0
votes

I am aware of the HTTP Data Collector API that can be used to pull data into Azure Log analytics, my ask here is on AWS Cloudwatch data to Azure. We have Azure hosted application and an external AWS hosted Serverless Lamda functions and we want to import the logs of those 13 serverless functions into Azure. I know from the documentation and there is a python function that can be used as a AWS Lamda function and the python example is in MSFT documentation. But what I am failing to understand is what Json format that AWS cloud collector needs to create so they can send it to Azure Log Analytics. Any examples on this ? Any help on how this can be done. I have come across this blog also but that is splunk specific. https://www.splunk.com/blog/2017/02/03/how-to-easily-stream-aws-cloudwatch-logs-to-splunk.html

1

1 Answers

0
votes

Hey never mind I was able to dig a little deeper and I found that in AWS I can STREAM the Logs from one Lambda to other Lambda function thru subscription. Once that was setthen all I did was consumed that and on the fly created the JSON and sent it to Azure Logs. In case if you or anyone is interested in it, following is the code:-

import json
import datetime
import hashlib
import hmac
import base64
import boto3
import datetime
import gzip

from botocore.vendored import requests
from datetime import datetime

Update the customer ID to your Log Analytics workspace ID
customer_id = "XXXXXXXYYYYYYYYYYYYZZZZZZZZZZ"

For the shared key, use either the primary or the secondary Connected Sources client authentication key
shared_key = "XXXXXXXXXXXXXXXXXXXXXXXXXX"

The log type is the name of the event that is being submitted
log_type = 'AWSLambdafuncLogReal'

json_data = [{
"slot_ID": 12345,
"ID": "5cdad72f-c848-4df0-8aaa-ffe033e75d57",
"availability_Value": 100,
"performance_Value": 6.954,
"measurement_Name": "last_one_hour",
"duration": 3600,
"warning_Threshold": 0,
"critical_Threshold": 0,
"IsActive": "true"
},
{
"slot_ID": 67890,
"ID": "b6bee458-fb65-492e-996d-61c4d7fbb942",
"availability_Value": 100,
"performance_Value": 3.379,
"measurement_Name": "last_one_hour",
"duration": 3600,
"warning_Threshold": 0,
"critical_Threshold": 0,
"IsActive": "false"
}]
#body = json.dumps(json_data)
#####################
######Functions######
#####################

Build the API signature
def build_signature(customer_id, shared_key, date, content_length, method, content_type, resource):
x_headers = 'x-ms-date:' + date
string_to_hash = method + "\n" + str(content_length) + "\n" + content_type + "\n" + x_headers + "\n" + resource
bytes_to_hash = bytes(string_to_hash, encoding="utf-8")
decoded_key = base64.b64decode(shared_key)
encoded_hash = base64.b64encode(
hmac.new(decoded_key, bytes_to_hash, digestmod=hashlib.sha256).digest()).decode()
authorization = "SharedKey {}:{}".format(customer_id,encoded_hash)
return authorization

Build and send a request to the POST API
def post_data(customer_id, shared_key, body, log_type):
method = 'POST'
content_type = 'application/json'
resource = '/api/logs'
rfc1123date = datetime.utcnow().strftime('%a, %d %b %Y %H:%M:%S GMT')
print (rfc1123date)
content_length = len(body)
signature = build_signature(customer_id, shared_key, rfc1123date, content_length, method, content_type, resource)
uri = 'https://' + customer_id + '.ods.opinsights.azure.com' + resource + '?api-version=2016-04-01'

headers = {
    'content-type': content_type,
    'Authorization': signature,
    'Log-Type': log_type,
    'x-ms-date': rfc1123date
}
response = requests.post(uri,data=body, headers=headers)
if (response.status_code >= 200 and response.status_code <= 299):
    print("Accepted")
else:
    print("Response code: {}".format(response.status_code))
    print(response.text)
def lambda_handler(event, context):
cloudwatch_event = event["awslogs"]["data"]
decode_base64 = base64.b64decode(cloudwatch_event)
decompress_data = gzip.decompress(decode_base64)
log_data = json.loads(decompress_data)
print(log_data)
awslogdata = json.dumps(log_data)
post_data(customer_id, shared_key, awslogdata, log_type)