaboration growth.
Created Workspaces: Shows the number of new workspaces created. Indicates organizational growth.
Avg Users Count: Reflects the average number of users in teams with two or more members. Helps analyze collaboration levels.
Users Count (Created Teams): Number of users who created at least one team. Tracks active team creators.
Users Count (Created Workspaces): Number of users who created at least one workspace. Highlights workspace contributors.
Projects:
Total Count: Displays the total number of projects on the server. Useful for understanding the overall scope of work.
Count in Period: Number of projects created during the selected time period. Tracks project activity.
Local Count: Shows the number of locally created projects. Indicates server-based project creation.
Imported Count: Reflects the number of projects imported from external sources. Useful for identifying data integrations.
Tasks:
By Type (Successful): Breaks down successfully completed tasks by type (e.g., clone, app). Helps monitor task outcomes.
By Type (Failed): Displays the count of failed tasks by type. Useful for identifying problem areas.
By Status: Shows tasks grouped by their current status (e.g., queued, started, error). Key for task monitoring and issue resolution.
Shares:
Links Created: Number of links generated for sharing data or projects. Useful for tracking resource distribution.
Users with Links: Reflects the number of users who created at least one link. Shows adoption of sharing functionality.
Agents:
Total Agents: Total number of agents registered on the server. Useful for understanding infrastructure size.
Created Agents: Number of new agents added during the selected period. Tracks growth in agent resources.
Active Agents: Number of agents that sent hardware info during the selected period. Indicates active resources.
Jobs:
Total Jobs: Total number of jobs created on the server. Reflects server usage for task processing.
Created Jobs: Number of jobs created during the selected period. Tracks job creation trends.
Users with Jobs: Number of users who created at least one job. Highlights task contributors.
Models:
Total Models: Displays the total number of models on the server. Useful for understanding modeling activity.
Created Models: Number of new models created during the selected period. Tracks development of new models.
Trained Models: Reflects models that have completed training. Key metric for model development progress.
Users with Models: Number of users who created at least one model. Highlights active contributors to model development.
Python Notebooks:
Total Containers Created: Number of containers created for Python notebooks. Indicates server activity related to scripting.
Notebooks Added: Reflects new notebooks added during the selected period. Tracks growth in notebook resources.
Containers Created: Shows notebooks that have been run at least once. Highlights active scripting tasks.
Containers Running Now: Indicates the number of currently active notebook containers. Useful for real-time monitoring.
Containers Lifetime: Displays the average lifetime of notebook containers. Useful for understanding resource consumption patterns.
Created Teams: Total number of teams created.
The Server Errors module helps diagnose and resolve application or system-level issues. By providing detailed logs, it allows admins to:
Identify errors: Quickly locate application errors or failures.
Monitor frequency: Track the number of error events over time.
Resolve issues: Use logs and configuration data to fix problems efficiently.
Error Logs
Error logs provide detailed information about system and application errors, enabling efficient identification and resolution of issues. Key components include:
Error Type: Categorizes the source of the error (e.g., App, System). This helps determine if the issue originates from user actions, applications, or server infrastructure.
User: Identifies the user associated with the error event, useful for tracking user-specific issues and providing targeted support.
Agent: Shows the hardware or environment (e.g., Kubernetes, specific agents) where the error occurred. This aids in diagnosing infrastructure-related issues.
Date: Displays when the error happened. Useful for correlating errors with recent changes or activities.
Duration: Indicates how long the error lasted, helping prioritize issues that have a greater impact on system performance.
Events: Tracks the frequency of the specific error type, helping to identify recurring or widespread issues.
Actions:
Show Log: Access detailed error logs for in-depth debugging and root cause analysis.
Show Config: View configuration settings associated with the error to verify or adjust settings to resolve the issue.
