high level solution presentation

Writing an effective end-to-end High-Level Design:

In this article we outline best practice on what constitutes a high quality E2E solution design.

The Architecture Design Blueprint or Technical Options Assessment is an effective way to produce a lean and just-in-time architecture that is aligned with the shorter sprint cycles of incremental product delivery. End-to-End HLDs are needed for undertaking complex transformation projects such as introduction of new IT stack, the introduction of a new product line, or a new business.

A draft E2E HLD is produced with the engagement of the stakeholders across Business, Technology, Suppliers, and the Project team through Architecture and Design workshops. The E2E HLD is produced over several design sprints with walkthroughs to the relevant stakeholders. The main components are:

• Application Context “as-is” and “to-be” diagrams are created and used to illustrate the impacted Applications and the logical interfaces. 
• Technical Flow diagrams are used to illustrate the Interfaces between applications and information flow. 
• Data Flow diagrams are used to illustrate the flow of data between applications. 
• Architecture and Design RAIDD is used to manage the Risks, Assumptions, Issues, Decisions, and Dependencies log. 
• The Requirements Traceability Matrix is used to demonstrate E2E traceability. 
• The key to the successful E2E solution design delivery for a complex transformation project is a comprehensive E2E HLD structure that provides a holistic view of the solution and continuous collaboration with all key stakeholders: business, technology, and all suppliers.

It is important to establish a framework and process for a quality design deliverable.

Comprehensive End-to-End HLD Template

  A typical End to End HLD template structure includes:

  1. Introduction: 

Provides an overview of the project and a brief summary of the solution to set the scene to the stakeholders. Provides a technical view of the project scope and outlines where some of the requirements are to be met by non-technical means such as business processes. Outlines dependency on other projects and the impact of the solution proposed in this HLD on other projects.  This section establishes a common high-level understanding of the project scope and the proposed solution for stakeholders at all levels.  

• Project Summary
• Project Scope (In/Out)
• Document Context
• Target Audience
• Glossary/Definitions    

2. Architecture

a. Architecture Diagram

Provides the overall Solution Context Diagram (example in the diagram above) that highlights the impacts to Business, Application, Technology layers, clearly marking the modified, newly introducing and decommissioning components.  This section visually establish the boundaries of the overall solution and the proposed solution context for stakeholders at all levels.

Provides background to relevant target solutions, Enterprise Architecture roadmap/guidance, including those partially-relevant and those looked at but not relevant, so that the consideration is captured in case of later questions.  Solution is ensured to :

• Deliver towards Enterprise Architecture Strategy and Roadmap
• Align with all Architecture & Design patterns
• Meet best practice guidelines
• Comply with current IT strategy including introduction of new components & obsolescence roadmap
• Follow the Business, Regulation, System, Cloud and Network security guidelines and be compliant with the Security & Non-Functional requirements

c. Architecture Principles & Patterns

Provides the list of applicable Architecture Principles and Patterns, and more importantly identifies the need for any new principles and patterns.  This section demonstrates the adherence to the Enterprise Architecture Principles & Patterns and where gaps were found to create new Patterns and Principles.

d. Architecture Dispensations

Outlines the deviations from the target Enterprise Architecture roadmap and best practice. Discusses the longer term plan to move toward the more desirable approach. In particular, outlines the steps to be taken within the project, or separately to “make good” any undesirable aspect of the proposed approach.  This section establishes the approach to reducing Technical Debt, cost of the Technical Debt and the approach to bring the alignment to Enterprise Architecture Strategy.

3. Solution Description

Provides a summary of the overall technical solution, applicable Architecture and Design patterns, clearly stating what the project is adding or changing, Application Impact Matrix, impacts to Customer Journey, Customer/User Experience, Use Cases/Technical Flows depicted as UML Sequence diagrams, changes to Business Processes and Business Service.  This section establish a common understanding of the technical solution for stakeholders including Business, Technology and Suppliers’ teams.

