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Job Management

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Define and execute specific tasks using configured agents. Set job criteria, monitor execution, and track performance metrics.

Overview​

Job Management is the core execution layer of the Supervaize Fleet platform. It allows you to create specific tasks, configure them with the necessary parameters, and monitor their execution in real-time. Jobs are the individual units of work that agents perform to accomplish mission objectives.

Define New Job​

Step 1: Fill Agent Variables​

Configure the specific parameters for this job using the agent variables form:

  • Customer Context: Enter customer details, account type, and interaction history
  • Business Context: Include current promotions, product updates, and company news
  • Agent Parameters: Set tone, response length, and escalation thresholds

Step 2: Define Job Criteria​

Set specific success metrics for this job using the criteria configuration form:

  • Success Metrics: Define response time targets, satisfaction scores, and resolution goals
  • Quality Gates: Enable grammar checks, tone validation, and accuracy verification
  • Fallback Triggers: Set conditions that trigger human escalation or agent fallback

Step 3: Start Job​

Execute the job with configured parameters by clicking the Start Job button in the interface.

Job Configuration Options​

Job Types​

Define the category and purpose of your job:

  • Customer Inquiry: Handle customer questions and support requests
  • Data Analysis: Process and analyze data sets
  • Content Creation: Generate written or visual content
  • Process Automation: Automate repetitive business processes
  • Quality Assurance: Review and validate outputs
  • Training: Improve agent performance through learning

Priority Levels​

Set the importance and urgency of your job:

  • Low: Non-critical tasks with flexible timelines
  • Medium: Standard tasks with moderate urgency
  • High: Important tasks requiring attention
  • Critical: Urgent tasks with immediate impact

Execution Parameters​

Configure how the job should be executed:

  • Timeout Settings: Maximum time allowed for completion
  • Retry Logic: Number of attempts for failed jobs
  • Parallel Execution: Whether multiple jobs can run simultaneously
  • Resource Limits: CPU, memory, and network constraints

Job Lifecycle Management​

Creation Phase​

  • Define job objectives and requirements
  • Configure agent parameters and variables
  • Set success criteria and quality gates
  • Assign priority and execution settings

Execution Phase​

  • Monitor job progress in real-time
  • Track resource usage and performance
  • Handle errors and exceptions
  • Manage escalations and fallbacks

Completion Phase​

  • Validate job outputs and results
  • Assess quality and satisfaction scores
  • Document outcomes and learnings
  • Trigger follow-up actions if needed

Job Monitoring and Analytics​

Real-time Status Tracking​

Monitor job progress through multiple views:

Dashboard View:

  • Real-time job status and progress percentage
  • Elapsed time and estimated completion
  • Current execution step
  • Performance metrics (CPU, memory, API calls)

Detailed View:

  • Step-by-step execution log with timestamps
  • Resource usage tracking
  • Detailed performance analytics

Performance Metrics​

Track key performance indicators:

  • Execution Time: Total time from start to completion
  • Success Rate: Percentage of successfully completed jobs
  • Resource Efficiency: Optimal use of computing resources
  • Quality Scores: Accuracy, relevance, and satisfaction ratings

Comparative Analysis​

Benchmark job performance:

  • Historical Comparison: Performance against previous similar jobs
  • Agent Comparison: Effectiveness across different agents
  • Process Optimization: Identify improvement opportunities
  • Cost Analysis: Track resource costs and efficiency

Advanced Job Features​

Batch Processing​

Execute multiple similar jobs efficiently using the batch processing interface:

  • Batch Size: Configure the number of jobs to process together
  • Parallel Execution: Enable concurrent processing for faster completion
  • Failure Handling: Set policies for handling individual job failures
  • Progress Tracking: Monitor both individual and batch progress

A/B Testing​

Compare different agent configurations using the A/B testing interface:

  • Test Configuration: Set up test variants with different parameters
  • Success Metrics: Define which metrics determine the winning variant
  • Sample Size: Configure the number of interactions for each variant
  • Test Duration: Set the timeframe for running the experiment

Integration Webhooks​

Connect with external systems through the webhook configuration panel:

  • Endpoint Configuration: Set up the webhook URL for your external system
  • Event Selection: Choose which events trigger webhook notifications
  • Authentication: Configure security tokens and access methods
  • Retry Policies: Set up retry logic for failed webhook deliveries

Job Quality Assurance​

Quality Gates​

Implement automated quality checks:

  • Grammar and Spelling: Ensure proper language usage
  • Tone Appropriateness: Validate response tone and style
  • Information Accuracy: Verify factual correctness
  • Completeness: Check for comprehensive coverage

Validation Rules​

Define criteria for job success:

  • Response Time: Meet specified time requirements
  • Customer Satisfaction: Achieve target satisfaction scores
  • Resolution Quality: Ensure problems are properly resolved
  • Escalation Triggers: Handle complex issues appropriately

Feedback Loops​

Collect and incorporate feedback:

  • Customer Ratings: Gather satisfaction scores and comments
  • Agent Learning: Use outcomes to improve future performance
  • Process Refinement: Optimize job configurations based on results
  • Continuous Improvement: Iterate on job parameters and criteria

Troubleshooting Common Issues​

Job Stuck in "Pending" State​

Check the agent status in the dashboard to identify the issue.

Common causes:

  • Agent offline or unreachable
  • Insufficient resources
  • Configuration errors

Solutions:

  • Verify agent availability and connectivity
  • Check resource allocation and limits
  • Review job configuration settings
  • Restart the job if necessary

Performance Degradation​

Monitor resource usage through the performance dashboard.

Common causes:

  • High resource utilization
  • Network latency
  • Service rate limits
  • Inefficient configurations

Solutions:

  • Monitor and optimize resource usage
  • Adjust job parameters for efficiency
  • Implement caching strategies
  • Scale resources if needed

Quality Issues​

Review job logs in the detailed monitoring view.

Common causes:

  • Insufficient context or training
  • Poor parameter configuration
  • Inadequate quality gates
  • Agent capability limitations

Improvement strategies:

  • Refine agent variables and context
  • Update training data and examples
  • Adjust success criteria and thresholds
  • Enhance agent capabilities

Best Practices​

Job Design​

  • Clear Objectives: Define specific, measurable goals
  • Appropriate Scope: Keep jobs focused and manageable
  • Realistic Expectations: Set achievable success criteria
  • Proper Context: Provide comprehensive background information

Execution Management​

  • Monitor Progress: Track execution in real-time
  • Handle Errors: Implement proper error handling and recovery
  • Optimize Resources: Use resources efficiently
  • Document Learnings: Capture insights for future improvements

Quality Control​

  • Implement Gates: Use quality gates to ensure standards
  • Validate Outputs: Verify job results meet requirements
  • Collect Feedback: Gather input from stakeholders
  • Continuous Improvement: Iterate on job configurations

Next Steps​

After creating and executing jobs:

  1. Monitor performance through real-time dashboards
  2. Analyze results using performance metrics
  3. Optimize configurations based on learnings
  4. Scale operations by creating similar jobs