Best Practices - Security Architecture and Enterprise Architecture

The more closely aligned the security architecture is to enterprise architecture, the more effective it will be. It should be a goal of an organization to complete the integration of security into EA .

Gartner  highlights a lot of best practices when it comes to security architecture that i want to highlight in this blog

• Security Architecture should be a continuous process
• It improves over time, and is improved with the experiences an organization gets over time
• The templates are created / developed in order to maintain compliance within the organization
• The design should be enabled by iteration with increasingly detailed levels of abstraction

Leveraging both the architectural principles and the methods in the security program of the organization can enable improvements in business alignment, maintain consistency and reuse. However it is a complex strategy that requires experience, practice and patience. 

Ref: https://www.gartner.com/doc/790521/aligning-security-architecture-enterprise-architecture

In my next part of the blog, i will talk about how security is increasingly getting important in cloud space. I will spend some time analyzing the risk involved with cloud and SaaS computing, and use case models for choosing security - appropriate SaaS (Software as a Service)

Enterprise Security Architecture - Overview

Security is always a hot topic. In today's blog i will reflect on how much security is essential for an enterprise. Without security, any organization whether small or large is prone to breaches. We hear every other day about the breaches in health companies, credit card numbers stolen, all this is a result of not a well thought out security layer in a companies infrastructure.
Whenever an organization starts their web presence that involves transactions, storing or transferring PII (personal data), they have to make sure to set up a well defined security layer that makes sure that the organization is protected from the phishing scams and breaches. That the data is well protected as it contains customer sensitive information.
According to the content in one of my class notes, there are five main areas of security for consideration

• Computing Security: Type of security that focuses on secure operations of the computers.
• Data Security : Ensuring that the data is secured and is protected from tampering.
• Application Security: Trying to prevent the errors and breaches in the security that can occur through errors in the design, development or deployment of an application.
• Information Security
• Network Security: Refers to the protection of network resources from unauthorized use. Intranet/ internal network security is essential for a company. This is essential because most of the companies assume that the breach in the security comes from external sources, but what they forget to take into consideration is the compromise that happens from within the system.
• Isolation: this is where the concept of firewalls come into picture.  This is to isolate certain apps from the others. These help in isolating the apps from general usage or unauthorized success.

Depending on what the focus of the organization is, a combination of these security areas will be helpful to create a well defined security layer that will protect the enterprise from the outside breaches.

According to Wikipedia "Enterprise Information Security Architecture is the practice of applying a comprehensive and rigorous method for describing a current and/or future structure and behavior for an organizations security processes , information security systems, personnel and organizational sub units, so that they align with the organization's core goals and strategic direction."

Cloud offerings

An interesting article on cloud services to be managed with right technology resources by Gartner; https://www.gartner.com/doc/2366916/manage-cloud-services-right-roles

With the increase in cloud services, it is very important to pick up right technology resources to establish a well defined cloud space for your organization. This means that this cloud space is flexible in terms of data, but also is secured to protect from malicious activities.

As pointed in the article, the CSB (cloud service brokerage) role will be very effective in the organization that is promoting usage of cloud services. The three primary CSB roles are

1. Aggregation Brokerage
2. Integration Brokerage
3. Customization Brokerage

The CSB will be responsible to assess what type of cloud services a customer requires, and customer demands and requirements for cloud services.

As pointed out in the article, which i also agree with is that the people in CSB role need to be proficient in cloud technologies and services as they play a very critical role in defining the next steps that will take the organization from its current maturity level to the next level of engaging with new technologies. With the CSB roles, the next defining factor is cloud management platforms or CMPs.

According to Gartner, Cloud Management Platforms are integrated products that provide for the management of public, private, and hybrid cloud environments. CMPs are incorporated within the organization by IT personnel to deliver technical cloud services to internal customers. Since these platforms are managed in cloud, they offer a faster delivery of services thus lowering the overall cost of technology. CMPs work very closely with IAAS (infrastructure as a service) platform. 

In order to summarize, CMP alongwith CSB role in an enterprise can help an organization to be more efficient in engaging with new emerging technologies such as cloud computing.

