How to Deploy Auto Scaling

Auto Scaling in Utho Cloud allows users to deploy instances that automatically scale based on predefined conditions. Follow this guide to deploy an auto-scaling instance efficiently.

Step 0: Login or Sign Up

• Visit the Utho Cloud Platform login page.
• Enter your credentials and click Login .
• If you’re not registered, sign up here.

Step 1: Navigate to Auto Scaling

• Navigate to the auto scaling listing page in your account, or click here to directly access it. .
• Click Create New to open the Auto Scaling deployment page.

Step 2: Configure Your Auto Scaling Instance

1. Choose Data Center Location

• Select the data center closest to your users.

  • Why it’s important : A data center is a physical location where cloud resources are stored. Choosing a nearby data center reduces network latency and improves response time for users.

    

2. Select a Stack

• Pick from your created stacks or available community stacks.

  • Why it’s important : A stack includes the operating system, software configurations, and pre-installed dependencies. It ensures your application runs smoothly with the right environment and avoids compatibility issues.

  • Select Stack Image : When selecting a stack, you will be prompted to choose a stack image from a dropdown menu.

  • A stack image is typically a pre-configured template or image that includes the operating system and the necessary software dependencies (such as web servers, databases, or frameworks) that your application needs to run.

  • Why it’s required : The stack image ensures your instance has all the necessary components to run your application without needing manual configuration. It saves time and ensures consistency across your instances by providing a predefined environment suited to your needs.

    

3. Choose a Plan

• Select a plan based on:

  • RAM : Memory available for your application.
  • vCPUs : Processing power to handle concurrent tasks.
  • SSD disk size : Storage space for data and applications.
  • Bandwidth : Network traffic capacity, determining how much data your instance can send/receive.

• Why it’s important : Choosing the right plan ensures your instance has sufficient resources to run efficiently and stay cost-effective.

• There are three types of plans you can choose from:

  1. Basic Plans : Suitable for general-purpose applications with moderate resource requirements. These plans provide balanced CPU, memory, and storage resources.
  2. CPU Optimized Plans : Designed for compute-intensive tasks such as processing large datasets, running complex algorithms, or handling high-performance applications. These plans offer higher CPU performance.
  3. Memory Optimized Plans : Ideal for memory-heavy applications like databases or caching servers, where large amounts of RAM are required. These plans prioritize memory over CPU performance.

• Why you should choose : Depending on your application’s needs, switching between these plans helps you optimize resources and costs based on whether your workload is more CPU- or memory-intensive.

  

4. Select VPC and Subnet

• Choose a VPC (Virtual Private Cloud) and subnet .

  • Why it’s important : A VPC isolates your cloud resources within a secure network, while a subnet organizes instances in the VPC, improving traffic management and security.

    

5. Choose CPU Model

• Select AMD or Intel based on your performance needs:

  • AMD : Best for cost-effective performance for standard workloads.

  • Intel : Ideal for high-performance tasks like AI or specialized computing.

  • Why it’s important : The right CPU model ensures your instance has the processing power needed for your application’s requirements.

    

6. Configure Firewall (Optional)

• Select a firewall to protect your instance.

  • Why it’s important : A firewall filters inbound and outbound network traffic, helping protect your instance from unauthorized access and threats.

    

7. Attach Load Balancer/Target Group (Optional)

• Attach a Load Balancer or assign to a Target Group .

  • Why it’s important : Load balancers distribute traffic across multiple instances, preventing overloading. Target groups help manage traffic for improved availability and fault tolerance.

    

8. Set Instance Scaling Parameters

• Define the scaling parameters:

  • Max Size : Maximum number of instances allowed.

  • Min Size : Minimum number of instances that must always run.

  • Desired Size : Ideal number of instances under normal conditions.

  • Why it’s important : These parameters ensure your instance scales dynamically based on load, balancing cost and performance.

    

9. Configure Scaling Policy

• Create a scaling policy to trigger scaling based on resource usage:

  • Name : A unique identifier for the scaling policy.
  • Type : Choose between CPU or RAM based scaling depending on the resource that should trigger scaling.
  • Compare : Define whether scaling should occur when usage is above or below the specified threshold.
  • Value : Set the specific resource usage percentage that triggers scaling (e.g., 70% CPU or RAM usage).
  • Adjust : Set the number of instances to add or remove (minimum is 1 instance).
  • Period : Choose the time window for monitoring (e.g., 5 minutes, 1 hour) before triggering scaling.
  • Cooldown : Define the minimum time in seconds to wait before executing another scaling action to prevent excessive scaling.

• Why it’s important : A scaling policy ensures your instance can scale efficiently, maintaining performance while avoiding unnecessary costs

  

10. Set a Scaling Schedule (Optional)

• Predefine scaling actions based on predictable traffic patterns.

  • Name : A unique identifier for the scaling schedule.
  • Desired Size : The number of instances you want to maintain during the scheduled time (minimum 1).
  • Time Zone : Select the time zone for the schedule (e.g., IST, UTC).
  • Recurrence : Choose how often the scaling action should repeat (e.g., Every 5 minutes, Every 30 minutes, Every 1 hour).
  • Day : Select the specific day (fixed to today’s date) when the scaling action should occur.
  • Time : Set the exact time when the scaling action should be triggered (fixed to the current time).
  • Start At : Define the exact date and time the schedule should begin (pick a date and time).

• Why it’s important : A scaling schedule ensures resources are adjusted proactively before traffic surges, improving cost efficiency and performance without relying solely on real-time metrics.

11. Name Your Auto Scaling Instance

• Provide a unique name for your instance.

  • Why it’s important : Naming your instance helps you identify and manage it easily, especially when handling multiple instances.

    

12. Deploy Auto Scaling Instance

• Click Deploy AutoScaling to initiate deployment after checking the deployment cost.

  

Step 3: Verifying your deployed auto scaling instance

• After successful deployment, you will be automatically redirected to the Manage Page of your newly deployed instance.

• On the Manage Page , you can verify the status of your deployment.

• The status will be displayed as “Active” in green color, indicating that your instance is running smoothly.

  

Conclusion

You’ve successfully deployed an Auto Scaling instance on Utho Cloud! This guide helped you configure and deploy your instance, set scaling rules, and optimize performance and cost.