Serverless Backend with AWS Lambda & API Gateway · Pelajaran

CodePipeline untuk Penerapan

Bangun pipeline rilis otomatis menggunakan AWS CodePipeline untuk mengatur proses build, pengujian, dan penerapan.

Pelajaran 2 dari 411 langkah

CodePipeline untuk Penerapan adalah pelajaran Serverless Backend with AWS Lambda & API Gateway gratis di CoddyKit. Ini adalah pelajaran 2 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.

Meet AWS CodePipeline

Welcome! In modern software development, automating releases is key. AWS CodePipeline helps you achieve Continuous Integration and Continuous Delivery (CI/CD) for your applications, including serverless ones.

CodePipeline is a fully managed service that automates your release process. It orchestrates the steps needed to get your code changes from a source repository through various stages and into production.

Why Use CodePipeline?

Automating your deployments with CodePipeline offers several benefits:

  • Faster Releases: Deliver new features and bug fixes to users quicker.
  • Improved Reliability: Standardized, automated processes reduce human error.
  • Consistent Deployments: Ensures every change follows the same path and checks.
  • Visibility: Track the status of your releases in real-time.

It acts as the central orchestrator for your serverless CI/CD.

Core Pipeline Stages

A CodePipeline typically consists of several stages, each with one or more actions. The most common stages are:

  • Source: Where your code originates (e.g., CodeCommit, GitHub).
  • Build: Where your code is compiled, tested, and packaged (e.g., CodeBuild).
  • Deploy: Where your application is deployed to AWS resources (e.g., CloudFormation, SAM).
  • Test: Where automated tests run to validate the deployed application.

These stages execute in a defined order, creating a workflow.

The Source Stage

The Source stage is the starting point of your pipeline. When you push new code to your repository, CodePipeline detects the change and automatically starts the pipeline.

Common source providers include AWS CodeCommit, GitHub, GitLab, and Amazon S3. For serverless applications, your source typically contains your Lambda code and serverless template (like a SAM template).

The Build Stage with CodeBuild

After the source code is retrieved, it moves to the Build stage. Here, AWS CodeBuild takes over. CodeBuild compiles your code, runs unit tests, and packages your serverless application artifacts.

For a serverless application, this often means creating a deployment package (a .zip file for Lambda) and preparing your AWS Serverless Application Model (SAM) template for deployment.

Buildspec for Serverless Apps

CodeBuild uses a buildspec.yml file in your source repository to define the build commands. Here's a common structure for a Python Lambda with SAM:

version: 0.2
phases:
  install:
    runtime-versions:
      python: 3.9
  build:
    commands:
      - echo "Building SAM application..."
      - sam build --template template.yaml --debug
artifacts:
  files:
    - '**/*'
  base-directory: .aws-sam/build

The Deploy Stage with SAM

The Deploy stage takes the artifacts produced by the build stage and deploys them to your AWS account. For serverless applications, this typically involves AWS CloudFormation, often orchestrated by AWS SAM.

CodePipeline can directly integrate with CloudFormation to execute a SAM template. It uses Change Sets to preview and safely apply infrastructure updates, minimizing risks.

Deployment Action Example

In CodePipeline, a deploy action for a SAM application might look like this (conceptually, configured in the pipeline definition):

  • Action Provider: CloudFormation
  • Action Mode: REPLACE_ON_FAILURE or CREATE_UPDATE
  • Stack Name: YourServerlessAppStack
  • Template Path: The path to your SAM template (e.g., build-artifact::template.yaml)
  • Capabilities: CAPABILITY_IAM (required for many serverless deployments)

This tells CodePipeline to update your CloudFormation stack based on the provided template.

Adding a Test Stage

While unit tests run in the Build stage, a dedicated Test stage in CodePipeline allows for broader validation after deployment. This could include:

  • Integration tests against the deployed API.
  • Smoke tests to ensure basic functionality.
  • End-to-end tests for critical user flows.

You can use another CodeBuild project or a Lambda function to execute these tests. If tests fail, the pipeline can stop the deployment.

Pipeline Check

Consider a serverless application deployed with AWS CodePipeline. Which of the following AWS services are commonly integrated into CodePipeline's stages for a typical serverless CI/CD workflow?

CodePipeline Recap

You've learned how AWS CodePipeline orchestrates your serverless application deployments. Key takeaways:

  • CodePipeline automates CI/CD from code commit to deployment.
  • It uses stages like Source, Build, and Deploy.
  • CodeCommit provides the source, CodeBuild performs builds (using buildspec.yml), and CloudFormation/SAM handles deployments.
  • Test stages ensure quality before production.

By leveraging CodePipeline, you create robust and repeatable deployment processes for your serverless applications!

Gratis untuk memulai

Belajar Serverless Backend with AWS Lambda & API Gateway dengan tutor AI — gratis

Tulis dan jalankan kode asli di browser kamu, dapatkan bantuan instan dari tutor AI 24/7, dan lanjutkan di mana kamu tinggalkan di web atau aplikasi.

Kursus
12
Pelajaran
48

Pertanyaan yang Sering Diajukan

Apakah pelajaran “CodePipeline untuk Penerapan” gratis?

Ya — teks lengkap “CodePipeline untuk Penerapan” 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 “CodePipeline untuk Penerapan”?

Bangun pipeline rilis otomatis menggunakan AWS CodePipeline untuk mengatur proses build, pengujian, dan penerapan. 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 2 dari 4.

Berapa lama pelajaran “CodePipeline untuk Penerapan” 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

  1. CodeCommit dan CodeBuild
  2. CodePipeline untuk Penerapan
  3. Mengotomatiskan Penerapan Tanpa Server
  4. Penerapan Aman dengan Canary dan Rollback
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