Couple things that need to be accounted for while coming up with a CMP/ CSB model, referring the gartner article

1. evaluating CMP for a hybrid cloud approach

2. Weighing options as an organization for an appropriate cloud offering vendor.

3. can the CSB aggregation tools offer an expanded option of external cloud services to internal users/ customers

4. to implement CSB, CMP tools at the portal level

 

Network Architecture - a subcomponent of technology infrastructure architecture

An important subcomponent of technology infrastructure architecture is Network Architecture.

In order to transfer information within and outside the organization, communication between resources, talking to the backed servers, databases, applications (external and internal), in all of this we need a well defined, secured network. Network is nothing but a component that keeps everything connected. In the absence of a well defined, secured, consistent network, the organization will not be able to talk to its various applications, and hence this will lead to a communication/ technology blackhole within the enterprise.

With more solutions being cloud and mobile based, it has become even more essential to define and design a network plan that can not only keep the applications and connection alive but can also handle heavy data traffic.Thus, it is important as a technology infrastructure architect to design a self sustained highly secured network diagram that is well equipped to fight malicious viruses, as well as be able to securely and efficiently let the communication flow.

An example of physical network infrastructure diagram from technet: https://technet.microsoft.com/en-us/library/cc961037.aspx

Overview - Technology Infrastructure

In my previous blog, i talked about big data concepts and how data is very important and essential to an enterprise as a whole. In today's blog, i will be giving my overview on technology infrastructure, major trends surrounding this layer and understanding the opportunities.

Technology layer supports both hardware and software technology. According to http://www.enterprise-architecture.org/techology-architecture-tutorials/58-techology-architecture-overview , technology layer is split into three views; Conceptual, Logical and Physical.

1. Conceptual layer: The question of "what", meaning what technology capabilities are required to provide the appropriate technology infrastructure for the enterprise
2. Logical layer: The question of "how", meaning how the technology infrastructure for the enterprise will be achieved. 
3. Physical Layer: this captures the implementation and deployments of technology in the enterprise.

How is this different from a system architecture? According to the chapter read " While system architecture, applied specifically within the context of information systems, encompasses both the application architecture and data assets, and their logical interrelations to the business processes they support; the technical architecture describes in detail the software and hardware capabilities to fully enable such application and data services" In other words, system architecture provides an umbrella over application architecture and data assets, whereas technical architecture focuses on the software and hardware capabilities to support system architecture. Technology architecture is dependent on application architecture and hence it is very important to make sure that within an enterprise various components of an application architecture are well defined. A very detailed mapping needs to happen between both technology and application architecture, so that both of them can work in sync and be overall beneficial to the enterprise.

Big Data Disruptions, best practices

In my previous two blogs I touched upon what is data architecture, how it is important, overview and its relationship with the Information architectural layer.
This blog I wanted to touch on the best practices for Data Stewardship and the big data disruptions.

Lets start with what is Data Stewardship? According to http://searchdatamanagement.techtarget.com/definition/data-stewardship, data stewardship is the management and oversight of an organizations' data assets to help provide business users with high quality data that is easily accessible in a consistent manner. These roles are common in organizations that are attempting to exchange data precisely and consistently between computer systems and also making them available for reusability in the future (ref: https://en.wikipedia.org/wiki/Data_steward)

Some of the benefits of data stewardship that I see, with reference to those listed in wiki https://en.wikipedia.org/wiki/Data_steward

• consistent use of data management resources
• easier mapability between various computer systems
• lower costs during migration
• avoiding redundancy and overlapping of information across the layers
• compliant with the organizations informational layer
• reusability

Now lets focus on some of the viewpoints shared in a Gartner article (https://www.gartner.com/doc/554646/best-practices-data-stewardship)

- data quality needs to be considered within a business process
- need of an effective governance strategy for data quality across the entire organization