• Overall Solution
• Customer Experience
• Customer Journey
• Business Processes
• Application Impacts

This section details the changes/impacts to each Application or element of the Application. Each sub-section covers the work for a given Application, the Functional/Capability Design, Interface Impacts, Data Entity Impacts, Infrastructure Impacts, Capacity Impacts, Operational and Support Impacts, Business Continuity and Resilience Impacts, Testing Impacts, Security Impacts, Reporting Impacts, End‑to‑end Service Impacts, and non-functional issues such as Capacity, Regulatory, Security and Non-functional Impacts.  This section provides a 360° coverage of the solution for each Application and establish the boundaries of delivery for the Application Owners, Application Delivery & Application Support teams.

5. Interfaces

This section lists the impacted Interface Matrix and details each interface changes with a Technical Flow Diagram represented as a UML Sequence Diagram, applicable business rules, message flow, service orchestration, applicable integration patterns, principles and implementation guidelines.  This section establishes the Integration and Interface Impacts, and for each Interface, establish the boundaries of delivery.

6. Data Impacts

This section details the changes to key data entities and their relationships, data changes subject to review as part of Data Architecture and Information Governance, Data Master-ship, Data Residency, applicable Data Security principles and patterns, applicable Regulations such as GDPR and Data Policy Impacts.  This section establishes the Data Impacts and helps seek the approval of Information Asset Owners, Information Governance and Security Teams.

7. Reporting

This section details the impacts to Management Information/Business Information Reporting, including changes to existing reports, new reports required, data sources for reporting, non-functional reports, applicable information retention policies.  This section establishes the reporting impacts and provides the correct level of reporting to the Business & Management.

8. Infrastructure

This section details the end-to-end impacts to On-premise & Cloud Infrastructure including hardware, data centre and cloud connectivity, location, issues of deployment and decommissioning of live and test environments. This section establishes the Infrastructure needs, the solution alignment with Infrastructure Strategy and communicates the solution to the Infrastructure Build & Deployment Teams.

9. Testing & Environments

This section details any Architecture and Design Impacts arising from Testing, in particular for the environments considered for testing and the test software.  This section clearly indicates to the Test Teams Environment considerations.

10. Implementation & Deployment (per release)

This section details the implementation and deployment approach, describing the capabilities, release dependencies and ongoing change impacts.  This section provides the necessary considerations for the Application Build & Release Teams.

11. Operational Impacts

This section details the Operational impact the Project and the proposed design introduces, the list of non-functional deliverables for Security, Availability Management, Service Levels, Service Capacity, Performance, In-life Support, Backup and Archiving, Business Continuity & Disaster Recovery and Service Failure Impacts and Service Recovery Mechanisms.

This section provides the necessary due diligence to  Operations & Service Teams and the Service Owners.

• Non-functional Deliverables
• Information Governance
• Availability Management
• Service Levels
• Service Design
• Performance
• In-life support
• Backup & DR

12. Decommissioning & Obsolescence

This section details opportunities for decommissioning of applications, hardware or individual element/interface. It also covers the migration of interface/data prior to decommissioning.  This section identifies all the opportunities for decommissioning and achieving Organisational benefits in reducing complexity, support costs, licenses, and resources.

13. Legal & Regulatory

This section articulates how the solution meets the applicable regulatory and compliance requirements including Information Governance, GDPR, Health & Safety, Equality, Environment Policy, Accessibility Standards, Sarbanes Oxley, Business Continuity, Security Policy, Public Sector Network compliance, Data Retention and Disclosure.  This section provides the necessary due diligence to Legal, Regulatory & Compliancy.

All companies have a different way of delivering change, this is why the support of expert professionals is important.  Our Partner Bruhati can help you to define governance frameworks, templates, and tools.  For more information and a FREE consultation please visit  www.bruhati.com  or write at  [email protected] .

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Manuel Di Toma

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Data & Finance for Work & Life

Solution Design: Template, Steps, & Definition

In business, solutions are a way of life. Companies aim to solve customers’ problems, and to do so, they have to overcome many of their own problems. However, solutions are rarely easy. They have to be fast, affordable, and qualitative — but they’re rarely all three. In addition, they need to be well understood throughout the organization. If not, it’s tough to get employees all working around a common goal.

