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UpdateDeploymentStrategyRequest

Source code in docs_src/capo_appconfig/types/update_deployment_strategy_request.py
class UpdateDeploymentStrategyRequest(TypedDict, closed=True):
    deployment_strategy_id: (
        "capo_appconfig.types.deployment_strategy_id.DeploymentStrategyId"
    )
    """<p>The deployment strategy ID.</p>"""
    description: NotRequired["capo_appconfig.types.description.Description"]
    """<p>A description of the deployment strategy.</p>"""
    deployment_duration_in_minutes: NotRequired[
        "capo_appconfig.types.minutes_between0_and24_hours.MinutesBetween0And24Hours"
    ]
    """<p>Total amount of time for a deployment to last.</p>"""
    final_bake_time_in_minutes: NotRequired[
        "capo_appconfig.types.minutes_between0_and24_hours.MinutesBetween0And24Hours"
    ]
    """<p>The amount of time that AppConfig monitors for alarms before considering the deployment to be complete and no longer eligible for automatic rollback.</p>"""
    growth_factor: NotRequired["capo_appconfig.types.growth_factor.GrowthFactor"]
    """<p>The percentage of targets to receive a deployed configuration during each interval.</p>"""
    growth_type: NotRequired["capo_appconfig.types.growth_type.GrowthType"]
    """<p>The algorithm used to define how percentage grows over time. AppConfig supports the following growth types:</p> <p> <b>Linear</b>: For this type, AppConfig processes the deployment by increments of the growth factor evenly distributed over the deployment time. For example, a linear deployment that uses a growth factor of 20 initially makes the configuration available to 20 percent of the targets. After 1/5th of the deployment time has passed, the system updates the percentage to 40 percent. This continues until 100% of the targets are set to receive the deployed configuration.</p> <p> <b>Exponential</b>: For this type, AppConfig processes the deployment exponentially using the following formula: <code>G*(2^N)</code>. In this formula, <code>G</code> is the growth factor specified by the user and <code>N</code> is the number of steps until the configuration is deployed to all targets. For example, if you specify a growth factor of 2, then the system rolls out the configuration as follows:</p> <p> <code>2*(2^0)</code> </p> <p> <code>2*(2^1)</code> </p> <p> <code>2*(2^2)</code> </p> <p>Expressed numerically, the deployment rolls out as follows: 2% of the targets, 4% of the targets, 8% of the targets, and continues until the configuration has been deployed to all targets.</p>"""

deployment_duration_in_minutes instance-attribute

deployment_duration_in_minutes: NotRequired[MinutesBetween0And24Hours]

Total amount of time for a deployment to last.

deployment_strategy_id instance-attribute

deployment_strategy_id: DeploymentStrategyId

The deployment strategy ID.

description instance-attribute

description: NotRequired[Description]

A description of the deployment strategy.

final_bake_time_in_minutes instance-attribute

final_bake_time_in_minutes: NotRequired[MinutesBetween0And24Hours]

The amount of time that AppConfig monitors for alarms before considering the deployment to be complete and no longer eligible for automatic rollback.

growth_factor instance-attribute

growth_factor: NotRequired[GrowthFactor]

The percentage of targets to receive a deployed configuration during each interval.

growth_type instance-attribute

growth_type: NotRequired[GrowthType]

The algorithm used to define how percentage grows over time. AppConfig supports the following growth types:

Linear: For this type, AppConfig processes the deployment by increments of the growth factor evenly distributed over the deployment time. For example, a linear deployment that uses a growth factor of 20 initially makes the configuration available to 20 percent of the targets. After 1/5th of the deployment time has passed, the system updates the percentage to 40 percent. This continues until 100% of the targets are set to receive the deployed configuration.

Exponential: For this type, AppConfig processes the deployment exponentially using the following formula: G*(2^N). In this formula, G is the growth factor specified by the user and N is the number of steps until the configuration is deployed to all targets. For example, if you specify a growth factor of 2, then the system rolls out the configuration as follows:

2*(2^0)

2*(2^1)

2*(2^2)

Expressed numerically, the deployment rolls out as follows: 2% of the targets, 4% of the targets, 8% of the targets, and continues until the configuration has been deployed to all targets.