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How Queue Execution Works
Cloud Worker Architecture
Concurrency Control
Queue Management
Key Features
Orchestration
Queue Service
Manage and orchestrate your automation workflows with queuing system
How Queue Execution Works
Pinkfish uses a modern cloud worker execution model that automatically handles resource management and scaling. Instead of managing individual “robots” or servers, your workflows run on cloud workers that scale automatically based on demand.
Cloud Worker Architecture
Automatic Scaling
: Cloud workers spin up and down based on queue demand
Isolation
: Each workflow runs in its own isolated environment
Resource Management
: No need to provision or manage infrastructure
Cost Efficient
: Pay only for actual execution time
Concurrency Control
Control how many workflows run simultaneously at two levels:
Customer Concurrency Limit
: Your overall account limit for parallel executions
Queue-Specific Concurrency
: Set per-queue limits for fine-grained control
This replaces traditional “robot management” with a simpler, more scalable approach.
Queue Management
Create custom queues to organize automation workflows:
Queue Name
: Descriptive name for your queue
Concurrency
: Control simultaneous job execution
Max Retries
: Set retry attempts for failed jobs
Priority
: Define queue priority levels
Monitor queues with real-time status showing pending jobs, running jobs, and queue actions.
Key Features
Scalable Processing
: Handle large volumes of automation runs
Batch Operations
: Upload and process multiple jobs simultaneously
Comprehensive Monitoring
: Full visibility into queue performance via Monitor tab
Questions?
Reach out on Discord
https://discord.com/invite/HaDg7R4VZG
Monitor
Batch Service
Assistant
Responses are generated using AI and may contain mistakes.