The document discusses several cloud computing platforms including Google App Engine, Amazon Web Services, Microsoft Azure, Hadoop, and Aneka. It provides descriptions of each platform, what types of applications they support, their capabilities and limitations. Key points covered include: - Google App Engine allows developers to build applications using Python and scales automatically. Amazon Web Services provides infrastructure services like storage, computing and databases. - Hadoop is an open-source framework for distributed storage and processing of large datasets across clusters of commodity hardware. It faces challenges around complexity, tuning, and platform choices. - Microsoft Azure provides a cloud platform for running Windows applications and storing data, allowing applications to scale out across many servers.

1. Jawaharlal Institute of Technology (Borawan)
Introduction on Cloud Computing
Cloud computing provides Internet-based services, computing, and storage for users in all
markets including financial, healthcare, and government. This new approach to computing
allows users to avoid upfront hardware and software investments, gain flexibility, collaborate
with others, and take advantage of the sophisticated services that cloud providers offer. However,
security is a huge concern for cloud users.
Cloud providers have recognized the cloud security concern and are working hard to address it.
In fact, cloud security is becoming a key differentiator and competitive edge between cloud
providers. By applying the strongest security techniques and practices, cloud security may soon
be raised far above the level that IT departments achieve using their own hardware and software.
NIST Definition of Cloud Computing
For the record, here is the definition of cloud computing offered by the National Institute of
Standards and Technology (NIST):
Cloud computing is a model for enabling convenient, on-demand network access to a shared
pool of configurable computing resources (e.g., networks, servers, storage, applications, and
services) that can be rapidly provisioned and released with minimal management effort or
service provider interaction.
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2. Jawaharlal Institute of Technology (Borawan)
Google App Engine
On April 2008, Google released the beta version of the Google App Engine which allows the
developers to develop the applications based on Python. The developers can also use Google’s
infrastructures to manage their developing process (maximum 500MB storage space).
Google App Engine is an application hosting and development platform that Powers everything
from enterprise web applications to mobile games, using the same infrastructure that powers
Google’s global-scale web applications. Developers know that time-to-market is critical to
success, and with Google App Engine’s simple development, robust APIs and worry-free
hosting, you can accelerate your application development and take advantage of simple
scalability as the application grows.
Google App Engine makes it easy to take your app ideas to the next level.
Quick to start with no software or hardware to buy and maintain you can prototype and deploy
applications to your users in a matter of hours.
Simple to use Google App Engine includes the tools you need to create test, launch, and update
your apps.
Rich set of APIs Build feature-rich services faster with Google App Engine’s easy-to-use APIs.
Immediate scalability there’s almost no limit to how high or how quickly your app can scale.
Pay for what you use get started without any upfront costs with App Engine’s free tier and pay
only for the resources you use as your application grows.
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3. Jawaharlal Institute of Technology (Borawan)
Amazon Web Service
Amazon’s ‘cloud’ was initialized in 2002 and named Amazon Web Service. It is a web based
remote computing collection. It is constructed based on four key services, Simple Storage
Service (S3), Elastic Compute Cloud (EC2), Simple Queuing Service and Simple DB. In other
words, Amazon now provide the storage service, computing service, queuing service and data
base access service through the Internet. Other Services include Amazon Associates Web
Services (A2S), Amazon AWS Authentication, Amazon Virtual Private Cloud (VPC).
Comparison of Google App Engine and Amazon Web Service
The comparison of Amazon Web Service and Google App Engine is shown in Figure 1. The
main difference between Amazon Web Service and Google App Engine is that Amazon Web
Service is IaaS while Google App Engine is PaaS. The next chapter will analyze the performance
of Google App Engine and Amazon Web Service in two different aspects respectively.
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4. Jawaharlal Institute of Technology (Borawan)
Hadoop
Hadoop is a powerful framework that allows for automatic parallelization of computing task.
Unfortunately programming for it poses certain challenges, namely it is really hard to understand
and debug Hadoop programs. One way to easy things a little bit is to have a simplified version of
the hadoop cluster that could run locally on the developer's machine. This tutorial describes how
to set-up such cluster on the computer running Microsoft Windows; also it describes how to
integrate this cluster with the Eclipse development environment. Eclipse is a prime environment
for Java development.
Hadoop challenges
With all large environments, deployment of the servers and software is an important
consideration. Dell provides best practices for the deployment of Hadoop solutions. These best
practices are implemented through a set of tools to automate the configuration of the hardware,
installation of the operating system (OS), and installation of the Hadoop software stack from
Cloudera.
