# Microservices Layer

The _Microservices Layer_ in Bragabot’s architecture is designed to encapsulate specific business logic into independently deployable and scalable services. Each microservice in this layer is responsible for a particular domain or feature of Bragabot, ensuring that the platform is modular, flexible, and maintainable. This layer is built using Django, a powerful web framework, and leverages the Data Layer for database interactions. Scheduling tasks are managed using Telegram Job Queues, and authentication is handled through the Telegram Mini App initData validation.&#x20;

## **Components and Functionality of the Microservices Layer**

### **1. User Management Service**

* **Role and Functionality:** The User Management Service is responsible for handling all user-related operations, including registration, authentication, profile management, and access control. This service ensures that users can securely interact with Bragabot, manage their accounts, and access the platform’s features according to their roles and permissions.
* **Key Features:**
  * **User Registration:** Handles the creation of new user accounts, including the validation of Telegram Mini App initData.
  * **Authentication:** Validates user sessions using Telegram’s initData, ensuring secure access without the need for additional authentication mechanisms.
  * **Profile Management:** Allows users to update their profiles, manage settings, and view their activity history.
  * **Role-Based Access Control (RBAC):** Implements role-based permissions, ensuring that users have access only to the features and data appropriate for their role.
* **Integration:** This service interacts with the Data Layer to store and retrieve user information and logs activity to the History Service for audit purposes.

### **2. Group Admins Service**

* **Role and Functionality:** The Group Admins Service manages group admins, their permissions, and their interactions with Bragabot’s features. This service ensures that group admins can effectively manage their groups, configure settings, and oversee bot operations.
* **Key Features:**
  * **Admin Registration:** Manages the registration and authentication of group admins using Telegram initData.
  * **Group Management:** Allows admins to configure group settings, manage funds, and create raids or giveaways.
  * **Permissions Management:** Handles the assignment of permissions to admins, ensuring they can access and manage only the groups and bots they are authorized to control.
* **Integration:** This service interacts with the Data Layer to store group and admin information and updates the History Service with changes made by admins.

### **3. Custom Twitter Fetching Service**

* **Role and Functionality:** The Custom Twitter Fetching Service is responsible for fetching tweets based on specific criteria and forwarding them to Telegram groups or tracking live mentions. This service supports features like Tweets Forwarding, Live Twitter Mentions, and KOL (Key Opinion Leader) Management.
* **Key Features:**
  * **Tweets Forwarding:** Captures tweets from the project account and forwards them to designated Telegram groups.
  * **Live Twitter Mentions:** Monitors Twitter for mentions of specific hashtags or keywords and relays these mentions to the relevant Telegram groups.
  * **KOL Management:** Tracks and manages the activities of KOLs, including monitoring their tweets and engagement metrics.
* **Integration:** This service uses the Twitter API to fetch tweets, interacts with the Data Layer to store fetched data, and uses the Notifications Service to alert groups about new tweets and mentions.

### **4. Raid Management Service**

* **Role and Functionality:** The Raid Management Service orchestrates the creation, management, and execution of raids within Bragabot. It handles the scheduling of raids, assignment of tasks to participants, and tracking of raid progress.
* **Key Features:**
  * **Raid Creation:** Allows admins to create and configure new raids, including setting objectives, timelines, and rewards.
  * **Task Assignment:** Automatically assigns tasks to raid participants based on their roles.
  * **Progress Tracking:** Monitors the progress of ongoing raids, updating participants on their status and ensuring that objectives are met.
* **Integration:** This service interacts with the Data Layer to store raid data, uses the Scheduling Services for timing and task distribution, and logs raid activities to the History Service.

### **5. Raids Validation Service**

* **Role and Functionality:** The Raids Validation Service ensures that all tasks performed during a raid are completed correctly and fairly. It validates the actions of participants and approves the distribution of rewards.
* **Key Features:**
  * **Task Validation:** Checks that all tasks assigned during a raid have been completed according to the defined criteria.
  * **Reward Distribution:** Validates participants’ contributions and approves the distribution of rewards based on their performance.
  * **Anti-Fraud Measures:** Implements checks to prevent fraudulent activities, ensuring that raids are conducted fairly.
* **Integration:** This service interacts with the Data Layer to verify task completion, and logs validation results to the History Service.

### **6. White-label Bot Service**

* **Role and Functionality:** The White-label Bot Service enables clients to create bots that are fully customized to their branding, including logos, colors, and behavior. This service ensures that clients can deploy bots that seamlessly integrate with their brand identity.
* **Key Features:**
  * **Brand Customization:** Allows clients to upload branding assets and configure the appearance and behavior of their bots.
  * **Bot Deployment:** Deploys the customized bots within the Kubernetes cluster, ensuring that they are isolated and managed separately from other bots.
  * **Ongoing Support:** Provides tools for clients to manage and update their white-label bots as needed.
* **Integration:** This service interacts with the Data Layer to store branding and bot configuration data, uses the Notifications Service for bot-related alerts, and logs activities to the History Service.

### **7. Custom Bot Generator Service**

* **Role and Functionality:** The Custom Bot Generator Service allows group admins to create and deploy custom bots tailored to their specific needs. This service supports the configuration of various bot types, including moderation bots, task bots, airdrop bots etc.
* **Key Features:**
  * **Bot Creation:** Provides an interface for admins to configure and generate custom bots with specific behaviors and integrations.
  * **Bot Deployment:** Deploys the configured bots within the Kubernetes cluster, ensuring they are isolated and scalable.
  * **Bot Management:** Allows admins to update, manage, and monitor the bots they have created.
* **Integration:** This service interacts with the Data Layer to store bot configurations, uses the Notifications Service to alert admins about bot status, and logs bot activities to the History Service.

