🧠 Text Analyzer API

A NestJS-based text analysis microservice with Redis caching, MongoDB storage, JWT authentication, and ELK integration for logging and observability. Deployable via Docker Compose or Kubernetes.

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🚀 Features

• Text analysis API
• JWT-based authentication
• MongoDB for persistence
• Redis for caching
• ELK stack logging (Logstash, Elasticsearch, Kibana)
• TDD with Jest
• Containerized with Docker & Docker Compose
• Kubernetes-ready

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🛠️ Requirements

• Node.js 20+
• Docker + Docker Compose
• kubectl
• (Optional) Minikube or a K8s cluster
• Helm (optional)

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📂 Project Structure

src/
├── application/       # Business logic
├── core/              # Domain entities and services
├── infrastructure/    # MongoDB, Redis, etc.
├── presentation/      # Controllers, modules
├── shared/            # Config, logger, etc.
└── main.ts            # Entry point

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📦 Installation (Development)

npm install
cp .env.example .env

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🧪 Run with Hot Reload (Dev Mode)

npm run start:dev

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🧪 Run Tests

npm run test
# For test coverage
npm run test:cov

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Test Coverage

------------------------------------|---------|----------|---------|---------|-------------------

File	% Stmts	% Branch	% Funcs	% Lines	Uncovered Line #s
All files	48.82	48.38	45.45	47.43
src	31.7	0	60	25.71
app.controller.ts	100	100	100	100
app.module.ts	0	100	0	0	1-50
app.service.ts	100	100	100	100
main.ts	0	0	0	0	1-19
src/application/text/services	95.74	60	100	95.55	57,84
src/core/text/entities	0	0	0	0	1-5
src/core/text/services	100	100	100	100
text-analyzer.service.ts	100	100	100	100
src/infrastructure/database/models	0	100	100	0	1-9, 1-13
src/infrastructure/redis	54.16	75	42.85	55	22-27,43
src/presentation/auth	60.52	37.5	80	61.29	10-12
src/presentation/auth/jwt.strategy	88.88	50	50	85.71	17
src/presentation/user	68.96	100	80	69.56	11
src/presentation/user/dto	100	100	100	100
src/shared/config	100	62.5	100	100	2-8
src/shared/logging	0	0	0	0	2-55, 1-22
------------------------------------	---------	----------	---------	---------	-------------------

Test Suites: 10 passed, 10 total
Tests: 26 passed, 26 total
Snapshots: 0 total
Time: 15.064 s
Ran all test suites.

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🐳 Docker Compose Setup

To run MongoDB, Redis, ELK, Kibana, and your app locally:

docker-compose up --build

If you wanna run locally:

docker compose up -d elasticsearch logstash kibana filebeat mongodb redis

Access:

• App: http://localhost:3000
• Kibana: http://localhost:5601
• MongoDB: localhost:27017
• Redis: localhost:6379

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📄 API Endpoints

All secured endpoints require a JWT token in the Authorization header like so: Authorization: Bearer <token>

🔐 Auth

Method	Endpoint	Description
POST	/auth/login	Login with username and password
POST	/user/signup	Register a new user

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🧠 Text Analysis

Method	Endpoint	Description
POST	/texts	Submit text for analysis
GET	/texts/:id/characters	Get character count
GET	/texts/:id/words	Get word count
GET	/texts/:id/sentences	Get sentence count
GET	/texts/:id/paragraphs	Get paragraph count
GET	/texts/:id/longest-words	Get longest words list

Replace :id with the actual text ID returned from the POST /texts endpoint.

📊 Log Visualization with Kibana

This project uses the ELK stack (Elasticsearch, Logstash, and Kibana) to collect, process, and visualize logs from the text-analyzer service.

✅ Prerequisites

Make sure the containers are up and running:

docker-compose up --build

🔍 Accessing Logs via Kibana

Once the stack is running, you can view and explore logs in Kibana:

• Kibana URL: http://localhost:5601

🚦 How It Works

• Filebeat monitors the logs directory (./logs) and Docker container logs.
• Logs are forwarded to Logstash for parsing and enrichment.
• Logstash sends the processed logs to Elasticsearch.
• Kibana visualizes the logs stored in Elasticsearch.

📁 Log Storage Location

Logs from the text-analyzer service are mounted locally in:

./logs

Ensure your application writes logs to this directory or to stdout/stderr (which Filebeat is also configured to capture).

📈 Creating a Log Dashboard

1. Open Kibana at http://localhost:5601.
2. Navigate to Discover.
3. Select or create an index pattern (e.g., filebeat-*).
4. You can now filter, search, and view real-time logs.

🛠️ Troubleshooting

• If you don’t see any logs in Kibana, ensure:

  • The ./logs directory exists and contains files.
  • Filebeat and Logstash services are running.
  • Your app is writing logs to the correct location.

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☸️ Kubernetes Deployment

Step 1: Build & Push Image

docker build -t your-dockerhub-username/text-analyzer:latest .
docker push your-dockerhub-username/text-analyzer:latest

Step 2: Create Secrets

kubectl create namespace text-analyzer

kubectl create secret generic mongo-secret \
  --from-literal=MONGO_USER=mongoUser \
  --from-literal=MONGO_PASS=secretPass \
  -n text-analyzer

kubectl create secret generic redis-secret \
  --from-literal=REDIS_HOST=redis \
  --from-literal=REDIS_PORT=6379 \
  -n text-analyzer

Step 3: Deploy App + Dependencies

kubectl apply -f k8s/deploy.yaml

You can use Helm or Kustomize for advanced deployment configuration (optional).

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✅ To-Do

• JWT Auth
• User Service
• ELK Logging
• Redis Cache
• MongoDB Store
• Kubernetes Deployment
• Rate limiting / throttling
• CI/CD Integration (GitHub Actions)