As with many other types of information technology (IT) solutions, change management and
systems monitoring are a primary consideration within Hadoop. The IT operations team needs to
ensure tools are in place to properly track and implement changes, and notify staff when
unexpected events occur within the Hadoop environment.
Hadoop is a constantly growing, complex ecosystem of software and provides no guidance to the
best platform for it to run on. The Hadoop community leaves the platform decisions to end users,
most of whom do not have a background in hardware or the necessary lab environment to
benchmark all possible design solutions. Hadoop is a complex set of software with more than
200 tunable parameters. Each parameter affects others as tuning is completed for a Hadoop
environment and will change over time as job structure changes, data layout evolves, and data
volume grows.
As data centers have grown and the number of servers under management for a given
organization has expanded, users are more conscious of the impact new hardware will have on
existing data centers and equipment.
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5. Jawaharlal Institute of Technology (Borawan)
Hadoop uses
Compute –A common use of Hadoop is as a distributed compute platform for analyzing or
processing large amounts of data. The compute use is characterized by the need for large
numbers of CPUs and large amounts of memory to store in-process data. The Hadoop ecosystem
provides the application programming interfaces (APIs) necessary to distribute and track
workloads as they are run on large numbers of individual machines.
Storage –One primary component of the Hadoop ecosystem is HDFS—the Hadoop Distributed
File System. The HDFS allows users to have a single addressable namespace, spread across
many hundreds or thousands of servers, creating a single large file system. HDFS manages the
replication of the data on this file system to ensure hardware failures do not lead to data loss.
Many users will use this scalable file system as a place to store large amounts of data that is then
accessed within jobs run in Hadoop or by external systems.
Database –The Hadoop ecosystem contains components that allow the data within the HDFS to
be presented in a SQL-like interface. This allows standard tools to INSERT, SELECT, and
UPDATE data within the Hadoop environment, with minimal code changes to existing
applications. Users will commonly employ this method for presenting data in a SQL format for
easy integration with existing systems and streamlined access by users.
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6. Jawaharlal Institute of Technology (Borawan)
Microsoft Azure
Cloud computing is here. Running applications on machines in an Internet-accessible data center
can bring plenty of advantages. Yet wherever they run, applications are built on some kind of
platform. For on-premises applications, this platform usually includes an operating system, some
way to store data, and perhaps more. Applications running in the cloud need a similar
foundation.
The goal of Microsoft’s Windows Azure is to provide this. Part of the larger Azure Services
Platform, Windows Azure is a platform for running Windows applications and storing data in the
cloud.
Figure 1: Windows Azure applications run in Microsoft data centers and are accessed via the Internet.
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7. Jawaharlal Institute of Technology (Borawan)
As the figure shows, Windows Azure runs on machines in Microsoft data centers. Rather than
providing software that Microsoft customers can install and run themselves on their own
computers, Windows Azure is a service: Customers use it to run applications and store data on
Internet-accessible machines owned by Microsoft. Those applications might provide services to
businesses, to consumers, or both.
The Compute Service
The Windows Azure Compute service can run many different kinds of applications. A primary
goal of this platform, however, is to support applications that have a very large number of
simultaneous users. (In fact, Microsoft has said that it will build its own SaaS applications on
Windows Azure, which sets the bar high.) Reaching this goal by scaling up—running on bigger
and bigger machines—isn’t possible. Instead, Windows Azure is designed to support
applications that scale out, running multiple copies of the same code across many commodity
servers.
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8. Jawaharlal Institute of Technology (Borawan)
Aneka
Aneka is a market oriented Cloud development and management platform with rapid application
development and workload distribution capabilities. Aneka is an integrated middleware package
which allows you to seamlessly build and manage an interconnected network in addition to
accelerating development, deployment and management of distributed applications using
Microsoft .NET frameworks on these networks. It is market oriented since it allows you to build,
schedule, provision and monitor results using pricing, accounting, QoS/SLA services in private
and/or public (leased) network environments.
Aneka is a workload distribution and management platform that accelerates applications in
Microsoft .NET framework environments. Some of the key advantages of Aneka over other
GRID or Cluster based workload distribution solutions include: · rapid deployment tools and
framework, ability to harness multiple virtual and/or physical machines for accelerating
application result · provisioning based on QoS/SLA · support of multiple programming and
application environments · simultaneous support of multiple run-time environments · built ontop of Microsoft .NET framework, with support for Linux environments through Mono.
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