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TraceMyPods – Application Workflow (Dev Focused)

TraceMyPods is AI ChatBot with OllamaAI integration, enabling users to interact with AI models effortlessly. This platform is designed for developers and DevOps engineers, offering a comprehensive solution for building, deploying, and managing microservice architectures

Tech Stack : Kafka | Redis | MongoDB | Ollama (AI) | Node.js | Python | GO |VectorDB (qdrant) | Microservices | Payments (razorpay) | Invoice/Reports | EMAIL | PostmanCollection | LoadTesting | OpenTelemetry | Gemini_AI | S3 (File Browser) | Image Generation API

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📍 Landing Page

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🤖 AI Assistant (Chat Box)

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Workflow Overview

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Workflow Architecture

This document outlines the architecture and workflow of the TraceMyPods application, detailing how various components interact to provide a seamless AI chatbot experience.

• App level communication
• kafka uses
• why vectors and otel
• why razorpay payment
• why mongo db and redis
• why ollama and free model —>

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Routes and APIs and post requests

• /api/ask : Handles AI queries and routes them to the appropriate model.
• /api/redis-data : Provides Redis analytics and active user data.
• /api/db-data : Displays MongoDB analytics and user data.
• /api/s3-data : Fetches S3 analytics and file browser data.
• /api/s3-page : Displays S3 file browser with pagination.
• /api/s3-analytics : Provides S3 analytics and file statistics.
• /api/s3-presigned : Generates presigned URLs for S3 files.
• /api/s3-folders : Lists S3 folders for file organization.
• /api/s3-search : Implements advanced search capabilities for S3 files.
• /deliver : Handles invoice delivery via email.
• /order : Manages order processing and payment verification.
• /send-otp : Sends OTP for email verification during order processing.
• /verify-otp : Verifies OTP for email confirmation.
• /create-order : Creates an order after payment verification.
• /verify-payment : Verifies payment status with Razorpay.
• /api/token : Manages token generation and validation.
• /api/validate-premium-token : Validates premium tokens for model access.
• /api/services : Lists services of jaeger and their traces.
• /api/heatmap : Provides a heatmap of user interactions and application performance from jaeger.
• /api/traces : Displays trace information for requests and their paths.
• /api/chat : Manages chat sessions and user interactions in oteldashapi.
• /api/optimize : Provides optimization suggestions for application performance.
• /otel (rewritten to /) : Integrates OpenTelemetry for observability.
• / (default/fallback route) : Serves the main application interface, including the chat box and admin dashboard.
• Public API used :
  • Cloudflare workers AI for Image Generation
  • Gemini AI assistant in Jaeger Traces Explanation
• Internal Routes:
  • /api/embedding : Handles embedding generation for user queries.
  • /api/vector : Manages vector storage and retrieval using Qdrant.

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🧩 Components Overview (ARCH)

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1. Frontend Pod: ai-frontend

Simple browser UI as Landing Page build on pure html

• Tech: HTML, CSS, JavaScript
• /chat.html : Frontend chat box with prompt & token input
• /image.html : Image Generation UI with text input
• /admin.html : Admin dashboard for analytics and data management
  • s3 file browser
  • active users
  • redis and mongo db analytics
  • Bucket Invoices
  • S3 Search
  • Total Orders and Revenue
• /otel : OpenTelemetry dashboard for observability integrated with jaeger and Gemini AI
• /pay.html : Payment page to buy premium model access

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2. adminapi microservice

• Tech: Node.js, Express, MongoDB, Redis, S3
• Handles admin operations, analytics, and data management.
• Provides endpoints for viewing Redis, MongoDB, and S3 analytics.
• Show active users, total orders, and revenue.
• Integrates with S3 for invoice preview with presigned URLs.
• Backed by Advanced search capabilities for S3 files.

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3. askapi microservice

• Tech: Node.js, Express, Redis, MongoDB, Ollama
• Handles AI queries and token validation from mongo db and redis.
• Routes requests to the appropriate AI model.
• Integrates with vectorapi to create embedding and store in vector DB and handle vector search for enhanced query handling.
• Uses OpenTelemetry for tracing and send otel traces to Jaeger and then later visualized in otel dashboard.

