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# 在 Step Functions 中执行状态机版本的逐步部署
<a name="version-rolling-deployment"></a>

滚动部署是一种部署策略，用新版本的应用程序慢慢地替换旧版本的应用程序。要对状态机版本执行滚动部署，可逐渐增加向新版本发送的执行流量。流量大小和增加速度属于一种参数，由用户进行配置。

您可以使用以下选项之一对版本执行滚动部署：
+ [Step Functions 控制台](https://console.aws.amazon.com/states/home?region=us-east-1#/) – 创建指向同一状态机的两个版本的别名。对于此别名，您可以对路由配置进行配置，以便在两个版本之间转移流量。有关使用控制台推出版本的更多信息，请参阅[版本](concepts-state-machine-version.md)和[Aliases](concepts-state-machine-alias.md)。
+ ** AWS CLI 和开发工具包的脚本** – 使用 AWS CLI 或 AWS 开发工具包创建 shell 脚本。有关更多信息，请参阅以下有关使用 AWS CLI CLI 和 AWS 开发工具包的部分。
+ **AWS CloudFormation 模板** – 使用 `[AWS::StepFunctions::StateMachineVersion](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-stepfunctions-statemachine.html)` 和 `[AWS::StepFunctions::StateMachineAlias](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-stepfunctions-statemachine.html)` 资源发布多个状态机版本，并创建指向其中一个或两个版本的别名。

## 使用 AWS CLI 部署新的状态机版本
<a name="version-canary-deploy-cli"></a>

本节中的示例脚本说明了如何使用 AWS CLI 将流量从以前的状态机版本逐渐转移到新的状态机版本。您可以使用此示例脚本，也可以根据需要对其进行更新。

此脚本显示了使用别名部署新状态机版本的金丝雀部署。以下步骤概述了脚本执行的任务：

1. 如果 `publish_revision` 参数设置为 true，则将最新的[revision](concepts-cd-aliasing-versioning.md#statemachinerev)作为状态机的下一个版本发布。如果部署成功，则此版本将成为新的实时版本。

   如果将 `publish_revision` 参数设置为 false，则脚本将部署状态机的上一个已发布版本。

1. 如果别名还不存在，则创建一个别名。如果别名不存在，请将该别名的 100% 流量指向新版本，然后退出脚本。

1. 更新别名的路由配置，将一小部分流量从以前的版本转移到新版本中。您可以使用 `canary_percentage` 参数设置此金丝雀百分比。

1. 默认情况下，每 60 秒监控一次可配置的 CloudWatch 警报。如果其中任何一个警报被触发，请立即回滚部署，将 100% 的流量指向先前的版本。

   在 `alarm_polling_interval` 中以秒为单位定义的每个时间间隔后，继续监控警报。持续监视，直到超过 `canary_interval_seconds` 中定义的时间间隔。

