amlana21

• Introduce a caching layer.
  • Do a query to call a Lambda. That lambda calls another lambda in async mode and the 1st lambda responds a req id to caller
  • The 2nd lambda queries ddb and waits for result. On result received from ddb write results to a cache like Elasticache
  • From frontend keep querying cache with request id. WHen result gets available, read the results. This will be much faster than ddb
• Use websocket
  • Implement a websocket service
  • Open a websocket connection from frontend
  • repeat above steps with 2 lambda (from caching option)
  • but instead of cache, 2nd lambda returns results to websocket and frontend gets result from socket connection
• Use DAX to improve performance. This will improve DDB performance if you have large number of records

amlana21

import yaml, subprocess, json, re, sys

FILE_NAME = 'auth_config.yaml'
KUBERNETES_GROUP = 'system:masters'

cmd = f'kubectl get configmap aws-auth -n kube-system -o yaml > {FILE_NAME}'

MASTER_PARSER = '({["rolearn":"arn]+[:a-z0-9\/\w-]+"[,"\w\/-:{{{]*[-\w}}",:\[]*[\]]*})' #regex101