Friday, 18 July 2014

Azure Machine Learning–K Means Clustering…


 

 

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Machine Learning (ML) has been around almost over 5 decades now. In the last couple of years with the cloud computing and big data been the dominant colours in the IT Industry, ML has found a unique space in the Big Data problem.

A Brief on Azure ML

Azure ML is Machine Learning is simpler Microsoft offering from quick and easy ML advent. Its definitely a good starting point to get to use to the Machine Learning. As one may start using this more often will realize the Azure ML is limiting in terms of choices of Algorithms , data manipulation operations & ability to run as part to run with bigger scheme of things.

Most folks will start with Azure ML and figure out that there are multiple places where the constructs are limiting, so as a good citizen MSFT went and added the ExecuteR where one could program on R Studio for test and development, eventually for larger dataset, code port or intelligent copy to ExecuteR. A good video on how to use ExecuteR in Azure ML can be found here http://channel9.msdn.com/Blogs/Windows-Azure/R-in-Azure-ML-Studio

K-Means Clustering in Azure ML Video-

The data analysis starts of with initial task of having to classify data.  There are various algorithm which one may employ to classify data. The single most simplest and widely used algorithm is the K-Means Clustering. This session talks about K-Means Clustering and how to do the same using Azure ML.

The session take away from Azure ML is great not without R.

 

Files

Presentation Shared Here-https://drive.google.com/file/d/0B5lmX16jC3ZEcEprM2F0aW9FOVU/edit?usp=sharing

DataSets & Demo Here

RScripts - https://drive.google.com/file/d/0B5lmX16jC3ZES1c5MEdiamFCN0E/edit?usp=sharing

DataSets- https://drive.google.com/file/d/0B5lmX16jC3ZEY2R0T3R3WDU3NzQ/edit?usp=sharing

 

 

Tuesday, 13 May 2014

Azure API Management



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The Apiphany buy out of Microsoft sometime around Mid Oct 2013 is made it into the Azure Stack as API Management in a very short while.
Here is complete  You Tube - video on Azure API Management.

API is no more an after thought for most architectures, its right there in front staring right into architects face. API Facade can make or break any architectures from improving integration, developer productivity to high business returns. There are many platforms in the market for API’s. 
Azure API Management is direct port of APIPhany into Azure. In this post we will explore the Azure API Management and towards the end a comparison with the leading API platforms.
The Azure API has managed to pull through a lot of features into Azure in very short period of time
API Management Administrators Portal
The starting point for any API Management platform is a good enough Administrator Portal.  The Administrator Portal is essentially the place where one can manage the API.  Below is the snapshot of the same.
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The Administrator Portal for API Management covers the following  at a high level.
  • Dashboard – Quick Snapshot view of the all the API’s and there health graphs, products, applications
  • API –  Managing API’s there associated operations, settings etc..
  • Products- This essentially is a container of API’s and the access management around the same.
  • Policies – This is a key feature for API’s.  The consumer’s of API are initially developers and in production its going to be the applications. There many generic constructs which are required by the API for example
    • Quota Management: Number of times a consumer can call the API’s
    • Format Changes: One may need to change parameter/output value before invoking/return value from the actual API or probably change the format ex json,xml
    • Allow cross domain calls
    • CORS
    • Data Changes – Replace certain values inbound/outbound.
    • Restrict caller IP’s
    • Store to Cache
There are additional constructs which can be applied. 
Note: Most good API platforms have ability to add workflow constructs to inbound and outbound flow of the API’s. For every call made to the api , one would want to call other services based on the data. As of current there are no workflow constructs in Azure API , one can expect the same.
  •  Analytics:  The core objective for any API platform is the health management of the API, Analytics includes the health management information, graphs etc..
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  • Developers: Considering a decent population of the API consumers are going to be developers, the management around the same is important. This is fairly basic as of current.
  • Security: Support for 3rd party identity for developer sign –up.
  • Developer Portal: This is content management piece of the API portal which includes the API’s, documentation around the same, the products and issue reporting.
In a nut shell the Azure API Management is much awaited piece in the Azure stack and off to a flying start.