In other words, solutions need to be designed in a way that is accessible to everyone and optimizes speed, cost, and quality. The process of finding business solutions outputs results in visual representations that we call solution designs.

Solution Design Template

If you’re here for a solution design template, you can download a flow chart template here for PowerPoint . It can be adapted to any solution — just make the appropriate changes to fit your situation. That said, if you want to really understand how to use them and impress your team, keep reading below to learn about the steps to make a good solution design and to see a few examples.

Definition of Solution Design

So what is solution design exactly? Written succinctly, solution design is the high-level visual representation of business solutions that outline how the company will minimize the time & cost of solution implementation and maximize the solution’s quality.

It’s important to note that the actual solution is not the design — only the visual representation of the solution is. It’s just like an architect’s blueprints: the building itself is the output, but the blueprint in the design for that output.

Solution designs come in a number of formats, including diagrams, bar charts, interactive visualizations, time lines, waterfall charts, and combo charts, but the most common format is flow charts .

Let’s look at steps to creating a solution design, then use a downloadable template to explore some examples.

Solution Design Requires Data Analysis

Modern solutions require modern skills. Big companies like Amazon made the transition to a data-driven culture in the early 2010s, and all other businesses and industries are following. Data analysis is a key part of any solution because data determines (1) which solution is best after testing, and (2) how successful the solution is through KPIs (for example, ROI or customer acquisition). When designing solutions, you must rely on data!

Don’t forget, you can get the free Intro to Data Analysis eBook to cover your data fundamentals in under 60 pages.

Get a Solution Design Resource

This article outlines what solution design is, and you can implement it using our guide. Sign up below to be eligible for a free copy!

Steps to Creating a Solution Design

Before you can start building a solution design, you need to discover what your solution is. The steps to developing a solution design, thus, are divided into two categories: 1. discovering & testing the solution, and 2. creating the solution design. Let’s look at them in detail here:

• Identify the target time frame. Timing is a core criterion for your solution, so you should define it well and get a buy in from all of the shareholders involved.
• Identify the budget for your solution. It’s all about the money — define your budget so you have a clear idea of if your solution is in the right price range .
• Identify the quality standards. What do your stakeholders expect? Do they want a quick-fix solution or one that will stand the test of time?
• List out all of the stakeholders and their requirements. Other than time, money, and quality, ask yourself if there are other criteria important to shareholders? Does your boss want the solution to look a certain way? Does he/she prefer accessibility over efficiency?
• List your assumptions. You can do this by verbally explaining the problem to a teammate and having him/her give you feedback on assumptions you’re making. Likewise, let other teammates explain the problem so you can understand what assumptions they make.
• Think of all possible solutions. This may sounds like a no-brainer, but it’s less common than you might think. In my experience, when people find a solution, they want to run with it instead of investigating if there’s an even better one waiting.
• Get creative with solutions by brainstorming even the craziest of options. This is my favorite step. You can let your imagination run wild. Forget about money and time, and just try to imagine a bunch of different ways in which you can find a solution to the problem. It often results in a number of useless ideas, but at least one good one.
• Settle on the solution. Once you’ve brainstormed and imagined a host of solutions, you need to settle on one that responds best to your requirements. This is your going-in position.
• Test the solution . If possible, try testing the solution in a mock environment. If you’re using data, use dummy data . If the solution doesn’t work, go back to step 6. If it does, get an initial buy-in from stakeholders. Once they agree, you can use this as the basis for your solution design .
• Test a few formats for your solution design. We’ll look at formats in the next section. It’s important to try several different formats with only the major information to see which one best fits your solution. As a rule of thumb
• Decide on the format you want to use.
• Include the problem. If there are more than one, make sure to show the several problems needing resolution.
• Include the constraints. Often called stakeholder requirements, constraints are non-mission critical borders by which the solution must abide. For example, a car mechanic may need to use an off-color paint simply because the car owner wants it that way.
• Create your solution design in a user-friendly software, such as PowerPoint . There are loads of software available for creating solution designs, but the challenge is making the design shareable among many parties. If you remember from the introduction, solutions need to be well understood throughout an organization. If not, it’s difficult to gather people behind a common goal. That’s why I suggest using Microsoft PowerPoint. If you’re working in a company that doesn’t have powerpoint or an equivalent, you can use the software available to you and take a screenshot. It’s less flexible, but get’s the job done.

