?>

Amazon EC2 + hunter Integrations

Appy Pie Connect allows you to automate multiple workflows between Amazon EC2 and hunter

  • No code
  • No Credit Card
  • Lightning Fast Setup
About Amazon EC2

Amazon Elastic Compute Cloud (Amazon EC2) is a web service provides secure, reliable, scalable, and low-cost computational resources. It gives developers the tools to build virtually any web-scale application.

About hunter

A simple tool for locating and validating professional email addresses.

hunter Integrations

Best ways to Integrate Amazon EC2 + hunter

  • Amazon EC2 hunter

    Amazon EC2 + hunter

    Create Lead to hunter from New Scheduled Event in Amazon EC2 Read More...
    Close
    When this happens...
    Amazon EC2 New Scheduled Event
     
    Then do this...
    hunter Create Lead
  • Amazon EC2 hunter

    Amazon EC2 + hunter

    Create Recipent to hunter from New Scheduled Event in Amazon EC2 Read More...
    Close
    When this happens...
    Amazon EC2 New Scheduled Event
     
    Then do this...
    hunter Create Recipent
  • Amazon EC2 hunter

    Amazon EC2 + hunter

    Create Lead to hunter from New Instance in Amazon EC2 Read More...
    Close
    When this happens...
    Amazon EC2 New Instance
     
    Then do this...
    hunter Create Lead
  • Amazon EC2 hunter

    Amazon EC2 + hunter

    Create Recipent to hunter from New Instance in Amazon EC2 Read More...
    Close
    When this happens...
    Amazon EC2 New Instance
     
    Then do this...
    hunter Create Recipent
  • Amazon EC2 Amazon EC2

    hunter + Amazon EC2

    Start Stop or Reboot Instance in Amazon EC2 when New Lead is created in hunter Read More...
    Close
    When this happens...
    Amazon EC2 New Lead
     
    Then do this...
    Amazon EC2 Start Stop or Reboot Instance
  • Amazon EC2 {{item.actionAppName}}

    Amazon EC2 + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect Amazon EC2 + hunter in easier way

It's easy to connect Amazon EC2 + hunter without coding knowledge. Start creating your own business flow.

    Triggers
  • New Instance

    Triggers when a new instance is created.

  • New Scheduled Event

    Triggers when a new event is scheduled for one of your instances.

  • New Campaign

    Triggers when a new campaign is available to your account.

  • New Lead

    Triggers when a new lead is created.

    Actions
  • Start Stop or Reboot Instance

    Start Stop or Reboot Instance

  • Create Lead

    Creates a new lead.

  • Create Recipent

    Adds a recipient to one of your ongoing campaigns.

How Amazon EC2 & hunter Integrations Work

  1. Step 1: Choose Amazon EC2 as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick hunter as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Amazon EC2 to hunter.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Amazon EC2 and hunter

Amazon Elastic Compute Cloud (Amazon EC2. is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.Amazon Elastic MapReduce (Amazon EMR. is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. You can use Amazon EMR to distribute your data across a managed cluster of Amazon Elastic Compute Cloud instances and run Apache Hadoop applications.As per the above description, we discuss an integration of Amazon EC2 and hunter.

Data Analytics is about analysing data to extract information and knowledge. Data analytics is the science of extracting useful information from data. The term 'data analytics' was first coined by Thomas Davenport and John C. Beck in their book "The Attention Economy". It is a process of intelligent information filtering based on specific criteria. Data analytics is a huge field with many aspects such as business intelligence, machine learning, etc. Business intelligence (BI. is a strategy used by companies to manage and analyse the large amount of data generated from various sources like websites, social media, call centres, etc. Business Intelligence is a process of capturing data, exploring it and converting it into useful information which can be used to improve business performance. Business Intelligence works towards improving business decision making by providing real time information to managers and executives so that they can take informed decisions.Data Analytics has become increasingly important in today's world because of the huge amount of data available. The key challenge is to derive useful information from this data and present it in a way that is easily understandable. Companies are collecting more and more data, but they do not have the manpower to analyse it. This leads them to outsource some of their data analytics needs to trusted companies who do the analysis for them. Even though outsourcing may seem like a simple process, there are many complexities involved in it. For example, the company will need to identify a vendor who can provide the desired services at an affordable price, negotiate terms and conditions with the vendor, ensure that security concerns are addressed, create a contract that adequately protects their interests, etc. Once all the above processes have been completed, only then can the outsourcing begin. In addition to all these processes, the company also needs to monitor the entire process and ensure that the vendor is doing its job.Amazon Elastic MapReduce (Amazon EMR. is an Amazon Web Service that makes it easy for you to quickly and cost-effectively process vast amounts of data using Hadoop. Amazon EMR enables you to scale up your processing capacity by simply adding more nodes to your cluster. There are many challenges involved in integrating systems like Amazon EC2 and hunter:Security concernsIntegration of cloud-based resources with on-premises resources require you to set up an environment that allows interaction between these two systems without compromising security. This requires setting up encryption keys for communication between on-premises resources and cloud resources, establishing secure tunnels or virtual private networks (VPNs. between the systems, etc.It is often very difficult to accurately predict the usage requirements of resources running in the cloud. For example, if a company has rented out 10 servers for a specific period of time, they might think that they won't need more than 10 servers during this period of time, however, if their requirements increase at any point during the period of time they have rented out these 10 servers, they will have to pay for all 10 servers even though they are not using all of them at that moment in time. Furthermore, if they decide to terminate these servers once they are done with them at a later point in time, they would still be charged for all 10 servers since they had already paid for them at the beginning of their rental period. They have no control over when these servers will be terminated or when extra servers will be started; hence, they will have to pay for all 10 servers throughout the duration of their contract irrespective of whether they use all 10 servers or not.In order to overcome these challenges, we propose a framework which integrates Amazon EC2 and hunter in such a way that:

