The core of modern cloud development involves the **DevOps and CI/CD** (Continuous Integration/Continuous Delivery) pipeline, ensuring rapid, reliable, and continuous delivery of software.
1. Planning and Architecture Design 🏗️
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1.1 Define Requirements
- Gather detailed requirements for functionality, **performance, scalability**, security, and compliance.
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1.2 Select Cloud Services
- Choose specific cloud services (e.g., AWS Lambda, Azure Cosmos DB) that fit the **Serverless, Microservices**, or Monolithic architecture.
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1.3 Design Architecture
- Create high-level and detailed designs, planning for **resiliency** across availability zones/regions.
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1.4 IaC Strategy
- Decide on the **Infrastructure as Code (IaC)** tool (e.g., Terraform) for managing cloud resources.
2. Development and Local Testing 💻
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2.1 Code Development
- Write code, focusing on **cloud-native practices** (e.g., statelessness, using environment variables).
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2.2 Version Control
- Commit all code (application and IaC) to a centralized **Git repository**.
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2.3 Unit Testing
- Run unit tests to ensure individual functions and components work as expected.
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2.4 Containerization
- Package the application using **Docker** to ensure consistency across environments (if applicable).
3. Continuous Integration (CI) 🔄
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3.1 Trigger Build
- A code commit triggers the **CI pipeline** (e.g., Jenkins, GitHub Actions).
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3.2 Automated Tests
- Run **Integration Tests**, **Security Scans (SAST)**, and Code Quality Checks.
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3.3 Artifact Creation
- If tests pass, the pipeline builds the final deployable artifact (e.g., Docker image) and stores it in a **registry**.
4. Continuous Delivery/Deployment (CD) 🚀
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4.1 Provision Environment
- The CD pipeline uses **IaC** to automatically provision resources in a **Staging/Test** environment.
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4.2 Deployment
- The artifact is deployed to the Staging environment.
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4.3 System Testing
- Execute automated functional, performance, load tests, and **Dynamic Application Security Testing (DAST)**.
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4.4 Promote to Production
- If tests pass, deploy to **Production** using safe techniques like **blue/green** or **canary deployments**.
5. Monitoring, Feedback, and Iteration 📊
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5.1 Observability Setup
- Implement logging, metrics, and tracing tools (e.g., Prometheus, CloudWatch) for production insight.
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5.2 Alerting
- Set up alerts based on key performance indicators (KPIs) like error rates and latency.
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5.3 Feedback Loop
- Gather real-world performance data and user feedback.
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5.4 Iteration
- Data feeds back into the planning stage, starting the cycle over for continuous improvement.