Thursday, 17 April 2014

Azure RMS (Rights Management Service)


 

With growing need data protection and compliance, Data security is always a key concern for any organization. Documents carry sensitive data. The data availability on multiple devices is critical to the business, and equally important is securing this data. Data at rest and transit both need to secure.

Almost a decade ago MSFT released it Rights Management Service for Windows 2003, later came AD RMS with 2008, 2012. In the past 1 year we have seen Azure take up the brigade of RMS , assuming there is Azure Active Directory.

With buzz around HIPAA compliance and Azure, still no clear directive on whether Azure is fully compliant

What most customers want is to implement a robust security solution to protect the organization’s data available in file servers, desktops via rights protecting the data, and make this data available via secure access. The data security and data-access control will help in enabling sharing of sensitive data in a secure and HIPAA compliant manner, and ensure confidentiality, integrity and authorized access to its data.

Microsoft Azure cloud service based Rights Management (RMS is the answer. This solution concept uses Azure Rights Management Service (RMS) as the basic building block for securing data and documents / files. The devices used for data access may or may not be connected to the organization network. (Devices are assumed to be organization locked and HIPAA compliant).

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Azure RMS will serve as a basic building block for encryption / decryption of documents / files with-in the client’s organization. Windows Server 2012 File Classification Infrastructure (FCI) will assist in automating the process of applying rights to documents. Most of the files to be accessed within the organization will be stored on the Windows File Server which has File Classification Infrastructure Service installed.

Azure RMS protection comes with 3 basic type content protection

  • Native RMS Microsoft formats– Office files
  • Non MSFT formats- Native PDF, Image files (bmp, jpeg…) txt. These will work only with P-Viewer tool for consumption and FoxIT for PDF.  One can write additional plugins if required.
  • Container level protections-  P-file container which imposed encryption/ decryption at a container level. The important point to note is once the files is out the container its unencrypted and has no rights management and is not secured. Container can have any files types.

Windows Server File classification Infrastructure (FCI) feature will identify sensitive files and encrypt them with RMS. FCI crawls file shares for files meeting certain criteria and tag them based on the results. Tags will be stored in the file attributes and persist even after moving files to another NTFS storage. Once files are tagged, they will be automatically applicable for "RMS Encryption" based on certain tags with RMS templates.

The RMS templates will be defined are organization-wide. With FCI one can perform different actions on files you identify as sensitive. One of them is to use the in-box RMS protection capability and there can be custom tasks for supporting other types of files trough two options:

· Putting files in encrypted container using Rights Protected Folder Explorer (RPFe)

· Triggering specific RMS protectors for certain types of files, such as PDF, CAD or images, supported with partner solutions

RPEe as a better option for protecting other file types. File Classification Infrastructure (FCI) provides insight into the data by automating classification processes. Rights Protected Folder Explorer (RPFe) is a Windows based application that allows you to protect files and folders.

A Rights Protected Folder is similar to a file folder in that it contains files and folders. However, a Rights Protected Folder controls access to the files that it contains, no matter where the Rights Protected Folder is located. By using Rights Protected Folder Explorer, one can securely store or send files to authorized users and control which users will be able to access those files while they are in the Rights Protected Folder.

Have implemented Azure RMS for more than 2 customers. So far so good.

Thursday, 3 April 2014

Global Azure boot camp Mumbai 29th March 2014


 

GWAB

Speaking at Global Azure Boot Camp 29/3 @ Mumbai has been quite a delight. Giving back to community plays a vital role in fuelling growth.

Covered topics around Cloud Computing  The Next Paradigm , Big Data & Large-scale Implementation on Azure. Find the presentation on the links below.

Cloud computing, Windows Azure has gained a general acceptance among the Microsoft and non-Microsoft participants. The drive around Open Source is seemingly building up around Azure.  The delighter to the sessions were the eagerness to know more about Big Data or HDInsight. Hadoop continues to be a bit of crystal ball gazing for most participant, a promising one. The twinkle in eyes of most to know more around the stack can/will be done in the coming session.

Most business user and software folks get asked the questions around the biggest implementation on Azure Platform. This is more of indicator to endorse there thought process.

Would like to make a special mention of Ajay Khankojhe from Synergetics the event was conducted wonderfully.

Presentations

1. Large-scale Implementation on Windows Azure

2. Cloud Computing – The Next Paradigm

3. Big Data Basics