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配置 Amazon Bedrock AgentCore 生命周期设置

的LifecycleConfiguration输入参数CreateAgentRuntime允许您在 Amazon Bedrock AgentCore Runtime 中管理运行时会话和资源的生命周期。此配置通过自动清理空闲会话和防止长时间运行的实例无限期消耗资源来帮助优化资源利用率。

您还可以使用该UpdateAgentRuntime操作为现有 AgentCore 运行时配置生命周期设置。

配置属性

约束

默认 行为

当LifecycleConfiguration未提供或包含空值时，平台将应用以下逻辑：

默认的 值

使用生命周期配置创建 AgentCore 运行时

在创建 AgentCore 运行时时，可以指定生命周期配置。

import boto3

client = boto3.client('bedrock-agentcore-control', region_name='us-west-2')

try:
    response = client.create_agent_runtime(
        agentRuntimeName='my_agent_runtime',
        agentRuntimeArtifact={
            'containerConfiguration': {
                'containerUri': '123456789012.dkr.ecr.us-west-2.amazonaws.com/my-agent:latest'
            }
        },
        lifecycleConfiguration={
            'idleRuntimeSessionTimeout': 1800,  # 30 minutes, configurable
            'maxLifetime': 14400  # 4 hours
        },
        networkConfiguration={'networkMode': 'PUBLIC'},
        roleArn='arn:aws:iam::123456789012:role/AgentRuntimeRole'
    )

    print(f"Agent runtime created: {response['agentRuntimeArn']}")
except client.exceptions.ValidationException as e:
    print(f"Validation error: {e}")
except Exception as e:
    print(f"Error creating agent runtime: {e}")

更新 AgentCore 运行时的生命周期配置

您可以更新现有 AgentCore 运行时的生命周期配置。

import boto3

client = boto3.client('bedrock-agentcore-control', region_name='us-west-2')

agent_runtime_id = 'my_agent_runtime'

try:
    response = client.update_agent_runtime(
        agentRuntimeId=agent_runtime_id,
        agentRuntimeArtifact={
            'containerConfiguration': {
                'containerUri': '123456789012.dkr.ecr.us-west-2.amazonaws.com/my-agent:latest'
            }
        },
        networkConfiguration={'networkMode': 'PUBLIC'},
        roleArn='arn:aws:iam::123456789012:role/AgentRuntimeRole',
        lifecycleConfiguration={
            'idleRuntimeSessionTimeout': 600,   # 10 minutes
            'maxLifetime': 7200                 # 2 hours
        }
    )

    print("Lifecycle configuration updated successfully")
except client.exceptions.ValidationException as e:
    print(f"Validation error: {e}")
except client.exceptions.ResourceNotFoundException:
    print("Agent runtime not found")
except Exception as e:
    print(f"Error updating configuration: {e}")

获取 AgentCore 运行时的生命周期配置

您可以获取现有 AgentCore 运行时的生命周期配置。

import boto3

client = boto3.client('bedrock-agentcore-control', region_name='us-west-2')

def get_lifecycle_config():
    try:
        response = client.get_agent_runtime(agentRuntimeId="my_agent_runtime")

        lifecycle_config = response.get('lifecycleConfiguration', {})
        idle_timeout = lifecycle_config.get('idleRuntimeSessionTimeout', 900)
        max_lifetime = lifecycle_config.get('maxLifetime', 28800)

        print(f"Current configuration:")
        print(f"  Idle timeout: {idle_timeout}s ({idle_timeout//60} minutes)")
        print(f"  Max lifetime: {max_lifetime}s ({max_lifetime//3600} hours)")

        return lifecycle_config

    except Exception as e:
        print(f"Error retrieving configuration: {e}")
        return None

