Data-Driven DevOps Concepts

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1. Team Strategy

• Knowledge Management and Collaboration Culture: Utilize centralized knowledge management tools and real-time collaboration tools to manage the team’s knowledge and problem-solving methods, and facilitate rapid collaboration.
• Real-time Collaboration and Notification System: Enhance real-time communication and feedback, and establish a system that can share critical notifications immediately.
• Phased Introduction of Automation Tools: Gradually introduce serverless container management tools and IoT device management tools to reduce initial complexity.
• Preparation for Transition to Microservices Architecture: Transition from monolith to microservices to ensure system flexibility and scalability.
• Data-driven Decision Making Automation: Make quick decisions and optimize operations using real-time data analysis tools.
• Lightweight Strategy: Use lightweight procedures and essential tools suitable for small teams to optimize resources and increase efficiency.

2. Development Process Management

Key points:

• Source Code Management: Enhance rapid code merging and work speed through a PR minimization strategy, and realize efficient branch management through a lightweight branch management strategy.
• Monorepo Management: Use dependency management tools and package management tools to eliminate duplicate packages and achieve consistent dependency management.
• CI/CD Pipeline: Automate the build, test, and deployment processes using CI/CD pipeline automation tools, and deploy each microservice independently.
• Deployment Failure Handling Strategy: Quickly address issues during deployment using automatic and manual rollback procedures, and recover quickly when problems occur.

3. AWS-based API Authentication and IoT Management

• API Management: Maintain API documentation using API specification automation tools, and enhance service reliability through API request limitations and security enhancements.
• Authentication and User Management: Automate user management processes and enhance security using user authentication and permission management tools.
• IoT Management and Operations: Manage various IoT devices in real-time using IoT device management tools, and monitor device status using a digital twin strategy.

4. Knowledge Management, Collaboration Culture, Alarm Service

• Knowledge Management: Use centralized knowledge management tools to record key information of the team and centrally manage frequently asked questions (FAQs).
• Enhancing Collaboration Culture: Link real-time collaboration tools with knowledge management tools to support real-time communication and problem-solving, and strengthen the collaboration culture.
• Alarm Service: Use system monitoring and alarm tools to detect performance issues in real-time and respond quickly through real-time notifications.

5. Data Strategy

• Data Collection and Storage: Use serverless computing tools and streaming data processing tools to collect real-time data, and utilize object storage services for long-term data storage.
• Data Processing and Flow Management: Build data pipelines using data processing automation tools and maintain consistent data flow.
• Data Analysis and Insight Extraction: Analyze stored data and provide immediate insights through real-time analysis using SQL-based data analysis tools.
• Visualization and Monitoring: Visualize data and monitor performance issues in real-time using system monitoring tools to detect and resolve issues early.