Formats of Solution Designs (with an Example)

To illustrate what solution designs look like in practice, let’s look at an example across three formats: waterfall charts, combo charts, and flow charts.

Imagine you run the sales department in a wholesale watch company called Batch Watch . The company just suffered a bad year, and your job is to increase sales by 15% in the this year. You can’t increase the current employee count, but you can lay off people if they are value destructive, and hire new ones in their place.

You decide the best way to increase sales is to eliminate your top 2 sales people, who have less experience in internet marketing, and hire 3 new internet marketers. You’re betting that your clients have moved to online purchases instead of in-person contact sales. You can also minimize the cost of your batch sales by eliminating the travel fees.

A bar chart is helpful to understand the situation, but it’s does little to explain the solution. We have to read the text to understand what the next steps will be.

Combo chart

A Bar Chart with Percent Change is also helpful for understanding the situation, but it does little to illustrate the solution. Again, we have to read the descriptions to understand how we plan to find a solution.

This flow chart clearly identifies the problem, the reason for the problem, and the solution. For simplicity’s sake, I’ve kept it very plain here, but you could add a timeline and more labels if it adds value in your situation.

Advantages and Disadvantages of Solution Designs

Solution Designs come with advantages and disadvantages. Some professionals glorify them as ultimate cross-departmental communication devices, while others critique that they oversimplify situations, resulting in poor collaboration. Here’s a list of advantages and disadvantages:

• Simplifies complex topics
• Clearly identifies steps to solutions
• Easy to share across and organization

Disadvantages

• Oversimplifies otherwise complicated challenges
• Leads to false consensus that must be modified in later stages

About the Author

Noah is the founder & Editor-in-Chief at AnalystAnswers. He is a transatlantic professional and entrepreneur with 5+ years of corporate finance and data analytics experience, as well as 3+ years in consumer financial products and business software. He started AnalystAnswers to provide aspiring professionals with accessible explanations of otherwise dense finance and data concepts. Noah believes everyone can benefit from an analytical mindset in growing digital world. When he's not busy at work, Noah likes to explore new European cities, exercise, and spend time with friends and family.

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How to Present to Senior Executives

• Nancy Duarte

Cut to the chase. Keep their attention.

Senior executives are one of the toughest crowds you’ll face as a presenter. They’re incredibly impatient because their schedules are jam-packed — and they have to make lots of high-stakes decisions , often with little time to weigh options. So they won’t sit still for a long presentation with a big reveal at the end. They’ll just interrupt you before you finish your shtick.

• ND Nancy Duarte is a best-selling author with thirty years of CEO-ing under her belt. She’s driven her firm, Duarte, Inc., to be the global leader behind some of the most influential messages and visuals in business and culture. Duarte, Inc., is the largest design firm in Silicon Valley, as well as one of the top woman-owned businesses in the area. Nancy has written six best-selling books, four have won awards, and her new book, DataStory: Explain Data and Inspire Action Through Story , is available now. Follow Duarte on Twitter: @nancyduarte or LinkedIn .

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Posted on Aug 4, 2021

Creating successful high-level software solutions

Building software most of the time feels like following a cooking recipe. For designing software solutions from scratch, we could also have some guidelines to help us through the process, ending up with a "recipe for creating successful high-level software solutions".

Introduction

High-level solution creation recipe, understand the problem, capture security implications, understand current technology situation, evaluate existing solutions in the market, prepare the data structure, identifying entities, enterprise vs startups, identify how you will solve the problem, design the high-level solution, monitoring, telemetry, and kpis.

