ReusePolicy

Package: flyte

Configure a task environment for container reuse across multiple task invocations.

When environment creation is expensive relative to task runtime, reusable containers keep a pool of warm containers ready, avoiding cold-start overhead. The Python process may be reused by subsequent task invocations.

Total concurrent capacity is max_replicas * concurrency. For example, ReusePolicy(replicas=(1, 3), concurrency=2) supports up to 6 concurrent tasks.

Caution: The environment is shared across invocations — manage memory and resources carefully.

Example:

        
    
env = flyte.TaskEnvironment(
    name="fast_env",
    reusable=flyte.ReusePolicy(replicas=(1, 3), concurrency=2),
)

Parameters

        
    
class ReusePolicy(
    replicas: typing.Union[int, typing.Tuple[int, int]],
    idle_ttl: typing.Union[int, datetime.timedelta],
    concurrency: int,
    scaledown_ttl: typing.Union[int, datetime.timedelta],
)

Parameter	Type	Description
`replicas`	`typing.Union[int, typing.Tuple[int, int]]`	Number of container replicas to maintain. - `int`: Fixed replica count, always running (e.g., `replicas=3`). - `tuple(min, max)`: Auto-scaling range (e.g., `replicas=(1, 5)`). Scales between min and max based on demand. Default is `2`. A minimum of 2 replicas is recommended to avoid starvation when the parent task occupies one replica.
`idle_ttl`	`typing.Union[int, datetime.timedelta]`	Environment-level idle timeout — shuts down all replicas when the entire environment has been idle for this duration. Specified as seconds (`int`) or `timedelta`. Minimum 30 seconds. Default is 30 seconds.
`concurrency`	`int`	Maximum concurrent tasks per replica. Values greater than 1 are only supported for `async` tasks. Default is `1`.
`scaledown_ttl`	`typing.Union[int, datetime.timedelta]`	Per-replica scale-down delay — minimum time to wait before removing an individual idle replica. Prevents rapid scale-down when tasks arrive in bursts. Specified as seconds (`int`) or `timedelta`. Default is 30 seconds. Note the distinction: `idle_ttl` controls when the whole environment shuts down; `scaledown_ttl` controls when individual replicas are removed during auto-scaling.

Properties

Property	Type	Description
`max_replicas`	`None`	Returns the maximum number of replicas.
`min_replicas`	`None`	Returns the minimum number of replicas.

Methods

Method	Description
`get_scaledown_ttl()`	Returns the scaledown TTL as a timedelta.

get_scaledown_ttl()

        
    
def get_scaledown_ttl()

Returns the scaledown TTL as a timedelta. If scaledown_ttl is not set, returns None.