Scale
sfp server scale
sfp server scaleScale worker services for a tenant
sfp server scale
sfp server scaleAdjust the number of worker instances for different queue priorities to handle varying workloads.
USAGE
$ sfp server scale -t <value> [--json] [--passphrase <value>
[--identity-file <value> --ssh-connection <value>]] [--critical-workers
<value>] [--normal-workers <value>] [--batch-workers <value>] [-g
<value>...] [--loglevel
trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL]
FLAGS
-t, --tenant=<value> (required) Name of the tenant
--critical-workers=<value> Number of critical queue workers (1-10)
--normal-workers=<value> Number of normal queue workers (1-10)
--batch-workers=<value> Number of batch queue workers (1-10)
SSH OPTIONS
--ssh-connection=<value> SSH connection string in the format user@host[:port]
--identity-file=<value> Path to SSH private key file
--passphrase=<value> Passphrase for the SSH private key if required
OTHER OPTIONS
--json Format output as json
-g, --logsgroupsymbol=<value>... Symbol used by CICD platform to group/collapse logs
--loglevel=<option> [default: info] logging level for this command invocation
<options: trace|debug|info|warn|error|fatal|TRACE|DEBUG|INFO|WARN|ERROR|FATAL>
DESCRIPTION
Scale worker services for a tenant
Worker Types:
- Critical Workers: Handle high-priority, time-sensitive tasks (auth, critical operations)
- Normal Workers: Process standard operations and deployments
- Batch Workers: Execute background jobs, scheduled tasks, and non-urgent operations
Each worker type can be scaled independently from 1 to 10 instances.
EXAMPLES
$ sfp server scale --tenant my-app --critical-workers 2
$ sfp server scale --tenant my-app --normal-workers 3
$ sfp server scale --tenant my-app --batch-workers 2
$ sfp server scale --tenant my-app --critical-workers 2 --normal-workers 3 --batch-workers 2
$ sfp server scale --tenant my-app --critical-workers 2 --ssh-connection [email protected] --identity-file ~/.ssh/id_rsaWorker Types
Critical Workers
Handle high-priority, time-sensitive operations:
Authentication requests
Security operations
System-critical tasks
Real-time notifications
Normal Workers
Process standard operations:
Package deployments
Build operations
Standard API requests
Regular task processing
Batch Workers
Execute background and scheduled tasks:
Report generation
Data cleanup
Scheduled maintenance
Long-running operations
Scaling Strategies
Scale Up for High Load
Increase workers during peak times:
Scale Down for Maintenance
Reduce workers for maintenance:
Gradual Scaling
Scale workers gradually to test capacity:
Output Formats
Standard Output
JSON Output
Remote Server Scaling
Scale workers on a remote server:
Scaling Recommendations
Based on Load Patterns
Light Load (< 100 operations/hour):
Medium Load (100-1000 operations/hour):
Heavy Load (> 1000 operations/hour):
Auto-Scaling Script
Performance Monitoring
Monitor worker performance after scaling:
Best Practices
Start Conservative: Begin with fewer workers and scale up as needed
Monitor After Scaling: Always check status after scaling operations
Consider Queue Depth: Scale based on queue backlog, not just time
Balance Worker Types: Ensure appropriate ratio between worker types
Plan for Peaks: Pre-scale before expected high-load periods
Troubleshooting
Workers Not Starting
High Memory Usage
Note: Worker scaling changes take effect immediately but may take a few moments for all instances to be fully operational.
Warning: Scaling down workers will gracefully shutdown excess instances, but any running tasks will be completed first.
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