# Usage
config = get_lifecycle_config()
print(config)

验证和限制

生命周期配置包括验证规则和约束条件，以防止配置无效。如果您的请求违反了以下任何规则，则会失败并显示ValidationException：

常见的验证错误

import boto3

client = boto3.client('bedrock-agentcore-control', region_name='us-west-2')

try:
    client.create_agent_runtime(
        agentRuntimeName='invalid_config_agent',
        agentRuntimeArtifact={
            'containerConfiguration': {
                'containerUri': '123456789012.dkr.ecr.us-west-2.amazonaws.com/my-agent:latest'
            }
        },
        lifecycleConfiguration={
            'idleRuntimeSessionTimeout': 3600,  # 1 hour, configurable
            'maxLifetime': 1800                 # 30 minutes - INVALID!
        },
        networkConfiguration={'networkMode': 'PUBLIC'},
        roleArn='arn:aws:iam::123456789012:role/AgentRuntimeRole',
        )
except client.exceptions.ValidationException as e:
    print(f"Validation failed: {e}")
    # Output: idleRuntimeSessionTimeout must be less than or equal to maxLifetime

验证辅助函数

MICROVM_MAX_SECONDS = 28800     # 8 hours
INSTANCES_MAX_SECONDS = 1209600  # 14 days
MIN_SECONDS = 60


def validate_lifecycle_config(idle_timeout, max_lifetime, uses_capacity_provider=False):
    """Validate lifecycle configuration before API call"""
    errors = []

    # The maximum depends on the compute type of the runtime
    maximum = INSTANCES_MAX_SECONDS if uses_capacity_provider else MICROVM_MAX_SECONDS

    # Check range constraints
    if not (MIN_SECONDS <= idle_timeout <= maximum):
        errors.append(f"idleRuntimeSessionTimeout must be between {MIN_SECONDS} and {maximum} seconds")

    if not (MIN_SECONDS <= max_lifetime <= maximum):
        errors.append(f"maxLifetime must be between {MIN_SECONDS} and {maximum} seconds")

    # Check relationship constraint
    if idle_timeout > max_lifetime:
        errors.append(f"idleRuntimeSessionTimeout ({idle_timeout}s) must be <= maxLifetime ({max_lifetime}s)")

    return errors

# Usage
errors = validate_lifecycle_config(3600, 1800)
if errors:
    for error in errors:
        print(f"Validation error: {error}")
else:
    print("Configuration is valid")

生命周期设置和运行时会话

您定义的生命周期配置设置将应用于每个单独的运行时会话。当你使用特定的代理调用代理时runtimeSessionId， AgentCore Runtime 会为该会话预置一个专用 microVM。生命周期超时（idleRuntimeSessionTimeout和maxLifetime）控制该特定 microVM 实例的生命周期。

import boto3
import json
import uuid

client = boto3.client('bedrock-agentcore', region_name='us-west-2')

# Each unique runtimeSessionId gets its own microVM with lifecycle settings applied
session_id_user_1 = str(uuid.uuid4())  # User 1's session
session_id_user_2 = str(uuid.uuid4())  # User 2's session

# First invocation for User 1 - creates new microVM with lifecycle timers
response1 = client.invoke_agent_runtime(
    agentRuntimeArn='arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/my-agent',
    runtimeSessionId=session_id_user_1,  # Dedicated microVM for this session
    payload=json.dumps({"prompt": "Hello from User 1"}).encode()
)

# First invocation for User 2 - creates separate microVM with its own lifecycle timers
response2 = client.invoke_agent_runtime(
    agentRuntimeArn='arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/my-agent',
    runtimeSessionId=session_id_user_2,  # Different microVM for this session
    payload=json.dumps({"prompt": "Hello from User 2"}).encode()
)

# Subsequent invocations to same session reuse the existing microVM
# The idle timeout resets with each invocation to the same session
response3 = client.invoke_agent_runtime(
    agentRuntimeArn='arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/my-agent',
    runtimeSessionId=session_id_user_1,  # Reuses User 1's existing microVM
    payload=json.dumps({"prompt": "Follow-up from User 1"}).encode()
)

有关生命周期设置和会话的要点：

最佳实践

在配置生命周期设置以实现最佳资源利用率和用户体验时，请遵循这些最佳实践。

建议

常见模式