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Error Handling and Retry Strategies in Apache Airflow

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Error Handling and Retry Strategies

Error Handling ArchitectureTask ExecutionRunning stateRetry LogicAutomatic retryTimeoutExecution limitsCallbackson{'_'}failure callbackSLA MonitoringSLA miss alertsRetry Delay Formuladelay = base{''}delay * exponential{''}backoff^retry{'_'}numberState Transitionsrunning {'->'} failed {'->'} up{''}for{''}retry {'->'} queuedAlert ChannelsEmail, Webhook, PagerDuty, SlackKey: retries=3, retry{'_'}delay=5min, timeout=3600s (typical config)

Architecture Diagram

Formal Definitions

Detailed Explanation

Retry Configuration

Airflow provides built-in retry mechanisms for handling transient failures.


Retry Parameters:

ParameterDescriptionExample
retriesNumber of retry attempts3
retry_delayTime between retriestimedelta(minutes=5)
retry_exponential_backoffDouble delay each retryTrue
max_retry_delayMaximum retry delay captimedelta(minutes=30)
execution_timeoutMax task execution timetimedelta(hours=1)

Callback Functions

Callbacks are invoked on specific task state transitions.


Callback Types:

CallbackTriggerUse Case
on_failure_callbackTask failsSend alerts, log errors
on_success_callbackTask succeedsNotify, update external systems
on_retry_callbackTask retriesLog retry attempts
on_execute_callbackTask startsInitialize resources

SLA Configuration

SLAs define expected completion times for tasks.


SLA Parameters:

LevelSettingEffect
DAG-levelsla_miss_callbackInvoked when any task misses SLA
Task-levelsla=timedelta(hours=2)Per-task SLA

SLA Violation Condition: T_completion > T_sla + T_execution_date

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