1. 如果在 `canary_interval_seconds` 期间未触发任何警报，则将 100% 的流量转移到新版本。

1. 如果新版本成功部署，则删除任何早于 `history_max` 参数中指定数字的版本。



```
#!/bin/bash
# 
# AWS StepFunctions example showing how to create a canary deployment with a
# State Machine Alias and versions.
# 
# Requirements: AWS CLI installed and credentials configured.
# 
# A canary deployment deploys the new version alongside the old version, while
# routing only a small fraction of the overall traffic to the new version to
# see if there are any errors. Only once the new version has cleared a testing
# period will it start receiving 100% of traffic.
# 
# For a Blue/Green or All at Once style deployment, you can set the
# canary_percentage to 100. The script will immediately shift 100% of traffic
# to the new version, but keep on monitoring the alarms (if any) during the
# canary_interval_seconds time interval. If any alarms raise during this period,
# the script will automatically rollback to the previous version.
# 
# Step Functions allows you to keep a maximum of 1000 versions in version history
# for a state machine. This script has a version history deletion mechanism at
# the end, where it will delete any versions older than the limit specified.
# 
# For an example that also demonstrates linear (or rolling) deployments, see the following: 
# https://github.com/aws-samples/aws-stepfunctions-examples/blob/main/gradual-deploy/sfndeploy.py

set -euo pipefail

# ******************************************************************************
# you can safely change the variables in this block to your values
state_machine_name="my-state-machine"
alias_name="alias-1"
region="us-east-1"

# array of cloudwatch alarms to poll during the test period.
# to disable alarm checking, set alarm_names=()
alarm_names=("alarm1" "alarm name with a space")

# true to publish the current revision as the next version before deploy.
# false to deploy the latest version from the state machine's version history.
publish_revision=true

# true to force routing configuration update even if the current routing
# for the alias does not have a 100% routing config.
# false will abandon deploy attempt if current routing config not 100% to a
# single version.
# Be careful when you combine this flag with publish_revision - if you just
# rerun the script you might deploy the newly published revision from the
# previous run.
force=false

# percentage of traffic to route to the new version during the test period
canary_percentage=10

# how many seconds the canary deployment lasts before full deploy to 100%
canary_interval_seconds=300

# how often to poll the alarms
alarm_polling_interval=60

# how many versions to keep in history. delete versions prior to this.
# set to 0 to disable old version history deletion.
history_max=0
# ******************************************************************************

#######################################
# Update alias routing configuration.
# 
# If you don't specify version 2 details, will only create 1 routing entry. In
# this case the routing entry weight must be 100.
# 
# Globals:
#   alias_arn
# Arguments:
#   1. version 1 arn
#   2. version 1 weight
#   3. version 2 arn (optional)
#   4. version 2 weight (optional)
#######################################
function update_routing() {
  if [[ $# -eq 2 ]]; then
    local routing_config="[{\"stateMachineVersionArn\": \"$1\", \"weight\":$2}]"
  elif [[ $# -eq 4 ]]; then
    local routing_config="[{\"stateMachineVersionArn\": \"$1\", \"weight\":$2}, {\"stateMachineVersionArn\": \"$3\", \"weight\":$4}]"
  else
    echo "You have to call update_routing with either 2 or 4 input arguments." >&2
    exit 1
  fi
  
  ${aws} update-state-machine-alias --state-machine-alias-arn ${alias_arn} --routing-configuration "${routing_config}"
}

# ******************************************************************************
# pre-run validation
if [[ (("${#alarm_names[@]}" -gt 0)) ]]; then
  alarm_exists_count=$(aws cloudwatch describe-alarms --alarm-names "${alarm_names[@]}" --alarm-types "CompositeAlarm" "MetricAlarm" --query "length([MetricAlarms, CompositeAlarms][])" --output text)

  if [[ (("${#alarm_names[@]}" -ne "${alarm_exists_count}")) ]]; then
    echo All of the alarms to monitor do not exist in CloudWatch: $(IFS=,; echo "${alarm_names[*]}") >&2
    echo Only the following alarm names exist in CloudWatch:
    aws cloudwatch describe-alarms --alarm-names "${alarm_names[@]}" --alarm-types "CompositeAlarm" "MetricAlarm" --query "join(', ', [MetricAlarms, CompositeAlarms][].AlarmName)" --output text
    exit 1
  fi
fi

if [[ (("${history_max}" -gt 0)) && (("${history_max}" -lt 2)) ]]; then
  echo The minimum value for history_max is 2. This is the minimum number of older state machine versions to be able to rollback in the future. >&2
  exit 1
fi
# ******************************************************************************
# main block follows

account_id=$(aws sts get-caller-identity --query Account --output text)

