Easy Deployment and Operations

About This Topic

Systems don't end when they're built—continuing to operate them is what matters. This project focused on designs that minimize effort from deployment through operations.

Auto-Deployment to Cloud

Just upload source code, and it's automatically deployed to the cloud environment.

Deployment Flow

Push Code

Developer sends code to Git repository

Auto-Detection

Cloud platform detects changes

Build

Install dependencies, compile

Deploy

Roll out new version

Health Check

Verify normal operation and complete

Auto-Deployment Benefits

Auto-Scaling

Even as usage increases, the cloud automatically adjusts resources.

Scaling Mechanism

Quiet Period

Minimal configuration for cost savings. 1 instance handles processing

Access increases

Normal Period

2-3 instances process in parallel

Month-end busy period

Busy Period

Automatically scale out. Distribute request processing

Scaling Points

Serverless architecture means you pay only for what you use. No charges during periods without access, making it cost-effective.

Configuration via Environment Variables

Settings are managed through environment variables. Adjust behavior without changing code.

Required Settings

Optional Settings (with defaults)

Testing Settings

Timeout Settings

Appropriate timeouts are set for long-running processes.

Timeout Control

Request Starts

Begin processing, set timer

Execute Processing

Run API calls, etc.

Timeout Check

Exceeded set time?

Within time

Return result normally

Exceeded

Abort processing, return error

Timeout Setting Guidelines

Distributed Cache Utilization

Using Redis (Upstash) distributed cache enables:

Distributed cache is optional but recommended. Without it, only memory cache operates, but cache isn't shared between instances, risking duplicate processing.