### **8. Notifications Service**

* **Role and Functionality:** The Notifications Service manages the delivery of notifications to users, admins and groups, informing them of important events such as new raids, tweet mentions, or bot actions. This service ensures timely and relevant communication across the platform.
* **Key Features:**
  * **Real-Time Notifications:** Delivers instant notifications via Telegram based on user or group preferences and system events.
  * **Event Subscription:** Allows users to subscribe to specific events, ensuring they receive notifications relevant to their interests.
  * **Bulk Notifications:** Supports sending notifications to large groups of users, such as during a raid or when important updates are made to a bot.
* **Integration:** This service interacts with all other microservices to receive event triggers, uses the Data Layer to store notification preferences, and logs notification delivery statuses to the History Service.

### **9. Scheduling Service**

* **Role and Functionality:** The Scheduling Services manage the timing and execution of scheduled tasks across Bragabot. This includes evaluating and distributing raid rewards after completion, updating chat information and admin lists daily, and fetching messages from Telegram groups for moderation and leaderboards.
* **Key Features:**
  * **Task Scheduling:** Uses Telegram Job Queues to schedule and execute tasks at specific times or intervals, ensuring that operations are performed consistently and without manual intervention.
  * **Daily Updates:** Automates the daily update of chat information, admin lists, and other time-sensitive data.
  * **Moderation Support:** Fetches and processes messages from Telegram groups to support moderation efforts and update leaderboards.
* **Integration:** This service interacts with the Data Layer to fetch and update relevant data, coordinates with the Raid Management and Raids Validation Services for post-raid evaluations, and logs scheduling activities to the History Service.

### **10. Wallet Service**

* **Role and Functionality:** The Wallet Service manages financial transactions within Bragabot, including deposits, and other wallet-related operations. This service ensures that group admins can manage their funds securely and that transactions are processed accurately.
* **Key Features:**
  * **Deposit Management:** Handles the processing of deposits, ensuring that funds are credited to groups accounts securely and promptly.
  * **Transaction Tracking:** Tracks all wallet transactions, providing group admins with a history of their financial activities within the platform.
  * **Integration with Rewards:** Works with the Raids Management Service to create raids with rewards for users to participants.
* **Integration:** This service interacts with the Data Layer to store and manage transaction data, uses the Notifications Service to alert group admins of financial activities, and logs all transactions to the History Service.

### **11. History Service**

* **Role and Functionality:** The History Service maintains a comprehensive log of all activities and transactions within Bragabot, providing an audit trail for compliance, troubleshooting, and analytics. This service ensures that historical data is available for analysis and reporting.
* **Key Features:**
  * **Activity Logging:** Captures detailed logs of all user actions, system events, and transactions across the platform.
  * **Audit Trail:** Provides an auditable record of all significant events, ensuring transparency and accountability.
  * **Data Retention:** Manages the retention and archival of historical data, ensuring that it is stored securely and can be retrieved when needed.
* **Integration:** This service interacts with all other microservices to collect and store logs, provides data to the Telemetry and Analytics Service for reporting, and ensures compliance with data retention policies.

### **12. Telemetry and Analytics Service**

* **Role and Functionality:** The Telemetry and Analytics Service is responsible for collecting, processing, and analyzing data from various components of Bragabot to provide insights into system performance, user behavior, and feature usage. This service generates reports and visualizations that help us optimize platform operations, identify trends, and make informed decisions about resource allocation and feature enhancements.
* **Key Features:**
  * **Data Collection::** The service aggregates telemetry data from all microservices, including metrics such as API response times, database query performance, user activity, and system load. It captures events related to user interactions, system health, and error occurrences, providing a comprehensive view of the platform's operations.
  * **Real-Time Analytics:** Provides real-time analysis of data, enabling us to monitor the current state of the platform and respond quickly to any issues or performance bottlenecks. Supports real-time dashboards that visualize key metrics, allowing for proactive management of the platform’s resources and features.
  * **Historical Data Analysis:** Analyzes historical data to identify trends and patterns, which can be used for capacity planning, feature development, and optimization of existing services. Provides insights into user engagement and behavior over time, helping to tailor the platform’s features to better meet user needs.
  * **Reporting and Visualization:** Generates detailed reports on system performance, user activity, and other critical metrics. These reports can be customized to focus on specific aspects of the platform. Integrates with visualization tools like Grafana to create interactive dashboards that display data in a user-friendly format, making it easier for us to understand and act on the information.
* **Integration:**
  * **Microservices Interaction:** Collects telemetry and log data from all microservices, including the User Management Service, Raid Management Service, and Custom Twitter Fetching Service, ensuring that all aspects of the platform are monitored.
  * **Data Layer Interaction:** Stores telemetry data in the Data Layer, allowing for both real-time and historical analysis. The service can query this data to generate reports and insights.
  * **Alerts and Notifications:** Works with the Notifications Service to send alerts when specific thresholds are breached, such as high error rates, increased latency, or unusual user behavior. This ensures that potential issues are addressed promptly.



The Microservices Layer is a cornerstone of Bragabot’s architecture, enabling the platform to function as a modular, scalable, and maintainable system. Each microservice is designed to handle specific aspects of Bragabot’s operations, from user management and group administration to raid management and financial transactions. By leveraging Django, the Data Layer, Telegram Job Queues, and Telegram Mini App initData for authentication, Bragabot ensures that its services are secure, efficient, and capable of meeting the diverse needs of its users and clients.
