48 lines
4.7 KiB
Markdown
48 lines
4.7 KiB
Markdown
## 1. Project Setup & Common Utilities
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- [ ] 1.1 Create project structure, `requirements.txt` (with `confluent-kafka`, `clickhouse-connect`, `phonenumbers`), and `.env.example` defining all environment variables and verify file presence.
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- [x] 1.2 Implement standard library structured JSON logging module emitting `timestamp`, `level`, `service`, `raw_id`, and `event`, and verify output formatting with unit test.
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- [ ] 1.3 Create idempotent ClickHouse canonical initialization schema (`app/worker/schema.sql`) creating database `telecom` and `ReplacingMergeTree` table `cdr_records` with TTL and indexing settings, and verify schema correctness.
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## 2. Framework-less Async Ingestion API
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- [x] 2.1 Implement lightweight HTTP/1.1 server using standard library `asyncio.start_server` with route dispatching for `POST /api/v1/cdr/raw`, `GET /metrics`, and `GET /stats`.
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- [x] 2.2 Implement bounded outstanding-delivery backpressure: verify `429 Too Many Requests` at capacity and `202 Accepted` only after broker acknowledgement.
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- [x] 2.3 Implement incoming payload validation: verify `400 Bad Request` with structured JSON error `{ "error": "...", "detail": "..." }` on malformed JSON or missing required fields.
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- [x] 2.4 Integrate `confluent-kafka` producer publishing to `cdr.raw` using `raw_id` as message key, and return `503 Service Unavailable` if Kafka is unreachable.
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- [x] 2.5 Implement Prometheus metrics endpoint (`cdr_api_received_total`) and public `GET /stats` endpoint that fetches worker runtime stats via internal HTTP and returns unified JSON.
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## 3. Processing Worker Implementation
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- [x] 3.1 Implement Kafka consumer loop with `confluent-kafka` consuming from `cdr.raw` and DLQ producer publishing to `cdr.raw.dlq`.
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- [ ] 3.2 Implement safe parser routing malformed records to DLQ with structured envelope and reason taxonomy (`missing_required_field`, `invalid_rat_value`, `invalid_epoch`, `malformed_json`, `normalization_error`).
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- [ ] 3.3 Implement schema normalizer: E.164 phone conversion via `phonenumbers`, RAT mapping (`1`→`3G`, `6`→`LTE_4G`, `9`→`5G_NR`), `cell_id` derivation (`lac_ci`), and deterministic UUIDv5 `cdr_id` generation.
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- [x] 3.4 Implement micro-batching buffer flushing on 1,000 records or 2 seconds elapsed, batch-inserting into ClickHouse via `clickhouse-connect`, and committing offsets only after ClickHouse ACK.
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- [x] 3.5 Implement exponential backoff retry for ClickHouse write timeouts (`CH_RETRY_MAX_ATTEMPTS`, `CH_RETRY_INITIAL_DELAY_MS`, `CH_RETRY_BACKOFF_FACTOR`) with fallback to DLQ.
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- [x] 3.6 Implement worker internal HTTP stats endpoint (`GET /internal/stats`) and worker Prometheus metrics (`cdr_processed_total`, `cdr_dlq_total`, histograms, gauges).
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- [ ] 3.7 Implement `SIGTERM` and `SIGINT` signal handlers to stop consuming, flush remaining in-memory buffer to ClickHouse, commit offsets, and exit cleanly without data loss.
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## 4. Containerization & Orchestration
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- [x] 4.1 Create lightweight Dockerfiles for Ingestion API and Processing Worker without framework dependencies.
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- [ ] 4.2 Create `docker-compose.yml` defining Kafka/Redpanda, ClickHouse, Ingestion API, and Processing Worker with healthcheck blocks and `depends_on: { condition: service_healthy }`.
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## 5. Verification & Test Traffic Generator
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- [ ] 5.1 Implement traffic generator script covering the 7 mandatory scenarios (valid records, missing fields, malformed JSON, bad RAT, invalid epoch, duplicates, burst load).
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- [ ] 5.2 Implement automated verification summary reporting verifying ClickHouse counts, DLQ counts, API 400 errors, and duplicate resolution.
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- [x] 5.3 Write comprehensive `README.md` covering quickstart, architecture, micro-batching, offset management, deduplication, monitoring, and configuration reference.
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## 6. Delivery Safety Regression Gates
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- [ ] 6.1 Add and pass unit regressions for confirmed API delivery, shutdown, strict validation and HTTP limits.
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- [ ] 6.2 Add and pass worker regressions for partition ordering, DLQ failure, commit failure, replay, batching, range checks and telemetry.
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- [ ] 6.3 Run isolated Compose integration with independent ports/storage, fresh defaults, schema collision/replay and failure recovery checks.
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- [ ] 6.4 Run actual DLQ traffic verification and the acknowledged 500-record burst; record evidence in README.
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- [ ] 6.5 Validate OpenSpec and reconcile all task completion claims with evidence.
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## Current evidence boundary
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Follow-up changes were reviewed and edited without running verification, as requested by the user. Unchecked items require renewed evidence for the current files; this does not imply their implementation is absent. Historical unit passes must not be used to mark changed code or integration/recovery/load scenarios complete. In particular, a verifier run without actual Kafka evidence is not an acceptance result.
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