Flint
Workflow Engine

System Architecture

How Flint's workflow system works behind the scenes

System Architecture

Learn about the infrastructure that powers your workflows and ensures reliable execution.

How the System Works

High-Level Overview

Flint's workflow system consists of three main components working together:

Your Interface

  • Web dashboard for creating workflows
  • Mobile apps for on-the-go access
  • API for programmatic control
  • Real-time monitoring and alerts

Orchestration Layer

  • Central brain that manages everything
  • Queues and schedules workflow runs
  • Monitors system health
  • Handles scaling and resource allocation

Execution Layer

  • Lightweight workers that run your workflows
  • Automatically scale based on demand
  • Distributed across multiple regions
  • Fault-tolerant and self-healing

Visual System Architecture

Your Dashboard/API

Central Orchestrator
    ↓        ↓
Worker 1   Worker 2  ... Worker N
    ↓        ↓           ↓
External Systems (Email, APIs, Databases)

Worker System

What Are Workers?

Workers are lightweight, specialized computers that execute your workflows. Think of them as digital employees that can:

  • Run workflows 24/7 without breaks
  • Handle multiple tasks simultaneously
  • Scale up during busy periods
  • Scale down when work is light
  • Recover automatically from failures

How Workers Operate

Stateless Design

  • Each worker can run any workflow
  • No data stored locally on workers
  • Easy to replace if one fails
  • Simple to add more when needed

Automatic Management

  • System creates workers when demand increases
  • Shuts down idle workers to save resources
  • Maintains optimal pool size automatically
  • Handles worker health and replacement

Regional Distribution

  • Workers deployed globally
  • Your workflows run close to your users
  • Reduced latency for better performance
  • Compliance with data residency requirements

Worker Lifecycle

Starting Up

  1. System detects need for more capacity
  2. New worker spins up in under 30 seconds
  3. Worker registers with orchestrator
  4. Becomes available for workflow execution

Processing Work

  1. Receives workflow from orchestrator
  2. Executes steps according to definition
  3. Reports progress and results back
  4. Marks itself available for next task

Scaling Down

  1. Worker completes current tasks
  2. Remains idle for 5+ minutes
  3. System marks for shutdown
  4. Worker gracefully terminates
  5. Resources returned to pool

Orchestration System

Central Coordination

The orchestrator is the "air traffic control" of your workflow system:

Job Management

  • Receives workflow execution requests
  • Queues jobs based on priority
  • Assigns jobs to available workers
  • Monitors execution progress
  • Handles failures and retries

Worker Management

  • Tracks all worker status
  • Decides when to create new workers
  • Routes jobs to optimal workers
  • Handles worker failures gracefully
  • Maintains performance metrics

Resource Optimization

  • Balances workload across workers
  • Predicts capacity needs
  • Optimizes for cost and performance
  • Manages regional distribution
  • Handles traffic spikes automatically

Intelligent Scheduling

Priority Handling

  • Urgent workflows jump to front of queue
  • Normal workflows processed in order
  • Low-priority jobs run during off-peak times
  • Custom priority levels for organizations

Load Balancing

  • Distributes work evenly across workers
  • Considers worker capacity and location
  • Avoids overloading any single worker
  • Adapts to changing conditions dynamically

Failure Recovery

  • Automatically retries failed jobs
  • Reassigns work from failed workers
  • Maintains backup workers for critical processes
  • Escalates persistent issues to support

Reliability Features

High Availability

No Single Points of Failure

  • Multiple orchestrators for redundancy
  • Worker pools across different regions
  • Database replication and backups
  • Network routing redundancy

Graceful Degradation

  • System continues operating during issues
  • Non-critical features may be temporarily limited
  • Priority given to running workflows
  • Full recovery when issues resolve

Disaster Recovery

  • Complete system backups
  • Cross-region failover capability
  • Data recovery procedures
  • Business continuity planning

Data Protection

Persistent Storage

  • All workflow data saved to database
  • Complete audit trails maintained
  • Results preserved even if workers fail
  • Long-term data retention policies

Security Measures

  • End-to-end encryption
  • Secure communication between components
  • Access control and authentication
  • Regular security audits and updates

Backup Systems

  • Multiple data center locations
  • Real-time data replication
  • Point-in-time recovery capability
  • Automated backup verification

Performance Characteristics

Scalability

Automatic Scaling

  • Workers scale from 1 to 1000+ automatically
  • Response to traffic spikes in under 1 minute
  • Global capacity management
  • Cost optimization through right-sizing

Capacity Planning

  • System learns your usage patterns
  • Pre-scales for known busy periods
  • Maintains buffer capacity for unexpected load
  • Provides capacity planning reports

Speed Optimization

Execution Speed

  • Workers optimized for specific tasks
  • Pre-warmed workers for instant response
  • Caching of frequently used data
  • Efficient resource utilization

Network Optimization

  • Content delivery networks (CDN)
  • Regional data centers
  • Optimized routing protocols
  • Compression and caching

Monitoring & Operations

System Monitoring

Health Checks

  • Continuous monitoring of all components
  • Early detection of potential issues
  • Automatic remediation when possible
  • Alerting for manual intervention needs

Performance Tracking

  • Real-time metrics collection
  • Historical trend analysis
  • Performance benchmarking
  • Capacity utilization reports

Error Tracking

  • Comprehensive error logging
  • Error pattern analysis
  • Automatic error categorization
  • Proactive issue identification

Maintenance Operations

Updates & Patches

  • Zero-downtime deployment process
  • Gradual rollout of updates
  • Automatic rollback if issues detected
  • Maintenance window notifications

Capacity Management

  • Proactive capacity expansion
  • Resource optimization
  • Cost management
  • Performance tuning

Security Operations

  • Regular security updates
  • Threat monitoring
  • Incident response procedures
  • Compliance maintenance

Enterprise Features

Advanced Configuration

Custom Regions

  • Deploy workers in specific regions
  • Data sovereignty compliance
  • Latency optimization
  • Regulatory requirements

Resource Allocation

  • Dedicated worker pools
  • Custom capacity limits
  • Priority queue management
  • SLA enforcement

Integration Options

  • VPN connectivity
  • Private network access
  • Custom authentication
  • Specialized protocols

Support & SLA

Service Level Agreements

  • 99.9% uptime guarantee
  • Response time commitments
  • Escalation procedures
  • Performance benchmarks

Support Tiers

  • 24/7 technical support
  • Dedicated account managers
  • Custom training programs
  • Professional services

Understanding Your Impact

What This Means for You

Reliability

  • Your workflows run consistently
  • Minimal downtime or interruptions
  • Automatic recovery from failures
  • Peace of mind for critical processes

Performance

  • Fast execution times
  • Handles traffic spikes gracefully
  • Scales with your business growth
  • Optimized for your use patterns

Cost Efficiency

  • Pay only for what you use
  • Automatic optimization saves money
  • No infrastructure to manage
  • Predictable pricing model

Best Practices

Workflow Design

  • Design for reliability from the start
  • Plan for reasonable execution times
  • Include appropriate error handling
  • Test thoroughly before production

Monitoring

  • Set up appropriate alerts
  • Review performance regularly
  • Monitor for unusual patterns
  • Plan capacity for growth

Optimization

  • Use parallel execution where beneficial
  • Optimize data flow between steps
  • Leverage caching for repeated data
  • Consider regional deployment options