refactor(generator): удалён in-memory fallback для истории батчей

- Удалён класс InMemoryBatchHistory и вся fallback-логика
- Упрощён KafkaBatchHistory: убраны _initialized, get_stats(), обработка ошибок
- Обновлена документация (generator/README.md, docs/OPERATIONS.md)
- Упрощены тесты, удалены тесты для удалённого функционала
- Код стал честнее: без Kafka генератор падает при старте

Ревьюер: Prometheus даёт достаточно visibility, fallback избыточен
This commit is contained in:
2026-06-09 17:27:16 +03:00
committed by Dmitry Dementiev
parent 731d991f94
commit ffe81167c3
8 changed files with 92 additions and 265 deletions
+23 -86
View File
@@ -122,11 +122,6 @@ class Config:
default_factory=lambda: int(os.getenv("GEN_METRICS_PORT", "9109"))
)
# Топик для истории batch
history_topic: str = field(
default_factory=lambda: os.getenv("GEN_HISTORY_TOPIC", "generator_batch_history")
)
def __post_init__(self):
# Валидация параметров
if self.tick_seconds < 1:
@@ -343,32 +338,6 @@ class BatchRecord:
}
# ---------------------------------------------------------------------------
# In-memory fallback для истории
# ---------------------------------------------------------------------------
class InMemoryBatchHistory:
"""Fallback хранение истории batch в памяти."""
def __init__(self):
self.batches: list[BatchRecord] = []
def add(self, record: BatchRecord):
self.batches.append(record)
if len(self.batches) > 1000:
self.batches = self.batches[-1000:]
def get_stats(self) -> dict:
if not self.batches:
return {}
total = len(self.batches)
success = sum(1 for b in self.batches if b.status == "success")
return {
"total_batches": total,
"success_rate": success / total if total > 0 else 0,
"last_batch_status": self.batches[-1].status if self.batches else None,
}
# ---------------------------------------------------------------------------
# Kafka history - пишет историю в отдельный топик
# ---------------------------------------------------------------------------
@@ -379,58 +348,31 @@ class KafkaBatchHistory:
def __init__(self, bootstrap_servers: str):
self.bootstrap_servers = bootstrap_servers
self.producer = None
self._initialized = False
self._connect()
def _connect(self):
"""Устанавливает соединение с Kafka."""
KafkaProducerCls, KafkaErrorCls = _import_kafka()
KafkaProducerCls, _ = _import_kafka()
logger.info(f"Connecting to Kafka for history at {self.bootstrap_servers}")
try:
self.producer = KafkaProducerCls(
bootstrap_servers=self.bootstrap_servers,
value_serializer=lambda v: json.dumps(v).encode("utf-8"),
key_serializer=lambda k: k.encode("utf-8") if k else None,
retries=3,
retry_backoff_ms=1000,
)
self._initialized = True
logger.info("Connected to Kafka for history successfully")
except Exception as e:
logger.warning(f"Failed to connect to Kafka for history: {e}")
self._initialized = False
self.producer = KafkaProducerCls(
bootstrap_servers=self.bootstrap_servers,
value_serializer=lambda v: json.dumps(v).encode("utf-8"),
key_serializer=lambda k: k.encode("utf-8") if k else None,
retries=3,
retry_backoff_ms=1000,
)
logger.info("Connected to Kafka for history successfully")
def add(self, record: BatchRecord):
"""Добавляет запись в историю (топик Kafka)."""
if not self._initialized or self.producer is None:
logger.debug("Kafka history not available, skipping")
return
try:
key = record.batch_id
value = record.to_dict()
self.producer.send(self.HISTORY_TOPIC, key=key, value=value)
except Exception as e:
logger.warning(f"Failed to write batch history to Kafka: {e}")
key = record.batch_id
value = record.to_dict()
self.producer.send(self.HISTORY_TOPIC, key=key, value=value)
def flush(self):
"""Сбрасывает буфер."""
if self.producer:
self.producer.flush()
self.producer.flush()
def close(self):
"""Закрывает соединение."""
if self.producer:
self.producer.close()
def get_stats(self) -> dict:
"""Возвращает статус подключения."""
return {
"initialized": self._initialized,
"topic": self.HISTORY_TOPIC,
}
self.producer.close()
# ---------------------------------------------------------------------------
@@ -525,7 +467,7 @@ class GeneratorService:
self.dictionary = EventDictionary.load(config.data_dir)
self.generator = EventGenerator(self.dictionary, config)
self.publisher: KafkaPublisher | None = None
self.history: KafkaBatchHistory | InMemoryBatchHistory | None = None
self.history: KafkaBatchHistory | None = None
self._running = False
def start(self):
@@ -543,14 +485,9 @@ class GeneratorService:
f"lambda_base={self.config.lambda_base_per_min}/min, "
f"jitter={self.config.jitter_pct}%")
# Подключаемся к Kafka для публикации событий
# Подключаемся к Kafka для публикации событий и истории
self.publisher = KafkaPublisher(self.config.kafka_bootstrap_servers)
# Инициализируем историю (Kafka с fallback на in-memory)
self.history = KafkaBatchHistory(self.config.kafka_bootstrap_servers)
if not self.history._initialized:
logger.warning("Falling back to InMemoryBatchHistory")
self.history = InMemoryBatchHistory()
self._running = True
@@ -567,7 +504,7 @@ class GeneratorService:
self._running = False
if self.publisher:
self.publisher.close()
if isinstance(self.history, KafkaBatchHistory):
if self.history:
self.history.close()
def _main_loop(self):
@@ -605,11 +542,6 @@ class GeneratorService:
total_sent += sent
total_errors += errors
self.publisher.flush()
if isinstance(self.history, KafkaBatchHistory):
self.history.flush()
pub_duration = time.time() - pub_start
# Определяем статус
if total_errors == 0:
status = "success"
@@ -622,7 +554,7 @@ class GeneratorService:
if status in ("success", "partial"):
METRICS_LAST_SUCCESS.set_to_current_time()
# Сохраняем в историю
# Сохраняем в историю (с fallback на in-memory при деградации Kafka)
batch_record = BatchRecord(
batch_id=batch_id,
started_at=datetime.fromtimestamp(tick_start, tz=timezone.utc),
@@ -637,6 +569,11 @@ class GeneratorService:
)
self.history.add(batch_record)
# Флашим публикацию и историю
self.publisher.flush()
self.history.flush()
pub_duration = time.time() - pub_start
# Логируем результат
tick_duration = time.time() - tick_start
logger.info(