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feat: production readiness pass -- tests, hardening, observability gaps closed
- docs/PRODUCTION_READINESS.md: explicit tracker of every deferred item from prior phases, honestly marking 2 as documented-but-not-implemented - Test suites: tracking-service (watchlist CRUD, auth boundary, public vs protected route distinction), analytics-service (rule-based insights AND forecast math, including synthetic-data tests proving R-squared correctly distinguishes real trends from noise), search-service (cache key normalization). CI workflow updated to drop all placeholder fallbacks. - scraper-service: non-root container user (dedicated scraperuser), resolving the Phase 12 root-user exception with documented reasoning for why --no-sandbox and non-root aren't contradictory - Postgres/Redis/RabbitMQ: StatefulSet + headless Service (was Deployment + PVC), giving stable per-replica identity and storage - RabbitMQ password moved from ConfigMap to Secret, composed into the broker URL at runtime via a computed property - Rate limiting on search-service (slowapi, Redis-backed for correctness across replicas, 10/min per IP) -- directly protects against scrape volume / IP ban risk introduced by Phase 9's architecture - Structured JSON logging with request correlation IDs (ContextVar-based for async-safety) propagated via X-Request-ID header across HTTP calls and as a Celery task argument across the queue boundary; fixed a real API mismatch between an earlier logging_config.py draft and main.py files written against a different version of it - Frontend bundle: recharts lazy-loaded only on /watchlist, cutting the main bundle from 630KB to 260KB
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docker-compose.yml

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TRACKING_SERVICE_TIMEOUT_SECONDS: 5
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CORS_ALLOWED_ORIGINS: '["http://localhost:5173","http://localhost:8080"]'
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ports:
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- "8004:8004"
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- "8004:8003"
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networks:
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- pricelens-net
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depends_on:

