Audit Your AWS EC2 instances

#!/usr/bin/python
# ovi

import boto3 # import boto3 library
import datetime
#from termcolor import colored

#print “———————”
print “Audit report date:”

today = datetime.date.today()

print today

#print ‘Audit report’

ec2 = boto3.resource(‘ec2′, region_name=’ca-central-1’) # call ec2 resource to perform further actions
instances = ec2.instances.all()  # get all instances from above region

for instance in instances:
print(“Instance id – “, instance.id)
print(“Instance public IP – “, instance.public_ip_address)
print(“Instance private IP “, instance.private_ip_address)
print(“Instance launch time “, instance.launch_time)
print(“Instance root device name “, instance.root_device_name)
print(“Instances tags” ,instance.tags)
print(“—————————————————“)

Redis

Redis is an open source, in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs and geospatial indexes with radius queries. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster

 

reference

https://redis.io/

 

Apache – Hue

Hue is a browser-based environment that enables you to interact with a Hadoop cluster. Hue includes several easy to use applications that help you work with Hadoop MapReduce jobs, Hive queries, Hadoop files and user accounts. The Hue applications run in a Web browser and require no client installation.

Hue is a Web UI for Hadoop.

Hue supports the following features:

  • Beeswax to execute Hive queries
  • FileBrowser to access HDFS
  • HCatalog application for Hive metadata and table management
  • Pig application to execute Pig queries
  • Job Designer to create MapReduce/Streaming/Java jobs
  • Oozie application to submit and schedule workflows
  • JobBrowser for view MapReduce jobs

Web access console

http://localhost:8000/

ovi

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