 With big data comes the efforts of managing this large amount of complex data within an organization. If the data quality is not maintained, as noted in the Gartner article, it can lead to the failing of many strategic business initiatives. Programs such as CRM (customer relationship management), BI will not be able to generate enough business if the quality of the data is not improved. The article talks about various ways in which this problem can be alleviated. One of the proposal that I don't completely agree with is " stewards residing in business and not in IT organization". In my opinion, even though we identify that the business is responsible for the quality of data, stewards should reside in the middle layer that connects both business and IT. As much as Data stewards need to understand the business, they also need to understand IT infrastructure, so that they can make sound decisions when it comes to harnessing data with quality, and if the current data architecture of the organization can even sustain such proposal. The only way data stewards can be respected within the organization is if they have a combined knowledge of both business and IT infrastructure. Having one of the two will not give them a holistic perspective of the entire data setup within the enterprise architectural layer.

Data steward in the middle of Business and IT layer


 

Lets quickly touch on various roles/ responsibilities of data steward (ref: https://www.gartner.com/doc/554646/best-practices-data-stewardship)

• ensuring the consistency and accuracy of data
• implementing governance tasks and achieving data quality metrics
• responsibility in master data management objectives
• identifying issues with source systems
• updating and maintaining documentation, taxonomies
• proactively finding errors/ bugs or issues within data
• ensuring data is compliant with industry standards

Lets shift gears and talk a little on Big Data Disruptions. Ref another Gartner article (https://www.gartner.com/doc/1964716/big-data-disruptions-tamed-enterprise)

Big data is an eye opener to the challenges that are being faced by the organizations on a daily basis related to data. It provides an insight to the deepest levels of the organizations, their relationships within the company and outside the company. If not handled properly by the business/ enterprise architects, they big data challenge can have a negative impact. Some of these impacts are, also as discussed in the Gartner article, reference above,

• although big data shows patterns on data types, if this information is not turned into a competitive advantage, then there is no use in spending money on all of these tools.
• big data will give a visual representation of cultural issues to business and IT leaders, this can be a positive impact, since the leaders can identify and work on solving these issues in a more proactive and effective manner

I do want to highlight one point that is mentioned in the Gartner article (ref URL above); "big data creates business value by enabling organizations to uncover previously unseen patterns, and to develop sharper insights about business environments". I strongly agree with this statement, since I believe Big data makes an organization very powerful, since they have a better understanding of the business processes within their environment, and the steps they can proactively take to either enhance the processes or work on the gaps and issues that got identified during this process.

Big Data - Handle with Care
 

To summarize, as long as we as an organization understand the criticality and importance of Big Data, convert the findings through data mining into effective and impactful strategies, as an organization we can be more efficient, have stronger relationships with our employees, vendors and other organizations.
 

Relationship between Information architecture and Data architectural layer

Data and information layers are interconnected in my opinion. According to Platt (2002), and as mentioned in one of my course readings " the information layer describes data that the organization needs to run its business processes and applications", in other words, without data information layer cant exists, and vice versa.
While we are working on streamlining data architecture within the information layer, it is important to take into consideration, and something that a data architect should keep in mind;

• data recovery
• data modeling and analytics related to the organization
• data handling
• big data usage and how it can be used within the enterprise
• data security, when the data is being used from outside the organization
• data storage, whether its physical servers or cloud.
• easy data accessibility and availability

From my experiences in the Information Systems domain, we have to be very careful in layering the data layer. This layer not only interacts with the inner architectural layers within an enterprise but it also talks/ interacts with the external applications both for in flow and out flow of the information. To ensure that this is well detailed, the use of data modeling/ UML diagrams and analytics software come into use, and allow us as architects to get a visual of the entire process. This also helps in cleaning out redundancy, overlapping of information assets, that could arise over the course of the data flow/ information flow within the enterprise.

A great blog that I ran across on IBM, layers the interaction of data in the BI (Business Intelligence world), data repositories, data warehouse architecture,  http://www.ibm.com/developerworks/data/library/techarticle/dm-0505cullen/
One of the diagrams that really caught my eye is where the analytics layer that provides the business analytic applications and their underlying capabilities and services, adding value to all areas in the enterprise.

Referencing http://www.ibm.com/developerworks/data/library/techarticle/dm-0505cullen/part4image3.gif