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4. deliverapi microservice

• Tech: Node.js, Express, S3, Kafka
• Manages invoice generation and and Email delivery to users.
• Integrates with S3 for invoice storage
• Uses Kafka for event-driven processing of order events.

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5. tokenapi microservice

• Tech: Node.js, Express, MongoDB, Redis
• Manages token generation and validation.
• Issues free tokens for basic model access and store in Redis with 1-hour TTL.
• Generate and Validates premium tokens against MongoDB for paid model and cache in Redis.
• Integrates with orderapi for premium token issuance after payment.

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6. orderapi microservice

• Tech: Node.js, Express, MongoDB, Redis, Kafka
• Handles order processing, Email verification via OTP and payment verification.
• Integrates paymentapi which is backend by Razorpay for payment processing.
• Integrate with Tokenapi to Generates premium tokens upon successful payment and stores them in Redis and MongoDB.
• Created orders and tokens send to kafka topic for further processing e.g. deliverapi

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7. paymentapi microservice

• Tech: Node.js, Express, Razorpay
• Manages payment operations using Razorpay (test-keys).
• Handles OTP verification and payment completion.
• Integrates with orderapi to create premium tokens after payment.

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8. oteldash microservice

• Tech: React, Gemini AI
• Provides observability dashboards for monitoring application traces and performance.
• Integrates with Jaeger for distributed tracing visualization.
• Displays metrics and traces from various microservices.
• Dashboard AI Feature include :
  • Trace visualization with detailed spans and logs.
  • Integration with Gemini AI for enhanced trace explanations.
  • Get Optimized Recommendations based on trace data.
  • Trace Explanation using Gemini AI for better understanding of complex traces.

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9. otelapi microservice

• Tech: Go, OpenTelemetry, Jaeger
• Backend for OpenTelemetry metrics and traces.
• Get traces from jaeger and visualized in oteldash.
• Provides APIs for querying and visualizing metrics.
• handle the AI explanation of traces using Gemini AI.

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10. vectorapi microservice

• Tech: Python, Qdrant, Embeddings
• Manages vector embeddings and similarity search.
• Integrates with Qdrant for efficient vector storage and retrieval.
• Integrate with embeddingapi to create embeddings for user queries and store them in Qdrant.
• Integrates with askapi to check vector cache before querying AI models.

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11. embeddingapi microservice

• Tech: Python, OpenAI Embeddings, Qdrant
• Generates embeddings for user queries using OpenAI’s embedding models.
• Handles embedding generation for text queries.
• Integrates with vectorapi for storing and querying embeddings.

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12. Other Services

ollamapods

• Hosts various AI models using Ollama.
• Provides endpoints for querying AI models.
• Supports Custom Model Hosting and management.

REDIS

• Caching layer for token storage and user sessions ttl 1 hour
• Used for quick lookups and reducing database load

MongoDB

• Primary database for user data, orders details and premium tokens
• Stores persistent data with high availability

Qdrant (VectorDB)

• Specialized database for storing and querying vector embeddings
• Supports efficient similarity search and retrieval

Kafka (Event Streaming)

• Used to handle order and delivery events
• Ensures decoupled communication between services

S3 (AWS)

• Object storage for invoices and other files
• Provides scalable storage with presigned URLs for secure access

Cloudflare AI Workers

• Provides AI capabilities for text/image generation
• Integrates with the application for enhanced AI features

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13. Load Testing

• Load testing is performed using k6 to ensure the application can handle high traffic.
• Simulates user interactions and measures performance metrics.

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AI Models Overview

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Top Models

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Mini Models

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📌 Author

Ahmad Raza
Sr. DevOps Engineer | Cloud Infra Specialist
🔗 ahmadraza.in
🔗 linkedin.com/in/ahmad-raza-devops

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For more, visit ahmadraza.in
Detailed commands, manifests, and guides are available on my blog.