Serverless Backend with AWS Lambda & API Gateway · Pelajaran

Menerapkan Aplikasi SAM

Gunakan SAM CLI untuk membangun, menguji secara lokal, dan menerapkan aplikasi tanpa server Anda ke AWS sambil mengelola berbagai lingkungan.

Menerapkan Aplikasi SAM adalah pelajaran Serverless Backend with AWS Lambda & API Gateway gratis di CoddyKit. Ini adalah pelajaran 3 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar Serverless Backend with AWS Lambda & API Gateway, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Serverless Backend with AWS Lambda & API Gateway mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

Introduction to SAM CLI

Welcome to deploying SAM applications! The AWS Serverless Application Model Command Line Interface (SAM CLI) is your best friend for building and managing serverless projects.

It extends AWS CloudFormation to simplify defining serverless resources. The SAM CLI provides commands to build, test, and deploy your serverless applications.

Building Your Application

Before deploying, your SAM application needs to be built. The sam build command takes your application code and dependencies, then prepares them for deployment.

It packages dependencies (e.g., Python libraries).
It transpiles code if needed (e.g., TypeScript to JavaScript).
It creates a deployable artifact in a .aws-sam/build directory.

Example Lambda Function

Let's look at a simple Python Lambda function and its template.yaml. The sam build command processes this to create deployable code.

After running sam build, the packaged code would be ready for local testing or deployment.

import json

def lambda_handler(event, context):
    """
    A simple Lambda handler.
    """
    return {
        "statusCode": 200,
        "headers": {
            "Content-Type": "application/json"
        },
        "body": json.dumps({
            "message": "Hello from your SAM Lambda!"
        })
    }

Local Testing with `sam local invoke`

The SAM CLI allows you to test your Lambda functions locally without deploying them to AWS, saving time and costs. Use sam local invoke to simulate a Lambda invocation.

You can pass event data directly to your function, just like how AWS services (like API Gateway or S3) would trigger it.

Running a Lambda Locally

To test the Lambda function from the previous scene, you'd use sam local invoke with the logical ID of your function and an event file.

For example, sam local invoke MyHelloWorldFunction --event event.json would test a function named 'MyHelloWorldFunction' using the data in event.json.

{
  "httpMethod": "GET",
  "path": "/hello",
  "queryStringParameters": null,
  "headers": {
    "Accept": "*/*"
  },
  "body": null
}

Local API Testing with `sam local start-api`

If your SAM application includes an API Gateway, you can simulate the entire API locally using sam local start-api. This command starts a local web server that mimics API Gateway.

You can then send HTTP requests to http://127.0.0.1:3000 and test your API endpoints end-to-end, locally.

Preparing for Deployment: `sam deploy`

Once your application is built and tested locally, you're ready to deploy it to AWS. The sam deploy command is used for this.

It packages your application artifacts, uploads them to an S3 bucket, and then uses AWS CloudFormation to deploy your serverless resources.

Your First Guided Deployment

For your first deployment, using the --guided flag is highly recommended. It will walk you through setting up necessary parameters interactively.

Stack Name: Unique identifier for your CloudFormation stack.
AWS Region: Where to deploy your resources.
S3 Bucket: For storing deployment artifacts.
Capabilities: Acknowledging IAM resource creation.

Example: sam deploy --guided

Managing Multiple Environments

In real-world scenarios, you'll often have development, staging, and production environments. SAM CLI helps manage this by allowing you to specify different stack names and parameters.

Use distinct Stack Names (e.g., my-app-dev, my-app-prod).
Use --parameter-overrides to pass different values for environment-specific configurations (e.g., database names, API keys).

Quick Check

Which SAM CLI command is used to test your API Gateway endpoints locally?

Recap & Next Steps

Congratulations! You've learned the essential steps for building, testing, and deploying serverless applications using the SAM CLI.

sam build: Packages and prepares your application.
sam local invoke: Tests individual Lambda functions locally.
sam local start-api: Simulates API Gateway for local API testing.
sam deploy: Deploys your application to AWS CloudFormation.

Mastering these commands is key to efficient serverless development!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Menerapkan Aplikasi SAM” gratis?

Ya — teks lengkap “Menerapkan Aplikasi SAM” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Serverless Backend with AWS Lambda & API Gateway, upgrade ke CoddyKit PRO. Kursus Serverless Backend with AWS Lambda & API Gateway mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Menerapkan Aplikasi SAM”?

Gunakan SAM CLI untuk membangun, menguji secara lokal, dan menerapkan aplikasi tanpa server Anda ke AWS sambil mengelola berbagai lingkungan. Kamu berlatih Serverless Backend with AWS Lambda & API Gateway dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai Serverless Backend with AWS Lambda & API Gateway?

Tidak diperlukan pengalaman sebelumnya. Serverless Backend with AWS Lambda & API Gateway di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 3 dari 4.

Berapa lama pelajaran “Menerapkan Aplikasi SAM” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran Serverless Backend with AWS Lambda & API Gateway ini?

Ya. Setiap pelajaran Serverless Backend with AWS Lambda & API Gateway menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

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