sm_arn="arn:aws:states:${region}:${account_id}:stateMachine:${state_machine_name}"

# the aws command we'll be invoking a lot throughout.
aws="aws stepfunctions"

# promote the latest revision to the next version
if [[ "${publish_revision}" = true ]]; then
  new_version=$(${aws} publish-state-machine-version --state-machine-arn=$sm_arn --query stateMachineVersionArn --output text)
  echo Published the current revision of state machine as the next version with arn: ${new_version}
else
  new_version=$(${aws} list-state-machine-versions --state-machine-arn ${sm_arn} --max-results 1 --query "stateMachineVersions[0].stateMachineVersionArn" --output text)
  echo "Since publish_revision is false, using the latest version from the state machine's version history: ${new_version}"
fi

# find the alias if it exists
alias_arn_expected="${sm_arn}:${alias_name}"
alias_arn=$(${aws} list-state-machine-aliases --state-machine-arn ${sm_arn} --query "stateMachineAliases[?stateMachineAliasArn==\`${alias_arn_expected}\`].stateMachineAliasArn" --output text)

if [[ "${alias_arn_expected}" == "${alias_arn}" ]]; then
  echo Found alias ${alias_arn}

  echo Current routing configuration is:
  ${aws} describe-state-machine-alias --state-machine-alias-arn "${alias_arn}" --query routingConfiguration
else
  echo Alias does not exist. Creating alias ${alias_arn_expected} and routing 100% traffic to new version ${new_version}
  
  ${aws} create-state-machine-alias --name "${alias_name}" --routing-configuration "[{\"stateMachineVersionArn\": \"${new_version}\", \"weight\":100}]"

  echo Done!
  exit 0
fi

# find the version to which the alias currently points (the current live version)
old_version=$(${aws} describe-state-machine-alias --state-machine-alias-arn $alias_arn --query "routingConfiguration[?weight==\`100\`].stateMachineVersionArn" --output text)

if [[ -z "${old_version}" ]]; then
  if [[ "${force}" = true ]]; then
    echo Force setting is true. Will force update to routing config for alias to point 100% to new version.
    update_routing "${new_version}" 100
    
    echo Alias ${alias_arn} now pointing 100% to ${new_version}.
    echo Done!
    exit 0
  else
    echo Alias ${alias_arn} does not have a routing config entry with 100% of the traffic. This means there might be a deploy in progress, so not starting another deploy at this time. >&2
    exit 1
  fi
fi

if [[ "${old_version}" == "${new_version}" ]]; then
  echo The alias already points to this version. No update necessary.
  exit 0
fi

echo Switching ${canary_percentage}% to new version ${new_version}
(( old_weight = 100 - ${canary_percentage} ))
update_routing "${new_version}" ${canary_percentage} "${old_version}" ${old_weight}

echo New version receiving ${canary_percentage}% of traffic.
echo Old version ${old_version} is still receiving ${old_weight}%.

if [[ ${#alarm_names[@]} -eq 0 ]]; then
  echo No alarm_names set. Skipping cloudwatch monitoring.
  echo Will sleep for ${canary_interval_seconds} seconds before routing 100% to new version.
  sleep ${canary_interval_seconds}
  echo Canary period complete. Switching 100% of traffic to new version...
else
  echo Checking if alarms fire for the next ${canary_interval_seconds} seconds.

  (( total_wait = canary_interval_seconds + $(date +%s) ))

  now=$(date +%s)
  while [[ ((${now} -lt ${total_wait})) ]]; do
    alarm_result=$(aws cloudwatch describe-alarms --alarm-names "${alarm_names[@]}" --state-value ALARM --alarm-types "CompositeAlarm" "MetricAlarm" --query "join(', ', [MetricAlarms, CompositeAlarms][].AlarmName)" --output text)

    if [[ ! -z "${alarm_result}" ]]; then
      echo The following alarms are in ALARM state: ${alarm_result}. Rolling back deploy. >&2
      update_routing "${old_version}" 100

      echo Rolled back to ${old_version}
      exit 1
    fi
  
    echo Monitoring alarms...no alarms have triggered.
    sleep ${alarm_polling_interval}
    now=$(date +%s)
  done

  echo No alarms detected during canary period. Switching 100% of traffic to new version...
fi

update_routing "${new_version}" 100

echo Version ${new_version} is now receiving 100% of traffic.

if [[ (("${history_max}" -eq 0 ))]]; then
  echo Version History deletion is disabled. Remember to prune your history, the default limit is 1000 versions.
  echo Done!
  exit 0
fi

echo Keep the last ${history_max} versions. Deleting any versions older than that...

# the results are sorted in descending order of the version creation time
version_history=$(${aws} list-state-machine-versions --state-machine-arn ${sm_arn} --max-results 1000 --query "join(\`\"\\n\"\`, stateMachineVersions[].stateMachineVersionArn)" --output text)

counter=0

while read line; do
  ((counter=${counter} + 1))

  if [[ (( ${counter} -gt ${history_max})) ]]; then
    echo Deleting old version ${line}
    ${aws} delete-state-machine-version --state-machine-version-arn ${line}
  fi
done <<< "${version_history}"

echo Done!
```

