Virtualization, Do Not Turn Cost Saving Into Money Wasting

Virtualization has become the cornerstone of every enterprise's favorite money-saving initiative. By reducing the numbers and types of servers that support their business applications, companies are looking at significant cost savings. Less power consumption and a smaller server footprint is simpler to manage.

Beyond the potentially dramatic cost savings, virtualization can greatly enhance an organization's business agility. Also, this technology offers the potential for a fundamental change in the way IT managers think about computing resources.

Server virtualization brings a lot of benefits to the organization. However there are some challenges presented to the IT operations as well.

Cost Justification

When implement virtual solution for data center, we need to clearly understand the business requirements and carefully plan for the capacity and infrastructure growth. If not it will actually posts a very big challenge for IT operations. Very often we see resources being wasted due to many different reasons such as whether resources can be shared among different applications due to security consideration, ongoing project postponed due to the budget constraints or resource conflicts. Hardware for the virtual infrastructure has its life cycle, when resources cannot be fully utilized within its life cycle, resources will be wasted. A typical example will be virtual infrastructure implemented for the project, the idea is to consider easy future expansion so resources were planned for the next six months or a year, then often the case the project delayed and resources sits there. After three to five years hardware resources need to be refreshed and new investment has to put in place.

Resources Calculation and Planning

Even though organization’s data center usually has a resources and capacity planning team, the reality is if you browse most of the organization’s virtual infrastructure you will find out that overall around 40 to 50 percent of resources are always idle. While a lot resources sitting idle new resources continue to be implemented as some of the resources are not suitable for some applications. While virtualization provides business with agility, it is with the extra costs. We often see that even within one data center, due to the fact that data center needs to provide infrastructure for different business units and due to some regulation and policy, applications cannot run on the same hosts thus more hardware and licenses will needed.

Virtual infrastructure management

For a large organization it is very complex to manage such virtual environment, user access rights and admin access rights to different farm, folder and resources are all need to be managed. Multiple virtual center servers, different version control and so on.

People are always talking about the benefits of virtualization but if we do not plan or architect it well, resources waste can happen easily. Instead of cost savings, it actually turns into money wasting. 

Using EA Principles in Enterprise Technical Architecture

Reference

Gartner: Toolkit Best Practice: Using EA Principles in Enterprise Technical Architecture

Enterprise technical architects — that is, technical architects, infrastructure planners, project architects and solution designers — often want to get straight to product comparison and selection. However, better enterprise technology viewpoints, ETA modeling and design work should reflect careful integration with overall business goals, as well as adherence to particular IT drivers and specific technology guidelines and best practices. EA principles are part of the guidelines to leverage — and leverage explicitly. Principles present expected behaviors that if adhered to will enable strategies to become realities.

We Enterprise Architects specify enterprise architecture principles based on organizational vision and strategies. Principles and Standards provide a firm foundation for making architecture and planning decisions, framing architecture and supporting resolution of contradictory situations. Architecture principles guide our architecture work, our decision making and choice of selection. As Gartner indicates “Choosing which principles are appropriate for a given organization at a lower level — for example, for standard ETA models such as technical patterns and technical services, or for particular individual infrastructure designs and implementations — should reflect the general goals of the organization at a high level.”

One of the big challenges for success architecture work is to incorporate a principled approach to designing technology and infrastructure. Each enterprise architecture team has a set of enterprise architecture principles but they are not always applied or used by architects during their architecture definition process. For principles to work a governance framework must be defined: the definition of a principle should specify the decision that has to be made, the choices (eventually), the body (role) that makes the decision and the typical use case (when to use it).

Finally, principles enable continuous improvement of the processes and artifacts. The more organizations know about the principles that guide their decision making — and the more specifically they document these principles in general (and in standard models), and then in per project designs document specifically how the principles are followed or broken — the better their models and designs will be.

Using EA principles in enterprise technology architecture reflects the maturity level of organization’s enterprise architecture. Less mature enterprise architecture often conducts architecture work without fully incorporated a principled approach, ended up with more project centric rather than architecture centric work. Understanding the importance of using EA principles in defining architecture is a critical factor for successful EA.

IPv6 Readiness and Architecture Approach

The most fundamental IT component of an enterprise is the network. The network must evolve to meet changing business requirements. Communication is required for organizations to function, yet costs need to be appropriately managed, and the portfolio of network services delivered by IT organizations should be formalized. The network architecture is a major subcomponent of the technology infrastructure architecture that specifies the design of the communications network. The network architecture framework specifies information such as the network components, their configuration and operating procedures. (EA 874 Enterprise Technology Infrastructure Architecture). 

Most organizations today do not have IPv6 enabled or deployed for production use, it is foreseen that support for IPv6 devices and communication will become increasingly demanded. There are many areas that require IPv6 ready, one area that will require IPv6 is Internet facing services and support for IPv6 only clients. Another area is the Internet of Things, which will bring a proliferation of IP connected devices. IT organization will have to prepare for this very lengthy and large transition to the next generation IP protocol, IPv6. The challenge of migration from an IPv4 network to a federally mandated IPv6 network is becoming a reality, and careful planning of your IPv6 transition will be critical to your success.

Organization needs to develop a future architecture to support current and future requirements for IPv6 based communication. The architecture should address and support the new business solutions that will require the next generation of IP Protocol. In addition, prepare a transition outline and roadmap to realize the architecture. Some envisioned basic preparation phases should cover scoping, training, business cases, and audit of baseline situation.

