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AWS Infrastructure setup and configuration for big data analysis

This project received 3 bids from talented freelancers with an average bid price of $18 AUD / hour.

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Employer working
Project Budget
$15 - $25 AUD / hour
Total Bids
3
Project Description

Hello, I require someone who is able to setup and build an platform infrastructure in AWS that will be used to do (near) realtime analytics on several different feeds and datasets (twitter, fb, etc.)
At this stage, due to time constraints, I would like to delegate the initial setup so i can design and build/manage the application logic

This platform will use the following frameworks/components:
1. elastic mapreduce
2. elasticsearch
3. flume
4. logstash
5. kibana
6. mapbox
7. additional application servers will ideally be built using [url removed, login to view]
8. git repositories for scripts, etc.
9. S3
10. additional aws services (IAM, Data Pipeline, DynamoDB) where appropriate (easier to manage configure)
11. whatever else is needed (open to discussion)

I would like to utilise OpsWorks and elastic beanstalk where possible rather than ec2 instances, and optionally (depending on complexity/cost) chef recipes if possible in preference over written documentation (there are plenty of open source examples that can be modified etc.).

There is a wealth of documentation and articles regarding how to set all these components so this initial job is predominantly a "follow the instructions and modify accordingly", and should be similar to architecture presented by :
[url removed, login to view]

The outcome of this phase of work should be a "nice, clean" infrastructure that is "ready to go" for customisations etc, and as stated, this shouldn't have any hidden complexities.

the infrastructure should be setup using micro-tier environments during development but will need to be scaled for production (this should be tagged as a 'dev' environment

I am an experienced solution and software architect, and would like to work with someone to collaborate and work with (ie your opinions and experience matter), and engage on an ongoing basis to help complete the application/project, so if you have an interest in "big data", machine learning, and visualisation, then this first phase is just the beginning.

Looking to make some money?

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