The present document intends to serve only as a guide for future high-level solution creation processes, every solution is unique, but the rationale to understand might include common steps. This document will expose a common lifecycle that may be present in most of the cases when we onboard a new project, based on personal experience and other’s experiences. In addition, will be mentioned some edge cases making the guide more flexible.

Among the duties of a solution architect, it’s included helping in the new clients’ onboarding process, understanding needs, answering questions from the technical perspective, and finally, come up with a high-level solution plan. The process is an iteration of steps from understanding the client’s requirements, to design a solution. To ease that process, this document will include a common recipe applicable as the basis for your next project.

This section will elaborate on the creation of a solution and proposes a series of steps that can be followed to develop a successful solution.

Conceptual solution process

Captures a big-picture vision of the whole solution.

The first step, and the most critical, it’s to understand what the end-users require to solve in the project. As a solution architect, you need to understand it intimately, because you will need to be able to answer questions throughout the process. In particular, you need to answer the “why” and “what” questions. Eventually in the flow, you will answer the “how” question.

A good approach to understanding the problem, it’s to gather all the possible information from the end-users. This includes talking with the end-users, having them exposing their desired workflow in order to understand the problem and how the solution should work.

While doing so, remember that most people can only think of a high-level “wish list”, it’s expected that the architect asks the correct questions, to understand the high-level “why” concern, helping you to make fast, calculated decisions during the build process, and eventually, together come up with a more defined solution.

• Take notes, those are your best friends.
• Understand “why” are we trying to solve and “what” will be the outcome result.
• Don’t be afraid to ask questions, this will reflect you are following the idea, and more importantly, you’re becoming an expert in the business.
• When you are listening to the problem, and you realize it’s too complex, apply the “divide and conquer” approach.
• Listen to the end, you’ll need every single piece of information to come up with a solution proposal.
• Sometimes our end-users will need some guidance through the process of understanding the problem.

One of the biggest aspects of designing a solution, it’s understanding and complying with any security implication driven by the business requirements, mostly related to data.

The first layer of implications is to build the data warehouse for the solution. There are some aspects we should consider before making the decision:

• Is there any contractual requirement that limits where the data should live?
• Is there any legal data restriction?
• Should we comply with any security protocol to store data?

By answering these questions we can determine:

• If we’re allowed to use cloud services or must be an on-premise solution.
• It will tell us about the target zone where the application could be deployed.
• If we’re allowed to store raw data, or we should limit the data we can save.
• If we should comply with any data certification or we can use another service to solve that part.

Secondly, the authentication process. Shall we manually save credentials into our database? Could we instead rely on a service to fulfill this? Those are some of the questions we should answer for our final proposal.

Finally, if we’re designing a solution that will be plugged into an existing environment, it’s important to know if there is any restriction to monitor the logs produced, this consideration becomes more important when the solution is running in production.

• Collaborate with the end-users, since they are the business experts they well know or at least have an idea of any security restriction.
• Learn from other experiences. Research other solutions looking for known lessons about security implications.

A well-designed solution takes into consideration a variety of aspects prior to design the actual solution. The solution architect may face one of these scenarios:

• The client hasn’t an IT team. The solution should be developed from a greenfield environment, building a technology vision along with the solution.
• Under this scenario, it’s important to keep in mind that (unless the current technology status is not optimal) we’re here to collaborate, and not trying to reinvent the wheel. Our solution implemented must work consistently with the current elements in the environment.
• If there is an existing IT team, schedule some time to work with them to learn how they work and the team’s dynamic.
• If there is no team, but there is a technical counterpart, schedule a meeting to gather information, ask about previous considerations or any vision in the long term. All the information collected should be used when we’re designing the high-level solution.

Logical solution process

Describes software components, how the information flows, and control flows among the components within the system.

Regardless of how unique you think your problem or solution is, it’s likely that someone has attempted to solve it before.

Look for similar products in the market, find existing architectures, read or ask what your peers have said about other solutions, and check with your stakeholders to see if they know similar approaches.

• List what works and what doesn’t work from other solutions, learn from other’s mistakes.