Organization first needs to assess the implications of IPv6 for the environment, including product compliance, address provisioning and management, routing policies, security, and infrastructure design. This assessment also identifies opportunities to take advantage of IPv6 features and functionality to simplify the environment, as well as areas of risk to be considered during transition to IPv6.

Organization should consider to establish an IPv6 working group to determine the training requirements for levels of IT personnel, such as network engineers, system engineers, helpdesk analysts and security engineers. Determine scope(s) of IPv6 deployment, identify business use cases such as Internet of Things. Audit the existing environment to determine the baseline “as-is” situation and then define the “To-Be” architecture blueprint for each scope.

Internet of Things (IoT) Architecture Platform and Development Approach

Internet of Things (IoT) is about equipping physical objects with smart sensors or actuators and the capability to exchange data amongst each other or with computer system via an IP-based network. The Internet of Things allows objects to be sensed and controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit.

Essentially, IoT expands IP-based networks, like the internet or company-owned intranets, beyond traditional computing devices and shifts it from the digital into the physical space. IoT makes use of synergies generated by the convergence of consumer, business and industrial internet and creates a global network connecting people, data, and things.

IoT means that there is a lot of data extracted from different devices and systems. This data can be an opportunity for a lot of improvements and changes, when interpreted right (e.g. for optimizing the supply-chain-management). Today, most IoT applications are about reacting to the measured data. In future the data could be used a lot more to not only react to a specific situation but to predict what will happen next (e.g. predicting the failure of specific parts of a machine). Therefore IoT will often be combined with Big data & Analytics and IT as a Service (also known as Cloud computing) capabilities to process the vast amount of data and to derive valuable knowledge out of it.

The IoT platform architecture(s) should satisfy the business requirements of today, and position the organization for the future growth in this area. Both vertical and horizontal integration must be strongly considered, and the architecture must enable this through the use of industry standards. Architecture development approach should follow a modular approach to start small and grow smart. This will create an adaptive architecture to cater to dynamic business requirements, driven by business projects.

The approach and general steps to develop the IoT Platform Architecture are:

• Consider the most preferred theoretic target, the ideal scenario based on the greatest potential business benefits
• Assemble the identified use cases and potential vendor / suppliers
• Assemble the vendor / supplier reference
• Evaluate each reference architecture based on the constraints / requirements list
• Look for synergies and commonalities among architectures. Consider future integration points

Master Data Management (MDM) – A phased Approach.

By definition of Wikipedia, “ In business, master data management (MDM) comprises the processes, governance, polices, standards and tools that consistently define and manage the critical data of an organization to provide a single point of reference. Master data management has the objectives of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information.”

The article “Supporting Your Data Management Strategy with a Phased Approach to Master Data management” by SAS brings some interesting points and provides some development approach.

We often talk about the MDM is to create a central repository of data or the master date to provide an organization a single point of reference. But the article argues that “If the goal of master data management is to integrate business value dependencies into a long-term information strategy, it is worthwhile to rethink both the intent – and potentially the value – of the concept of “master data.” Therefore, the focus must shift away from delivering master repositories. Organizations must transition the implementation from being technology-based and consolidation-focused to being value-based and consumption-focused. This more reasonable approach to the idea of master data is not creating a single source of truth but providing unobstructed access to a consistent representation of shared information.”

This article also provides a phased approach to MDM, this approach can influence a phased organizational plan for fully embracing master data management. The plan incorporates five key fundamental techniques to enable master data management success, including:

•        Business data consumer engagement.

•        Data governance.

•        Collaborative semantic metadata management.

•        Data quality management.

•        Identity resolution and management.

In our organization we are developing master data management strategy, this article makes me rethink how we should develop strategy which can help to meet the business requirements. I think MDM not only needs to provide “a single point of truth” master data but it is also important to deliver the benefits of sharing consistent, high-quality data while aligning the milestone and deliverables of medium and long-term information strategy.

Reference

Supporting Your Data Management Strategy with a Phased Approach to Master Data management - SAS

https://en.wikipedia.org/wiki/Master_data_management

Data Strategy

Data Architecture describes how data is processed, stored, and utilized in a given system. Data architecture defines the types and sources of data needed to support the business, in a way that can be understood by stakeholders. One of the most important tasks that a Data Architect is often asked to help with is the creation of an Enterprise Data Strategy. The data strategy lays the foundation for the data and information architecture. 

Data and information is becoming more and more important as it will be an essential and integral part of future business models. Data and information from all over the enterprise, combined with data and information from external business partners and other sources needs to be managed. Big data initiatives will explore a huge amount of data to gain new insights with the objective to further optimize processes and decision making or create new services and business models.

The potentially disruptive shift driven by data and information centric initiatives opens up new markets and improvement potentials in many different domains including products, supply chain, manufacturing, production, sales and marketing, finance and accounting or research and development. Data and information and their “smart” management is one of the enablers for the digitization of organization.

“Top-performing organizations use data for competitive advantage and exploit more internal and external data. Technology doesn’t separate top performers from the rest of the pack; data governance and the alignment of data processes and business processes make the difference.” (Forrester Research, 2015)

The strategic recommendation is to have a joint approach of business and IT. The idea is to develop the data and information architecture with a professional data management and a flexible governance organization together with concrete use cases. This effort will generate sustainable business value and prepare the data and information landscape for future demands.

The Enterprise Data Strategy is:

·       Actionable

·       Relevant (e.g. contextual to the organization, not generic)

·       Evolutionary (e.g. it is expected to change on a regular basis)

·       Connected / Integrated – with everything that comes after it or from it

Reference

http://dataconomy.com/why-organizations-need-a-data-strategy/