Enabling Autoscaling for your Async Service

In this section, we'll explore enabling autoscaling for your async service, a feature that allows your application to dynamically adjust its resources based on real-time demand and predefined metrics. Autoscaling optimizes performance, responsiveness, and resource efficiency..

Autoscaling involves dynamically adjusting computing resources based on real-time demand and predefined metrics. This optimization ensures that your service efficiently utilizes resources while responding to varying traffic loads.

Autoscaling Configuration

Autoscaling configuration involves setting minimum and maximum replica counts as well as defining metrics that trigger autoscaling actions. Here are the available settings for autoscaling:

• Minimum Replicas: The minimum number of replicas to keep available.
• Maximum Replicas: The maximum number of replicas to keep available.
• Cooldown Period: The period to wait after the last trigger reported active before scaling the resource back to 0.
• Polling Interval: This is the interval to check each trigger on

Configuring Autoscaling via UI

To configure autoscaling parameters for your service via the UI, follow these steps:

1. In the Deployment Form, find the "Show advanced fields" toggle button at the bottom.

2. Once activated, the Replicas Section will become visible.
3. Enable Autoscaling by checking the corresponding checkbox.

4. Enter the desired values for both the minimum and maximum replica counts.

4. Click the "Show advanced fields" toggle again.
5. Fill in the cooldown period and polling interval according to your needs.

Async Service Autoscaling Metrics

For your asynchronous service, autoscaling metrics play a crucial role in dynamically adjusting resource allocation to meet changing demands while maintaining optimal performance.

• AWS SQS Average Backlog: This metric measures the average backlog of messages in your AWS SQS queue. It helps your asynchronous service adapt to varying workloads by tracking the queue's message backlog over time.
  This option is only available when the Input Worker is based on AWS SQS.
• NATSAverageBacklog: This metric monitors the average backlog of messages in your NATS message queue. It helps your asynchronous service adapt to varying workloads by tracking the queue's message backlog over time. ChatGPT
  This option is only available when the Input Worker is based on NATS.