Software solution process is all about solving problems, automate repetitive tasks and produce useful output for the end-users. How your data flow is structured dictates how your solution should look in the end.

Data structures refer to how your data will flow within your solution. Initially, we should ask:

• For instance: user input, service communication, data ingested, process transformation.
• For instance: process transformation, consumed by another service, reports.

Organizing our data may include distinct structures. The most important is how you will organize your database. The first step, even before choosing the approach and the engine, it’s to define the entities, and for that, we’ll use all the information gathered from the previous conceptual process.

What is an entity? It’s something you want to store data about. We can think of entities as tables in our database, and eventually design our solution to use it.

We’ll analyze the business requirements, and working out the nouns in the sentences. What are our nouns? They are things or objects. Nouns will be table representations, each one could be a potential table in our final database design.

Once we finalized to identify all the nouns, it’s time to define what properties we want to store about those entities.

• With practice, from the conceptual process, we would be able to highlight the tables in the middle of the brainstorm.
• Study existing solutions. There are some business scenarios with a well-defined recipe in terms of data structure that we can try to adapt to our purposes.
• Explore the best relation approach for your final data, determine why relational/non-relational is the best option for you.
• Start simple, let your data grow along with your solution.
• Be careful when our solution requires consuming data from third-party service, this could lead potentially to synchronization problems or data corruption.

The “how” may vary if your solution is targeted for an enterprise business or a startup. These are some aspects we should take into consideration, depending on the target.

For enterprise business

• The planning of the project could be in longer-term and may involve multiple teams. Identifying bigger elements and think ahead about microservices could result in benefits for the overall interaction.
• The lifetime expected for the solution may be longer, so analyze all the internal and external interfaces, be prepared for creating a solution that could support/solve problems in the future.
• The business should know more about the “why” and the “what”. Take advantage of that and plan ahead in the future.
• Your stakeholders could expect more detailed documentation about your solution.

For startups

• The main goal at the beginning is to prove the concept. So plan your solution to solve the most urgent problems.
• The lifetime expected is shorter in comparison with an enterprise solution. Don’t be afraid of designing new solutions every 6 months, that means our application has grown enough and end-users ask for more.
• The business requirements could be limited. We should expect to shape some knowledge along with the stakeholders. Design your solution complexity level to scale with your business. Under this scenario, simplicity is better than complexity.
• Don’t over complicate your solution. Deliver just enough design.

At this stage, after you’ve become familiar with the “what” and the “why”, the “how” is the next logical question. Start from the top: what are you building? How will users interact with your solution? What functionality will the users require? etc.

One common technique is to apply Conway’s law, which is the idea that organizations that design systems are constrained to produce designs that are copies of the communication structures of these organizations. Basically, the elements of your solution should communicate as the organizational structure.

As you peel through the layers, you’ll find that most of your potential features can be categorized/grouped into different types of deliverables. Features can be categorized as one of the following:

Infrastructure

Required for the solution to get started. E.g. data modeling, security, authentication, storage, environment.

Pre-requisite features

These are user-level management features. Maintenance tasks. E.g. user management, configuration settings, profiles.

Transactions

The core of your solution, as these are activities your solution is automated around. E.g. Bookings through our system, sales for our customers, cancellations, reminders, activities that save time and money.

Business results

This is where users can realize the solution has worked for them. E.g. Reports, metrics, automated procedures, automated alerts.

Once the features are categorized, you can start making technology decisions. You’ll have to decide things like buying versus building, which platform to build on, whether you’ll use pre-built open-source solutions or if you’re going to build it yourselves, etc.

• You must begin by imagining the end, then reverse-engineer your way.
• Define your functional and non-functional requirements.

The final step is to produce documentation with your solution in a proper and understandable format. There are several techniques we can explore and leverage to produce the solution documentation. Among the approaches, we can use one of the following methodologies:

• Viewpoints and perspectives.

Regardless of the approach chosen, the delivered documentation is expected to be useful and readable for different groups of stakeholders, technical and non-technical. As the final output, we should provide a high-level solution architectural documentation, that must elaborate on the functional and non-functional requirements and presents a high-level view of all the elements that will interact to make up the solution.

