article-app

Article App sends one article to your phone each day. An AWS Lambda checks 33 RSS feeds, selects an article with an estimated reading time of 5–15 minutes, and publishes it to an ntfy topic.

The picker does not learn user preferences. It selects a wildcard category 30% of the time, avoids repeating categories, and limits each source to three selections within 30 days.

The production flow is EventBridge Scheduler → Lambda → ntfy. A private S3 object named state.db stores the SQLite selection history.

Requirements

• Python 3.13
• AWS CLI v2 configured for the target account
• Terraform 1.10 or later
• Make and Git
• An AWS account
• The ntfy app and separate development and production topics

Setup and deployment

1. Create a Python virtual environment and install requirements.txt and requirements-dev.txt.
2. Run make test to verify the application locally. Use make dry-run to exercise the pipeline against live feeds without sending a notification.
3. Create a private, versioned S3 bucket for Terraform state. Configure its name in the S3 backend blocks for both environments. Terraform cannot use a variable for this value because backend configuration is loaded first.
4. Copy each environment's terraform.tfvars.example to terraform.tfvars, then set a unique ntfy_topic and bucket_suffix. These local files are excluded from Git.
5. Initialize and deploy development with make init ENV=dev and make deploy ENV=dev. Confirm it with make invoke ENV=dev.
6. Repeat the initialization, deployment, and invocation with ENV=prod after development works as expected.

ENV defaults to dev, so a command without an environment does not target production.

Common commands

Command	Purpose
make test	Run the offline test suite
make dry-run	Run locally against live feeds without sending
make validate-feeds	Check that configured feeds resolve
make inspect-feeds	Measure usable articles from each feed
make plan ENV=…	Build the package and review infrastructure changes
make deploy ENV=…	Build and apply an environment
make invoke ENV=…	Invoke the deployed function once
make logs ENV=…	Follow the function's CloudWatch logs
make stats ENV=…	Report selection statistics from state.db
make destroy ENV=…	Delete an environment and its state bucket

Environments

Development and production use the same application code but separate AWS resources, ntfy topics, Terraform state, and selection history.

Setting	Development	Production
Schedule	Disabled; manual invocation only	Daily at 07:00 UTC
Log retention	7 days	14 days
Terraform state key	envs/dev/terraform.tfstate	envs/prod/terraform.tfstate

The development deployment catches issues that offline tests cannot, including package compatibility and AWS permission errors.

Repository layout

• src/ contains the application and Lambda handler.
• tests/ contains the pytest suite.
• scripts/ contains feed, packaging, dry-run, and statistics utilities.
• infra/terraform/modules/ contains the reusable AWS modules.
• infra/terraform/envs/ contains the development and production deployments.

Operations and security

The workload is small and is designed for very low AWS usage, but actual cost depends on the account's current AWS pricing and free-tier eligibility.

Annual cost estimate

Current architecture: approximately $0–$1.20 per year. With 1,000 users on the same ntfy topic: approximately $0–$1.20 per year. This assumes one shared daily notification, AWS free allowances, and free ntfy.sh.

See security.md for IAM, storage, encryption, secret-handling, and vulnerability-reporting details.

Production state.db contains the complete send history. Destroying the production environment deletes that history and resets category repetition and per-source limits.