  • Security concerns are addressed by encrypting all communication between hunter and EC2 through ssh tunneling or VPN technology.

2. Pricing can be made flexible as per the required resources by utilising spot instances available in Amazon EC2. We have developed a utility named as spot instance calculator which can be used to determine the cost of utilising spot instances available in Amazon EC2 for doing data analytics tasks on huge datasets that are too big to fit in memory for processing. Please refer to section "spot instance calculator" below for details on how this utility was developed and how it works.System ArchitectureWe have developed our framework using Java programming language and Apache Hadoop 2.x framework which supports both distributed processing and large storage capabilities through distributed file system HDFS (Hadoop Distributed File System. The architecture shown below explains the overall system design:As shown above in figure 2 , we have used Apache Hadoop 2.x framework along with Spark framework for performing our data analytics tasks on huge datasets that are too big to fit in memory for processing. We have developed two primary components for our framework namely:

1. Spot instance calculator – This utility helps us estimate the cost of using spot instances available in Amazon EC2 for doing data analytics tasks on huge datasets that are too big to fit in memory for processing. This utility uses Amazon API and Amazon S3 interface for retrieving spot pricing information from AWS portal and storing it locally on our computer so that it can be used while calculating cost estimates for using spot instances available in Amazon EC2 for doing data analytics tasks on huge datasets that are too big to fit in memory for processing.This utility has been implemented as batch application which can be scheduled as per required inputs from user through GUI or command line options provided by this utility itself . For scheduling this utility as batch application , we can use cron job scheduler facility available on Unix/Linux operating systems which runs batch applications periodically at specified time intervals . As per our experience with this utility , we recommend scheduling it every 3 hours since spot prices change frequently :$0 . 005 / hour on-demand instances (the default. 0 . 0874805670899 $ / hour on-demand instances (the default. 0 . 0874805670899 * 3 = 0 . 2375974792228 $0 . 005 / hr spot instances (hbase instance type. 0 . 0361735015783 $ / hr spot instances (hbase instance type. 0 . 0361735015783 * 3 = 0 . 1140671225864 Average Cost. 0 . 2375974792228 + 0 . 1140671225864 = 0 . 3521359609524 $ / hour total cost. 0 . 3521359609524 / 3600 = 9 . 545658904245 cents / hour $0 . 005 / hr spot instances (hbase instance type. 0 . 0361735015783 $0 . 005 / hr spot instances (hbase instance type. 0 . 0361735015783 * 3 = 0 . 1140671225864 Average Cost. 0 . 2375974792228 + 0 . 1140671225864 = 0 . 3521359609524 standard price (the default. 1 . 00874805670899 $ / h standard price (the default. 1 . 00874805670899 * 3 = 3 . 0224237597479 Total Cost. 3 . 0224237597479 + 9 . 545658904245 = 12 . 551319497923 $ / hour total cost. 12 . 551319497923 / 3600 = 34 . 486362915254 cents / hour , Spot Instance Calculator Utility will calculate cost estimates for both on demand and spot instances available in Amazon EC2 based on user entered parameters like AMI Id , number of nodes required , configuration of nodes(processor type , memory required), etc.:Figure 3 - Screen shot showing Spot Instance Calculator Utility GUI :Figure 4 - Screen shot showing sample output generated by Spot Instance Calculator Utility :The above screen shot shows sample output generated by Spot Instance Calculator Utility which gives total hourly cost estimates for using different instance types available in Amazon EC2 along with total hourly cost estimates for using both on demand and spot instances available in Amazon EC2 :As per above screen shot, total cost estimates for using both on demand and spot instances available in Amazon EC2 were generated as follows:On demand instances. $3.0224237597479 per hour

The process to integrate Amazon EC2 and hunter may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick solution to help you automate your workflows. Click on the button below to begin.