过滤 output 的使用 get_object 从 S3 获取的 cloudtrail 日志

Question

我正在使用 Lambda function 来跟踪我的实例启动和停止时间。

我确实设置了我的踪迹 - 用于管理事件 - 我的 S3 存储桶附加了适当的权限。 我使用 get_object 从 S3 读取数据。 下面的代码。 Get_object 以字典的形式向我返回数据。 我的下一步是过滤此数据 - 其中“eventName”：“StopInstances”或“StartInsances”。 如果有人可以告诉如何做到这一点。 我尝试了各种字典方法，但没有任何效果。

lambda 处理程序的代码：

def lambda_handler(event, context):
  object_key = 'event_history_j.json'
  bucket = 'demo-cloudtrail-logs-ec2'
  client = boto3.client('s3')
  data = client.get_object(Bucket = bucket , Key = object_key)['Body'].read()
  return data

Output 这个：

{"Records": [
{ "eventVersion": "1.07",
  "userIdentity": {
    "type": "AssumedRole",
    "principalId": "ARO",
    "arn": "arn:aws",
    "accountId": "0123456",
    "accessKeyId": "ABCDEFGH",
    "sessionContext": {
      "sessionIssuer": {
        "type": "Role",
        "principalId": "ARO",
        "arn": "JDHJDJDHJS",
        "accountId": "0123456",
        "userName": "XYZ@ABC.COM"
      },
      "webIdFederationData": {},
      "attributes": {
        "creationDate": "2022-04-22T23:16:28Z",
        "mfaAuthenticated": "JDJDHFD"
      }
    }
  },
  "eventTime": "2022-04-22T23:34:46Z",
  "eventSource": "ec2.amazonaws.com",
  "eventName": "StopInstances",
  "awsRegion": "eu-west-1",
  "sourceIPAddress": "AWS Internal",
  "userAgent": "AWS Internal",
  "requestParameters": {
    "instancesSet": {
      "items": [
        {
          "instanceId": "i-0039483"
        },
        {
          "instanceId": "i-92399"
        }
      ]
    },
    "force": DJDIJ
  },
  "responseElements": {
    "requestId": "FJDSJFJDFJFDJDJ",
    "instancesSet": {
      "items": [
        {
          "instanceId": "i-0039483",
          "currentState": {
            "code": 64,
            "name": "stopping"
          },
          "previousState": {
            "code": 16,
            "name": "running"
          }
        },
        {
          "instanceId": "i-92399",
          "currentState": {
            "code": 64,
            "name": "stopping"
          },
          "previousState": {
            "code": 16,
            "name": "running"
          }
        }
      ]
    }
  },
  "requestID": "758b",
  "eventID": "68228982",
  "readOnly": false,
  "eventType": "AwsApiCall",
  "managementEvent": true,
  "recipientAccountId": "01234567",
  "eventCategory": "Management",
  "sessionCredentialFromConsole": "true"
},
{
  "eventVersion": "1.07",
  "userIdentity": {
    "type": "AssumedRole",
    "principalId": "AROA",
    "arn": "XYZ",
    "accountId": "01234567",
    "accessKeyId": "ABCDEFGH",
    "sessionContext": {
      "sessionIssuer": {
        "type": "Role",
        "principalId": "EWUDHAKFJ",
        "arn": "SJDSJDJSND",
        "accountId": "01234567",
        "userName": "ADKJDJAFDJFHDK"
      },
      "webIdFederationData": {},
      "attributes": {
        "creationDate": "2022-04-22T23:16:28Z",
        "mfaAuthenticated": "TRUE"
      }
    }
  },
  "eventTime": "2022-04-22T23:34:43Z",
  "eventSource": "compute-optimizer.amazonaws.com",
  "eventName": "GetEC2InstanceRecommendations",
  "awsRegion": "eu-west-1",
  "sourceIPAddress": "AWS Internal",
  "userAgent": "AWS Internal",
  "requestParameters": {
    "instanceArns": [
      "aSKSKASKASAA"
    ],
    "maxResults": 0,
    "accountIds": [
      "273273273728"
    ]
  },
  "responseElements": null,
  "requestID": "cb106ba",
  "eventID": "d8f6",
  "readOnly": true,
  "eventType": "SJSDKDSK",
  "managementEvent": true,
  "recipientAccountId": "283283829382983",
  "eventCategory": "Management",
  "sessionCredentialFromConsole": "true"
},
........

我不能使用 Pandas 和其他库。

Answer 1

我用来分隔事件的代码 -

key = 'event_history_j.json'
bucket = 'demo-cloudtrail-logs-ec2'
client = boto3.client('s3')
data = client.get_object(Bucket = bucket , Key = key)['Body'].read()
a = json.loads(data)

data2 = a["Records"]

# step2: prepare data of stop and start instances
data3 = []
for i in range(len(data2)):
    if data2[i]['eventName'] == "StopInstances":
        data3.append(data2[i])
    elif data2[i]['eventName'] == "StartInstances":
        data3.append(data2[i])
    else:
        pass

它可以优化，但它的工作解决方案..!!