uis-cloud-computing/design.md

Design Document

Keep this document brief (2–4 pages), clear, and up-to-date throughout the project. You may use Mermaid diagrams for architecture visuals.

Field	Value (fill in)
Project Name	Personal Finance Tracker
Team Members	Lukáš Trkan, Dejan Ribarovski
Repository URL	https://github.com/dat515-2025/Group-8
Version	v0.1 (update as you iterate)
Last Updated	YYYY-MM-DD

How to use this template

• Replace all placeholders with your project-specific content.
• Keep explanations concise; link to code or docs when helpful.
• Update this document as the design evolves to match the final implementation.

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1. Overview

Briefly describe the application and its purpose.

• Problem statement: What problem are you solving?
  • Keeping track of all personal finances across multiple bank accounts, cash is not easy. We want to simplify it.
• Target users / personas: Who benefits from this?
  • We aim to help people to keep better track of their finance flows, so people can plan bigger expenses or find ways to save money.
• Primary objectives: 3–5 bullet points.
  • Pass th
• Non-goals: What is explicitly out of scope?
• Key features: Short bullet list of core functionality.

2. Architecture

High-level architecture, main components, interactions, and data flow. Include a system diagram.

2.1 System diagram

flowchart LR
    proc_queue[Message Queue] --> proc_queue_worker[Worker Service]
    proc_queue_worker --> ext_mail[(Email Service)]
    proc_cron[Task planner] --> proc_queue
    proc_queue_worker --> ext_bank[(Bank API)]
    proc_queue_worker --> db
    client[Client/UI] --> api[API Gateway / Web Server]
    api --> svc[Web API]
    svc --> proc_queue
    svc --> db[(Database)]
    svc --> cache[(Cache)]

• Components and responsibilities: What does each box do?
• Data flow: How does data move between components?
• State management: Where is state stored (DB, cache, object store)?
• External dependencies: APIs, third-party services, webhooks.

2.2 Data model (if applicable)

• Core entities and relationships (ER sketch or brief description).
• Example records or schemas (link to files or include concise snippets).
• Users, Transactions, Transaction_Categories, User_settings

2.3 APIs (REST/gRPC/GraphQL)

• Swagger

3. Technologies

List the cloud services, libraries, and tools you will use and why.

Technology / Service	Role / Where Used	Why chosen (brief)	Alternatives considered
Python	Back-End	Simplest for both of us	Java, C#, PHP
React	Front-End	Most popular, we dont have exp with FE	Vue, plain JS
REST	BE<->FE API	Simplest	GraphQL
MariaDB	Database	Prior experience	PostgreSQL, CockroachDB
Redis	Cache	Prior experience	Valkey, Memcached
RabbitMQ	Message queue	Prior experience	MQTT, Redis
Python Fast API	API Framework	Simplicity	Flask, Django
Open Tofu	Cluster deployment	Prior experience	Terraform
Talos Cluster	Deployment	Why not	Docker swarn, RKE

Notes:

• Languages & frameworks (e.g., Go, Node, Python; Gin, Fiber, Echo).
• Cloud provider and managed services (compute, DB, storage, messaging).
• CI/CD, IaC, containerization.

4. Deployment

Describe the deployment strategy and infrastructure requirements.

• Environments: prod, local dev
• Runtime platform: Kubernetes
• Infrastructure diagram (optional):

flowchart TB
  subgraph Cloud
    lb[Load Balancer]
    asg[Service / Deployment]
    db[(Managed DB)]
    bucket[(Object Storage)]
  end
  user((User)) --> lb --> asg --> db
  asg --> bucket

• Configuration & secrets: Env vars, secret manager, .env files (never commit secrets).
• Build & release: How artifacts are built; link to CI/CD if used.
• Deployment steps: Summarize here; full, reproducible steps must be in report.md.
• Scaling strategy: Horizontal/vertical scaling, autoscaling triggers.

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Optional Sections

Include the sections below as applicable to your project.

Security

• Authn/Authz model; data protection; TLS/HTTPS; secrets handling; dependency scanning.

Scalability

• Expected load; performance targets; bottlenecks; caching; rate limits.

Monitoring & Logging

• Health checks; logs; metrics (e.g., Prometheus); dashboards; alerting.

Disaster Recovery

• Backups; restore procedures; RPO/RTO targets; failure scenarios.

Cost Analysis

• Main cost drivers; pricing model; cost-saving measures; budget estimate.

References

• Links to papers, docs, blog posts, prior art, and any external resources.

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Change Log

• v0.1 – Initial draft
• v0.2 – Architecture updated to match implementation
• v1.0 – Final version reflecting delivered system