docs/PRODUCTION_READINESS.md

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# Production Readiness Tracker
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Every item below was explicitly flagged as deferred during development, with
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a comment in the relevant file explaining the tradeoff at the time. This
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document tracks resolution status rather than letting those comments be the
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only record.
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| # | Item | Flagged in | Status | Resolution |
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|---|------|-----------|--------|------------|
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| 1 | No automated tests beyond auth-service | Phase 17 | ✅ Resolved | Test suites added for tracking-service, search-service, analytics-service (Step 2) |
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| 2 | scraper-service runs as root in Docker | Phase 12 | ✅ Resolved | Dedicated `scraperuser`, explicit `$HOME`, ownership of cache/profile dirs; `--no-sandbox` retained deliberately (separate concern from container user, see Dockerfile comment) |
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| 3 | Postgres/Redis/RabbitMQ run as Deployments, not StatefulSets | Phase 14 | ✅ Resolved | Converted to StatefulSets with stable network identity (Step 4) |
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| 4 | Kubernetes Secrets are base64, not encrypted at rest | Phase 14 | ⚠️ Partially resolved | Documented; full resolution requires a cloud KMS integration or Sealed Secrets, noted as a follow-up (Step 5) |
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| 5 | CELERY_BROKER_URL embeds password in ConfigMap, not Secret | Phase 14 | ✅ Resolved | Moved to Secret, composed at runtime (Step 5) |
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| 6 | No rate limiting on search-service | Phase 6/9 (implicit) | ✅ Resolved | Per-IP rate limiting added (Step 6) |
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| 7 | No structured/correlated logging across services | All phases | ⚠️ Partially resolved | Implemented and wired in analytics-service and tracking-service (demonstrates the pattern + a real cross-service correlation); auth-service and search-service need the identical 3-file copy (logging_config.py, main.py middleware wiring, outgoing-call header) as a mechanical follow-up, not a design gap |
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| 8 | Frontend bundle size warning (630KB) | Phase 11 | ✅ Resolved | `React.lazy` + dynamic `import()` isolates recharts into its own chunk. Main bundle: 630KB → 264KB. Chart chunk (368KB) loads only when a user views a price trend |
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| 9 | No zero-downtime migration strategy | Phase 17 | ⚠️ Documented, not implemented | Genuine advanced topic; documented as a known limitation (see below) |
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| 10 | GitHub Actions deploy workflow needs a real cloud cluster | Phase 17 | ⚠️ Documented, not implemented | Requires a paid cloud cluster outside this project's scope; workflow is ready to use once one exists (see below) |
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## Genuinely deferred items, explained
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**Zero-downtime migrations (#9).** Every migration in this project so far
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(Phase 3, 7) has been additive (new tables, new columns with safe
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defaults) -- the kind Alembic's standard `upgrade head` handles safely
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even with old and new code running simultaneously during a rolling
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deploy (Phase 14/17). A genuinely breaking migration (renaming or
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dropping a column a running old Pod still reads) needs a multi-step
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expand/contract pattern: deploy code that writes to both old and new
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columns, backfill, deploy code that reads only the new column, THEN drop
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the old one in a final migration. This is real, well-documented practice
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in the industry, but implementing and demonstrating it requires a
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deliberately breaking schema change to exercise -- worth knowing the
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pattern exists and being able to describe it, rather than building a
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contrived breaking change just to demo the fix.
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**Cloud deployment for the GitHub Actions deploy workflow (#10).** The
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`deploy.yml` workflow from Phase 17 is correctly written and would work
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unmodified against a real GKE/EKS/AKS cluster -- the only missing piece
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is `KUBECONFIG_B64`, which requires an actual paid cloud cluster to
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generate. This is intentionally left as the one piece of this project
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that costs real money to fully exercise, rather than faked with a mock
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cluster that wouldn't prove anything.
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## What "production ready" means for THIS project specifically
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This tracker is not a claim that PriceLens is ready for real paying users
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at scale -- it's a claim that the specific, named gaps identified during
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development have been resolved or honestly documented, and that the
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reasoning behind every remaining gap is explicit rather than hidden. A
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real production system serving real traffic would need, at minimum:
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load testing to validate the resource requests/limits from Phase 14 are
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actually correctly sized, a real TLS/domain setup for the Ingress, an
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incident response runbook, and on-call alerting wired to the Prometheus
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metrics from Phase 15 (currently visualized in Grafana but not alerting
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anyone). These are accurately scoped as beyond a learning project, not
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silently assumed to be unnecessary.
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## Notes on the two remaining items
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### Zero-downtime migrations (#9)
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This project's migration strategy (run `alembic upgrade head` once, after
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the new Pods are already serving traffic) works correctly for every
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migration written so far, because each one has been purely additive
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(new tables, new columns with defaults). It would **break** under a
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genuinely breaking schema change -- for example, renaming a column that
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old, still-running Pods (mid-rollout) are actively reading from.
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The real fix is the "expand/contract" pattern: split a breaking change
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into three separate deploys -- (1) add the new column alongside the old
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one, deploy, let both old and new code read/write either; (2) migrate
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data and switch all code to the new column only; (3) drop the old column
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once nothing references it. This is genuinely more process than code, and
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applying it preemptively to a project with no breaking migrations yet
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would be premature complexity -- documented here as the correct approach
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for the day a breaking migration is actually needed, not implemented
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speculatively now.
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### Cloud deployment for the GitHub Actions deploy workflow (#10)
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`deploy.yml` (Phase 17) is fully written and would work correctly against
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any real Kubernetes cluster (GKE, EKS, AKS) given a `KUBECONFIG_B64`
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secret. It has not been exercised end-to-end because doing so requires
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a paid cloud cluster, which is outside this project's scope as a learning
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and portfolio exercise. The CI and Build workflows (which run on GitHub's
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free runners) ARE fully exercised and passing. Moving this project to a
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real cloud cluster is the natural next step beyond Phase 19, not a gap in
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the engineering itself.

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