Completed code challenge

[cookiezGIT]

Cloud Data Engineer Challenge — MR

Summary

This MR delivers an end-to-end, free-tier–friendly AWS data pipeline using Terraform + Python:

• S3 (incoming/) → Lambda (ingest) → RDS PostgreSQL (PostGIS)
• API Lambda (FastAPI + Mangum) → API Gateway (GET /aggregated-data)
• CloudWatch Logs for both Lambdas
• Networking: VPC with public/private subnets; Lambdas run in private subnets
• Zero NAT cost: We intentionally avoid a NAT Gateway (see “NAT note”) and use:
  • Gateway VPC endpoint for S3
  • Interface VPC endpoints for Secrets Manager and CloudWatch Logs
• Local dev: Docker Compose for PostGIS, MinIO, and API (uvicorn)

NAT note (requirement vs implementation): The spec suggests “Lambda must use a NAT Gateway”. I justify using VPC endpoints instead of NAT to stay within free-tier budget (NAT ≈ $30–$35/mo). Endpoints preserve private networking and cover all required egress (S3/Secrets/Logs). I can switch to NAT quickly if reviewers prefer the literal requirement.

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Repository Layout

.
├── README.md
├── docs/
├── examples/
│   ├── airbnb_listings_sample.csv
│   └── s3_put_event.json
├── docker-compose.yml
├── docker/
│   ├── initdb/01_enable_postgis.sql
│   └── lambda_layer/… (optional helper)
├── lambda/
│   ├── ingest/        # S3-triggered CSV→city aggregation→upsert
│   └── api/           # FastAPI + Mangum (GET /aggregated-data)
└── terraform/
    ├── envs/dev/main.tf
    ├── modules/{vpc,endpoints,s3,rds,iam,lambdas,apigw,backup}
    ├── providers.tf
    ├── variables.tf
    └── outputs.tf

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What’s Implemented

• IaC with Terraform modules per concern (VPC, endpoints, S3, RDS, IAM, Lambdas, API GW).
• S3 trigger: ObjectCreated:* with prefix=incoming/ and suffix=.csv → ingest Lambda.
• Aggregation: Normalize city (Title Case), parse price (comma/locale tolerant), compute listing_count + avg_price.
• PostgreSQL + PostGIS: RDS in private subnets; CREATE EXTENSION postgis and table created on first connect.
• API Gateway: Public HTTP API exposing GET /aggregated-data?limit=&city=.
• CloudWatch Logs: Log groups with retention; optional error alarms.

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Additional Features

• Data Quality: Price coercion (handles 1,234.56 and 6,81), city normalization, sanity bounds; invalids skipped.
• Indexing & Query Optimization:
  • idx_agg_count_city (listing_count DESC, city ASC) for API ordering
  • idx_agg_city (city) for lookups
  • idx_agg_geom (GIST) to enable spatial queries (nullable geom)
  • ANALYZE aggregated_city_stats after ingest
• Monitoring & Alerts: CloudWatch Alarms Errors > 0 to SNS (opt-in).
• Automated Backups (optional): AWS Backup daily plan targeting the RDS instance.
• Local Docker: PostGIS + MinIO + local API (uvicorn) for pre-deploy validation.
• CI/Pre-commit (optional wiring): terraform fmt/validate, Python lint (ruff), detect-secrets.

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Deploy Instructions

Prerequisites

• AWS account + IAM credentials for Terraform (us-east-1)
• Terraform, AWS CLI v2, Docker Desktop
• Python 3.10 (local)
• (Windows) make optional; PowerShell fallbacks are in README.md

Configure AWS

aws configure            # region: us-east-1
aws sts get-caller-identity

Build Lambda zips (Linux-compatible wheels)

We vendor dependencies inside the Lambda Python 3.10 Docker image to match Amazon Linux.

Windows (PowerShell):

make clean
make build-linux-all

(If not using make, README includes Docker one-liners to build both zips.)

Apply Terraform

cd terraform/envs/dev
terraform init
terraform apply -var="prefix=renzob-nanlabs" -var="env=dev" -auto-approve

Grab outputs

terraform output -raw s3_bucket
terraform output -raw api_base_url

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Test Instructions

1) End-to-end with S3 Put

BUCKET=$(terraform output -raw s3_bucket)
aws s3 cp ../../examples/airbnb_listings_sample.csv "s3://${BUCKET}/incoming/airbnb_listings_sample.csv" --content-type text/csv
aws logs tail "/aws/lambda/renzob-nanlabs-dev-ingest" --follow

Expected logs: s3_get_object_before, csv_parsed, db_connect_*, done.

2) Query the API

API=$(terraform output -raw api_base_url)
curl "$API/aggregated-data?limit=100"
curl "$API/aggregated-data?city=Berlin&limit=50"

3) Manual Lambda Invoke (optional)

BUCKET=$(terraform output -raw s3_bucket)
cat > event.json <<EOF
{
  "Records": [
    {
      "eventSource": "aws:s3",
      "awsRegion": "us-east-1",
      "eventName": "ObjectCreated:Put",
      "s3": {
        "bucket": { "name": "${BUCKET}" },
        "object": { "key": "incoming/airbnb_listings_sample.csv" }
      }
    }
  ]
}
EOF

aws lambda invoke --function-name renzob-nanlabs-dev-ingest --payload fileb://event.json out.json
cat out.json

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Security & Networking

• Lambdas in private subnets, no public IPs.
• No NAT to stay free-tier; VPC endpoints for S3/Secrets/Logs.
• RDS is private; SG allows only Lambda SG on 5432.
• DB credentials in Secrets Manager (retrieved at runtime).

If NAT is strictly required, I can enable a small nat submodule (IGW + NAT + routes) without changing app code.

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Deliverables Checklist

• ✅ Terraform modules for the full architecture
• ✅ README with Windows/Linux steps and design justifications (incl. NAT rationale)
• ✅ Working API Gateway returning aggregated data from PostgreSQL
• ✅ CloudWatch Logs for Lambda execution/errors
• ✅ examples/ with sample CSV and s3_put_event.json
• ✅ Optional docs/, CI, and pre-commit config

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Assumptions

• CSV minimal schema: city and optional price; others ignored.
• City normalized to Title Case; price parsed with comma/locale tolerance and sanity bounds.
• geom is nullable; GIST index prepped for future spatial queries.

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Troubleshooting

• No logs on upload → Verify S3 notification (ObjectCreated:*, prefix=incoming/, suffix=.csv), ensure region us-east-1, try a new key name.
• psycopg2 missing → Rebuild zips via Docker (make build-linux-all), then terraform apply.
• API 5xx → Tail /aws/lambda/renzob-nanlabs-dev-api; confirm RDS is ready and Secrets accessible.
• Code updated but no change → Ensure source_code_hash = filebase64sha256(...) is set for both Lambdas.