• Practice just enough documentation.
• The initial solution must not be the final version, it’s preferred to implement continuous architecture.

Final considerations

Once you designed your solution, it’s time to work on improving the platform. To deliver your solution to production-ready is just the first step, afterward will be necessary to learn from the user in order to understand what would generate more value for coming releases.

Your software architecture should take in mind to instrument your applications. Define with your team how to prevent issues/bugs even before they happen or the user notices. Work with your stakeholders and define useful metrics to measure your business success.

When we are designing a new solution, the first step is understanding the problem and how to solve it. This guide should be read just like a to-do list for understanding and onboarding a new project in the practice.

• https://www.forbes.com/sites/forbestechcouncil/2016/10/19/a-four-step-process-for-building-a-software-solution-from-scratch/?sh=25c8e3595ef5
• https://www.mitre.org/sites/default/files/publications/pr-17-4589-guide-for-creating-useful-solution-architectures.pdf
• https://gohighbrow.com/identifying-entities/

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From Abstract Concepts to Tangible Value: Solution Architecture in Modern IT Systems

1. Overview

Systems architecture involves designing, planning, and structuring a complex system’s organization and functionality. It is a critical engineering component that is vital in ensuring that a system functions effectively and efficiently.

Since the early days of software engineering , the concept of systems architecture has undergone significant evolution. Initially, systems were relatively simple, and their architecture was ad-hoc and informal. However, as technology and systems grew more complex, architects realised the importance of designing modular, scalable, and easy-to-maintain systems.

One of the earliest approaches to systems architecture was the Structured Programming paradigm, which emphasized using control structures such as loops and conditional statements to manage program flow. This approach was later refined with the Modular Programming paradigm, which advocated using modular code blocks to increase reusability and maintainability.

In the 1980s, Object-Oriented Programming (OOP) became popular, introducing the concept of classes and objects, which encapsulate data and methods and communicate with one another through well-defined interfaces . This approach was highly effective for developing large, complex systems and remains a popular approach to systems architecture today.

Recently, the industry has seen a shift towards microservices architecture. In this approach, a large system is broken down into smaller, independently deployable services that can communicate with each other through APIs . This approach allows for greater scalability and flexibility, as each service can be developed and deployed independently.

Today, systems architecture continues to evolve, with new approaches and paradigms being developed to meet the needs of modern systems. Regardless of the specific approach, the fundamental principles of systems architecture remain the same: to create a high-level design that meets the system’s requirements, is modular, scalable, and easy to maintain.

This article will discuss the fundamental principles of software systems architecture. The ideas presented here are based on excellent lectures from the MIT OpenCourseWare channel on Youtube. We have dedicated a separate five-part series on solution design , which we highly recommend you read.

2. What Other Topics Does this Series Cover?

Interface Design and Management

Interface Design and Management — A How-To Guide for System Engineers

Interface Definition Document Template

Interface Design and Definition Document Template — A Short Guide for the Best Results

Large Systems Integration

Systems Integration — Challenges and Solutions to Assembling Large Systems

Solution Architecture

Software Architecture and Design

Software Architecture and Design — Order, Complexity, and Chaos

3. Architecture vs Design — Which Term to Use?

Here are the key differences between the concepts of “architecture” and “design” in software systems:

• Scope: Software architecture refers to a software system’s structure and organization. It includes high-level decisions about the system’s components, interfaces, and behaviour and the relationships between them. In contrast, software design focuses on the detailed design of individual components and their interactions.
• Abstraction level : Software architecture concerns abstract concepts and high-level decisions, while software design concerns concrete implementations and low-level details.
• Timeframe : Software architecture decisions are typically made early in the development process before any significant coding has been done. They are intended to provide a framework for the rest of the development process. In contrast, software design decisions are made later in the process as the system details are fleshed out.
• Stakeholders : Software architecture decisions often involve input from stakeholders outside the development team , such as business analysts, project managers , and customers. Software architecture decisions significantly impact the organisation’s business strategy and long-term goals. On the other hand, software design decisions are typically made by the development team alone.
• Flexibility : Software architecture decisions are harder to change later in development than software design decisions. This is because architecture decisions have a wider impact on the system and its stakeholders, and changing them can be more costly and time-consuming . Software design decisions, while still important, are typically easier to change later in the process.
• Scale : Software architecture concerns the overall system and how its components fit together. As a result, architecture decisions tend to have a bigger impact on the system as a whole than design decisions. Software design, in contrast, is concerned with the individual components themselves.

