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This section takes a look at how to manage snapshots of EC2 through boto3. In the actual production environment, beans use the solution EBS Snapshot Scheduler provided by AWS, which is directly imported into the stack of Cloudformation. The Lambda function and DynamoDB database are automatically configured, and then we can set them through tags. From a learning point of view, let's go straight to an ultra-simple version. We can write two Lambda functions directly, one to create and the other to delete.

First, set a tag tag

Next, create the Lambda function

The configuration of IAM Role is as follows

{"Version": "2012-10-17", "Statement": [{"Effect": "Allow", "Action": ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"], "Resource": "arn:aws:logs:*"}, {"Effect": "Allow" "Action": ["ec2:CreateSnapshot", "ec2:CreateTags", "ec2:DeleteSnapshot", "ec2:Describe*", "ec2:ModifySnapshotAttribute", "ec2:ResetSnapshotAttribute"], "Resource": "*"}

The specific functions are as follows:

From datetimeimport datetimeimport boto3def lambda_handler (event, context): ec2_client = boto3.client ('ec2') # get the names of all region regions = [region [' RegionName'] for region in ec2_client.describe_regions () ['Regions']] # loop every region Find all instances labeled backup for region in regions: print ('Instances in EC2 Region {0}:' .format (region)) ec2 = boto3.resource ('ec2', region_name=region) instances = ec2.instances.filter (Filters= [{' Name': 'tag:backup') 'Values': [' true']}]) # get the timestamp # ISO 8601 timestamp, i.e. 2019-01-31T14:01:58 timestamp = datetime.utcnow (). Replace (microsecond=0). Isoformat () # for each volume of each instance All create a snapshot for i in instances.all (): for v in i.volumes.all (): desc = 'Backup of {0}, volume {1}, created {2}' .format (i.id, v.id) Timestamp) print (desc) snapshot = v.create_snapshot (Description=desc) print ("Created snapshot:", snapshot.id)

Then set a scheduled task in Cloudwatch and execute this function on a regular basis

This is a schematic diagram of binding Role and trigger.

After execution, you can view the snapshot

Looking at the output log of print in Cloudwatch, you can see that it has been successfully executed.

In the same way, we can create a Lambda function to delete the snapshot

The specific functions are as follows:

Import boto3def lambda_handler (event, context): # sts returns a dictionary and obtains the ownerId of the current account through get If failed, None account_id = boto3.client ('sts') .get_caller_identity () .get (' Account') ec2 = boto3.client ('ec2') ": type: pyboto3.ec2" regions = [region [' RegionName'] for region in ec2.describe_regions () ['Regions']] for region in regions: print ("Region:", region) ec2 = boto3.client (' ec2') Region_name=region) "": type: pyboto3.ec2 "" response = ec2.describe_snapshots (OwnerIds= [account _ id]) snapshots = response ["Snapshots"] print (snapshots) # Snapshot is a long list Each element is a dictionary structure Sort specifies sorting by time # the following is equivalent to # def sortTime (x): # return x ["StartTime"] # snapshots.sort (key=sortTime) # Sort snapshots by date ascending snapshots.sort (key=lambda x: X ["StartTime"]) # Remove snapshots we want to keep (i.e.3 most recent) snapshots = snapshots [:-3] for Snapshot in snapshots: id = snapshot ['SnapshotId'] try: print ("Deleting snapshot:" Id) ec2.delete_snapshot (SnapshotId=id) except Exception as e: print ("Snapshot {} in use, skipping." .format (id)) continue

You can also create scheduled task execution functions

Print log in CloudWatch after execution

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