•3-Enriching the
integration as a
service paradigm for
the cloud era
Introduction To Cloud Integration
• Cloud Integration is about simplifying
technology so that it could be adopted by a
much broader audience.
• Cloud integration is the process of configuring
multiple application programs to share data
in the cloud.
• In a network that incorporates cloud
integration; diverse applications
communicate either directly or through
third-party software.
Conti…
• Cloud integration is the linking of information
flows between cloud-hosted applications and
other applications hosted in different clouds
or in the datacenter.
• Without integration, cloud applications can’t
share data with the rest of the company and
that limits or even eliminates the utility of the
cloud.
Advantages of Cloud Integration
• Each user can access personal data in real
time from any device and from any location
with Internet access.
• Each user can integrate personal data such as
calendars and contact lists served by diverse
application programs.
Conti…
• Each user can employ the
same logon information (username and
password) for all personal applications.
• The system efficiently passes control
messages among application programs.
• By avoiding the use of data silos(separate
database), data integrity is maintained.
• Cloud integration offers scalability to allow
for
– Future expansion in terms of the number of
users,
– the number of applications,
– or both.
• Integration as a service (IaaS)
• B2B systems are capable of driving this new
on-demand integration model because they
are traditionally employed to automate
business processes between manufacturers
and their trading partners.
• That means they provide
application-to-application connectivity along
with the functionality that is very crucial for
linking internal and external software
securely.
Evolution of SaaS
• The use of hub & spoke (H&S) architecture
further simplifies the implementation and
avoids placing an excessive processing burden
on the customer sides.
• The hub is installed at the SaaS provider’s
cloud center to do the heavy lifting such as
reformatting files.
• A spoke unit at each user site typically acts as
basic data transfer utility.
THE CHALLENGES OF SaaS PARADIGM
The Challenges Of SaaS Paradigm
• 1. Controllability
• 2. Visibility & flexibility
• 3. Security and Privacy
• 4. High Performance and Availability
• 5. Integration and Composition
• 6. Standards
Integration Challenges
• The first issue is that the majority of SaaS
applications are point solutions and service one line
of business.
• As a result, companies without a method of
synchronizing data between multiple lines of
businesses are at a serious disadvantage in terms of
– maintaining accurate data,
– forecasting, and
– automating key business processes.
Application Programming Interfaces (API) are
Insufficient
• Many SaaS providers have responded to the
integration challenge by developing APIs.
• Unfortunately, accessing and managing data
via an API requires a significant amount of
coding as well as maintenance due to
frequent API modifications and updates.
• No standardization or consensus(agrement)
on the structure or format of SaaS APIs.
Data Transmission Security.
• Transfer data from on-premise systems or
applications behind the firewall with SaaS
applications should be secure.
The Impacts of Clouds
• Integration is being stretched further to the
level of the expanding Internet.
• Interoperability between SaaS and non-SaaS
solutions remains the lead demand.
NEW INTEGRATION SCENARIOS
• Three major integration Scenarios are identified
• Within a Public Cloud
• Two different applications are hosted in a cloud.
• The role of the cloud integration middleware (say cloud-based
ESB or internet service bus (ISB)) is to seamlessly enable
these applications to talk to each other.
Homogeneous Clouds
• The applications to be integrated are posited in two
geographically separated cloud infrastructures.
• The integration middleware can be in cloud 1 or 2 or in a
separate cloud.
• There is a need for data and protocol transformation and
they get done by the ISB.
Heterogeneous Clouds
• One application is in public cloud and the
other application is private cloud.
• This is the currently dominating scene for
cloud integration
Integration Methodologies
Traditional enterprise integration tools deployed on premise
with special connectors to access cloud based applications.
• This is a most likely approach for IT organizations who have
already standardized on an integration tool for integrating
their enterprise applications, and now looking to extend that
capability to include cloud applications.
• Many integration vendors are also providing subscription
based licensing options to help customers license their
technologies for term-based projects.
• Examples include data integration technologies like
Informatica’s Power Center product, message based EAI/ESB
technologies, and appliance based integration tools.
Traditional enterprise integration tools hosted in the cloud.
• This approach is similar to the first option, except that the
equipment for installing the integration software is hosted
by a third party provider so that the customer does not have
to worry about procuring and managing the hardware, or
installing the integration software.
• An example of a hosted integration technology is
Informatica’sPowerCenter, Cloud Edition on Amazon EC2.
Integration-as-a-Service or On Demand Integration offerings :
• These are SaaS applications that are designed to deliver
integration securely over the internet, and are able to
integrate cloud applications to on-premise systems,
cloud-to-cloud applications, or on-premise to on-premise
applications without requiring the users to setup a VPN
connection or provide any special access through their
firewall.
• This approach is a good fit for companies who care the most
about ease of use, ease of maintenance, time to
deployment, and are on a tight budget.
• It is appealing to small and mid-sized companies, as well as
large enterprises with a departmental application
deployment.
• good example is Informatica’s On Demand Integration
Services.
Integration Methodologies
• No single approach is a perfect fit for all scenarios, and the
right approach for any company will depend on some of the
following factors:
• Who will build and maintain integration jobs – In-house?
• The scope and complexity of the project – Is it a pilot project,
a small departmental project or a strategic enterprise
deployment?
• The size of the company – what is their budget for an
integration tool and do they prefer a buy vs lease approach?
SaaS INTEGRATION SERVICES
• Informatica On-Demand
• Informatica Cloud is available in multiple editions to meet
the needs of organizations of all sizes.
• Easy to use Cloud Integration and Data Quality Applications
built on the market-leading Platform.
• http://www.informaticaondemand.com
• Features
• Comprehensive, Unified, Open, and Economical
• Easy-to-Use Cloud Data Management and Integration
Applications
– Informatica Cloud introduced the industry's first
usage-based data integration service,
• Cloud Master Data Management
– Cloud MDM is fully integrated and deployed in the cloud,
with no need to install additional hardware or software.
• Validate and Cleanse Your Contacts
• Secure Sensitive Data During Development and Test
• Create Step-by-Step Guides and Automate Processes
• Build Your Own Cloud Integration Applications
Characteristics Of Integration Solutions And Products
• Connectivity
Refers to the ability of the integration engine to engage with
both the source and target
• Semantic Mediation
Refers to the ability to account for the differences between
application semantics between two or more systems.
• Semantics means how information gets understood,
interpreted and represented within information systems
• Data Mediation converts data from a source data format
into destination data format
Data Migration
Means that the data in the old system is mapped to the new
systems,
Data Security
Means the ability to insure that information extracted from the
source systems has to securely be placed into target systems.
Data Integrity
Means data is complete and consistent.
Data Integration Engineering Life Cycle
The pivotal phases of Data Integration Engineering Life Cycle are
• Understanding- the existing problem domain means defining
the metadata that is native within the source system
• Definition refers to the process of taking the information
called during the previous step and defining it at a high level
including what the information represents, ownership, and
physical attributes.
• Design the integration solution around the movement of
data from one point to another accounting for the
differences in the semantics.
Data Integration Engineering Life Cycle
• Implementation refers to actually implementing the data
integration solution within the selected technology.
• Testing refers to assuring that the integration is properly
designed and implemented and that the data synchronizes
properly between the involved systems.
