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Names Terraform and Docker Compose as the IaC tooling and folds Relevance back into the Description section as a bold subheading to match the PR template structure. Sets target deadline to 26 September, ahead of the course-wide async deadline.
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Assignment Proposal
Title
Crypto & Stock Alerts Telegram Bot — A DevOps Pipeline for a Notification Service
Names and KTH ID
Deadline
26 September
Category
Project
Description
We will build and operate a small Telegram notification service for cryptocurrency and stock price alerts. Users can subscribe to a symbol and define a target price or percentage-change threshold. The application periodically retrieves market prices from external APIs and sends a Telegram notification when an alert condition is reached. Alert subscriptions and state are stored persistently. The application will be written in Python and containerized with Docker.
The main focus of the project is the DevOps workflow around the application, rather than the complexity of the bot itself. The project will include:
The repository will contain the application code, tests, Docker configuration, CI/CD workflows, infrastructure/deployment configuration, and documentation required to reproduce the complete system, together with a short report describing the architecture, CI/CD workflow, infrastructure setup, security and quality automation, tooling choices, and limitations of the system.
Relevance
This project demonstrates a complete DevOps workflow for a long-running service. Each code change is automatically tested, analyzed, and packaged through CI, while accepted changes are automatically published and deployed through CD. The deployment environment is provisioned and defined as code, making it reproducible rather than manually configured. The application also introduces practical DevOps concerns such as external service dependencies, persistent state, secrets management, scheduled background work, containerization, automated security checks, and deployment reliability. This keeps the application itself relatively small while allowing us to focus on designing, implementing, testing, and explaining an end-to-end DevOps pipeline.