## 使用 AWS 开发工具包部署新的状态机版本
<a name="version-deploy-sdk"></a>

[aws-stepfunctions-examples](https://github.com/aws-samples/aws-stepfunctions-examples/tree/main/gradual-deploy) 中的示例脚本展示了如何使用适用于 Python 的 AWS 开发工具包将流量从状态机的旧版本逐步转移到新版本。您可以使用此示例脚本，也可以根据需要对其进行更新。

该脚本展示了以下部署策略：
+ **金丝雀** – 流量将通过两次递增进行转移。

  在第一次递增中，将一小部分流量（例如，10％）转移到新版本。在第二次递增中，在指定的时间间隔（以秒为单位）结束之前，将剩余的流量转移到新版本。只有在指定的时间间隔内未触发 CloudWatch 警报时，才会将剩余流量切换到新版本。
+  **线性或滚动** – 以相等的增量将流量转移到新版本中，每个增量之间的间隔秒数相等。

  例如，如果您将增量百分比指定为 **20**，`--interval` 为 **600** 秒，则此部署将每 600 秒增加 20% 的流量，直到新版本接收 100% 的流量。

  如果触发了任何 CloudWatch 警报，此部署会立即回滚新版本。
+ **一次部署全部或蓝/绿** – 立即将 100% 的流量转移到新版本。此部署会监控新版本，并在触发任何 CloudWatch 警报时自动将其回滚到先前版本。

## 使用 AWS CloudFormation 部署新的状态机版本
<a name="version-deploy-cfn"></a>

以下 CloudFormation 模板示例发布了名为 `MyStateMachine` 的状态机的两个版本。它会创建一个名为 `PROD` 的别名，该别名指向这两个版本，然后部署了版本 `2`。

在此示例中，每五分钟将 10% 的流量转移到版本 `2`，直到该版本接收 100% 的流量。此示例还介绍了如何设置 CloudWatch 警报。如果您设置的任何警报进入 `ALARM` 状态，则部署将失败并立即回滚。

```
MyStateMachine:
  Type: AWS::StepFunctions::StateMachine
  Properties:
    Type: STANDARD
    StateMachineName: MyStateMachine
    RoleArn: arn:aws:iam::account-id:role/myIamRole
    Definition:
      StartAt: PassState
      States:
        PassState:
          Type: Pass
          Result: Result
          End: true

MyStateMachineVersionA:
  Type: AWS::StepFunctions::StateMachineVersion
  Properties:
    Description: Version 1
    StateMachineArn: !Ref MyStateMachine

MyStateMachineVersionB:
  Type: AWS::StepFunctions::StateMachineVersion
  Properties:
    Description: Version 2
    StateMachineArn: !Ref MyStateMachine

PROD:
  Type: AWS::StepFunctions::StateMachineAlias
  Properties:
    Name: PROD
    Description: The PROD state machine alias taking production traffic.
    DeploymentPreference:
      StateMachineVersionArn: !Ref MyStateMachineVersionB
      Type: LINEAR
      Percentage: 10
      Interval: 5
      Alarms:
        # A list of alarms that you want to monitor. If any of these alarms trigger, rollback the deployment immediately by pointing 100 percent of traffic to the previous version.
        - !Ref CloudWatchAlarm1
        - !Ref CloudWatchAlarm2
```