Elastic Autoscaling
Pay only for the resources you actually use with RepoCloud’s dynamic scaling system
Elastic Hourly Autoscaling
RepoCloud’s Elastic Hourly Autoscaling is an intelligent resource management system that automatically adjusts your application’s resources based on actual usage, helping you optimize performance while minimizing costs.
How Autoscaling Works
Traditional cloud hosting requires you to choose a fixed resource tier and pay for those resources 24/7, regardless of actual usage. With RepoCloud’s autoscaling:
Real-time Monitoring
Our system continuously monitors your application’s resource utilization (CPU, RAM, and storage).
Dynamic Resource Allocation
When demand increases, additional resources are instantly allocated to maintain performance.
Automatic Optimization
During periods of lower activity, resources scale down automatically to reduce costs.
Hourly Billing
You’re billed hourly based on the actual resources consumed, rather than a fixed monthly amount.
The Autoscaling Advantage
Cost Efficiency
Pay only for what you use, reducing waste from idle resources
Performance Optimization
Automatically handle traffic spikes without manual intervention
Resource Efficiency
Stop paying for idle servers during low-traffic periods
Simplified Management
No need to predict exact resource requirements in advance
Understanding Resource Scaling
RepoCloud’s autoscaling works by dynamically adjusting three primary resources:
CPU Scaling
Memory (RAM) Scaling
Storage Scaling
Real-World Savings Examples
Example 1: Blog with Variable Traffic
A blog typically receives most of its traffic during business hours and very little overnight:
- Fixed Tier Approach: Would require provisioning for peak traffic (4GB RAM, 2vCPU) at $12/month
- With Autoscaling: Average resource usage might be only 1.5GB RAM and 0.8vCPU across 24 hours
- Resulting Billing: Approximately $4.50/month (62.5% savings)
Example 2: Business Application with Weekend Drop-offs
An internal business application used primarily Monday to Friday:
- Fixed Tier Approach: Requires 8GB RAM, 4vCPU at $24/month
- With Autoscaling: Resources scale down by 80% during weekends (28.6% of the month)
- Resulting Billing: Approximately $18.85/month (21.5% savings)
Example 3: E-commerce with Seasonal Peaks
An e-commerce store with significant traffic during holiday seasons:
- Fixed Tier Approach: Would need to provision for peak season (16GB RAM, 8vCPU) at $48/month year-round
- With Autoscaling: Resources might average 4GB RAM, 2vCPU during regular periods
- Resulting Billing: Averaged across the year, approximately $18/month (62.5% savings)
Applications with highly variable usage patterns typically see the greatest savings from autoscaling, sometimes reaching 70-90% cost reduction compared to fixed-tier pricing.
Setting Up Autoscaling
Enabling autoscaling for your RepoCloud application is simple:
Navigate to Instance Management
Go to your application’s management page in the RepoCloud dashboard
Access Scaling Options
Click on the “Scale” tab to view resource management options
Enable Autoscaling
Toggle the “Elastic Autoscaling” option to enable it
Set Resource Boundaries (Optional)
Optionally, set minimum and maximum resource limits to control scaling boundaries
Save Changes
Click “Apply Changes” to enable autoscaling for your application
Autoscaling Controls
When setting up autoscaling, you have several controls to fine-tune the behavior:
Minimum Resources
Set the minimum resources that your application should always have available. This ensures that your application always has at least a baseline level of performance, even during very low usage periods.
Maximum Resources
Define the upper limit for scaling to prevent unexpected costs. By setting a maximum, you ensure that your application won’t scale beyond your budget, even during unexpected traffic spikes.
Scaling Sensitivity
Adjust how quickly the system responds to changes in resource demand:
- High Sensitivity: Scales quickly in response to small changes in demand
- Medium Sensitivity: Balanced approach to scaling (default)
- Low Sensitivity: Waits for sustained changes before scaling
Monitoring and Analytics
RepoCloud provides comprehensive monitoring tools to help you understand your application’s resource usage:
Resource Graphs
Visualize CPU, RAM, and storage usage over time
Scaling Events
Track when your application scaled up or down
Cost Projections
Estimate costs based on current usage patterns
Usage Insights
Get recommendations to optimize resource utilization
Billing with Autoscaling
With autoscaling enabled, your billing works differently from fixed-tier pricing:
- Hourly Metering: Resources are measured on an hourly basis
- Usage Calculation: We calculate the average resource usage for each hour
- Hourly Rate: Each hour is billed based on the resources consumed during that hour
- Monthly Billing: All hourly charges are aggregated for your monthly bill
- Minimum Charge: A minimum of $3.00 per month applies to all applications
Billing for autoscaled applications is transparent and predictable. You can view detailed usage reports in your dashboard to understand exactly what you’re being charged for.
Autoscaling Limitations
While autoscaling is powerful, there are some limitations to be aware of:
- Platform Apps: Autoscaling is not available for Platform Apps (Coolify and Dokploy)
- Minimum Charge: All applications have a minimum charge of $3.00 per month
- Resource Constraints: Some applications may have minimum resource requirements to function properly
- Scaling Delays: There may be a brief delay (typically seconds) in responding to sudden, extreme spikes in demand
When to Choose Fixed Resources
While autoscaling works well for most applications, fixed resources might be better in some scenarios:
Optimizing for Autoscaling
To get the most from autoscaling, consider these best practices:
- Monitor Usage Patterns: Understand your application’s typical resource usage patterns
- Set Appropriate Limits: Configure minimum and maximum resources based on your application’s needs
- Design for Variability: Structure your application to efficiently handle variable resources
- Regular Review: Periodically review scaling analytics to optimize your settings
- Test Performance: Verify that your application performs well at different resource levels