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
Dynamic Resource Allocation
Automatic Optimization
Hourly Billing
The Autoscaling Advantage
Cost Efficiency
Performance Optimization
Resource Efficiency
Simplified Management
Understanding Resource Scaling
RepoCloud’s autoscaling works by dynamically adjusting three primary resources:CPU Scaling
How CPU Scaling Works
How CPU Scaling Works
- CPU usage is monitored in real-time
- When CPU utilization exceeds thresholds, additional CPU cores are allocated
- During low CPU utilization, resources are reduced to the minimum needed
- Scaling occurs without interruption to your application
Benefits of CPU Scaling
Benefits of CPU Scaling
- Handle processing-intensive tasks efficiently
- Maintain application responsiveness during peak loads
- Reduce costs during periods of low computational demand
- Avoid over-provisioning CPU resources
Memory (RAM) Scaling
How RAM Scaling Works
How RAM Scaling Works
- Memory usage is continuously monitored
- When RAM utilization approaches capacity, additional memory is allocated
- When memory needs decrease, allocation is reduced
- Scaling ensures your application always has sufficient memory without waste
Benefits of RAM Scaling
Benefits of RAM Scaling
- Prevent out-of-memory errors during traffic spikes
- Support memory-intensive operations when needed
- Optimize costs based on actual memory requirements
- Scale memory independently from CPU resources
Storage Scaling
How Storage Scaling Works
How Storage Scaling Works
- Storage usage is monitored
- Additional storage is automatically allocated as needed
- You’re billed only for the storage you actually use
- Scaling occurs without application downtime
Benefits of Storage Scaling
Benefits of Storage Scaling
- Never run out of disk space unexpectedly
- Pay only for the storage you utilize
- Accommodate growing data needs without manual intervention
- Optimize costs for applications with variable storage requirements
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)
Setting Up Autoscaling
Enabling autoscaling for your RepoCloud application is simple:Navigate to Instance Management
Access Scaling Options
Enable Autoscaling
Set Resource Boundaries (Optional)
Save Changes
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
Scaling Events
Cost Projections
Usage Insights
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
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:Predictable Workloads
Predictable Workloads
Budget Certainty
Budget Certainty
Performance Guarantees
Performance Guarantees
Resource-Intensive Applications
Resource-Intensive Applications
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
Frequently Asked Questions
How quickly does autoscaling respond to traffic spikes?
How quickly does autoscaling respond to traffic spikes?
Will my application experience downtime during scaling?
Will my application experience downtime during scaling?
How is billing calculated with autoscaling?
How is billing calculated with autoscaling?
Can I set a maximum monthly budget?
Can I set a maximum monthly budget?
What happens if my application needs more resources than the maximum I set?
What happens if my application needs more resources than the maximum I set?