In summary, while both software architecture and design are essential aspects of software development , they focus on different levels of abstraction, have different stakeholders, are carried out at different times, and have different levels of flexibility and impact on the system as a whole. Understanding these differences is crucial for effective software development and project management .

4. Creating Business Value

4.1 business and product value for organisations.

In software, business or product value refers to the benefits a software product or solution provides to a business or organization. These benefits can include the following:

• Increased efficiency
• Customer satisfaction
• Cost savings

Business value is a key consideration in software development, as it drives the decision-making process for software projects .

Business value is not just limited to the initial implementation of a software solution. As the software solution is used and evolves, it should continue to provide ongoing business value. This can include regular updates and enhancements that improve the software’s functionality or address new business needs.

Business Requirements: An Essential Guide to Definition and Application in IT Projects

4.2 Business and Product Value for Society

Product value should be measured not only in terms of its benefits to businesses or organizations but also in terms of its impact on societies or communities. In today’s world, there is a growing awareness of the importance of social responsibility and sustainability in business practices, which also extends to software development.

Software solutions can significantly impact society, both positively and negatively. For example, a software solution that improves access to healthcare or education can positively impact society. In contrast, a solution that perpetuates biases or discrimination can have a negative impact.

As such, it is essential for software development teams to consider the potential social impact of their solutions. This can include conducting a social impact assessment to identify potential positive or negative impacts on communities or societies.

Measuring the social impact of software solutions can be challenging, but it is essential for ensuring that software development is socially responsible and sustainable. This can involve working closely with stakeholders, including community groups, to understand their needs and concerns and incorporating their feedback into the development process.

4.3 The Creation of Business Value

The below diagram illustrates the value creation process.

Value creation in software occurs through a process that involves identifying and delivering value to customers or end-users. This process can be broken down into three key components: value identification, value proposition, and value delivery .

4.3.1 Value Identification

Value identification involves understanding the needs and desires of customers or end-users and identifying opportunities to create value through software solutions. This can involve: conducting market research, engaging with customers and end-users, and analyzing data to identify areas where software can provide value.

4.3.2 Value Proposition

Once the business value has been identified, developing a value proposition is next. This involves creating a clear and compelling statement of a software solution’s value to customers or end-users. The value proposition should communicate the solution’s benefits, how it addresses customer needs or pain points, and how it is superior to alternative solutions.

4.3.3 Value Delivery

Finally, value delivery involves delivering the software solution and ensuring it provides the promised value to customers or end-users. This involves designing and developing the software solution, testing and validating it to ensure that it meets user needs and expectations, and deploying it to users.

4.4 Continuous Value Monitoring and Regeneration

Throughout the value creation process, it is essential to continually monitor and measure the value the software solution provides. This can involve collecting and analyzing user engagement and satisfaction data, measuring the impact on key business metrics, and soliciting user feedback to identify improvement areas.

In summary, value creation in software involves identifying opportunities to create value, developing a clear and compelling value proposition, and delivering a software solution that provides the promised value to customers or end-users. Software development teams can create solutions that deliver real user value and drive business success by focusing on these key components.

5. Case Study: Architecting a Communications System

5.1 problem definition.

Are you ready to take on the challenge of solving the age-old information transmission problem across large distances? This task requires your expertise and creativity as a solution architect or systems engineer.

Imagine this scenario: a centrally-located command and control centre needs to receive near-real-time intelligence from geographically remote monitoring outposts. The information must be transmitted quickly, reliably, and securely across long distances.

As the solution architect or systems engineer, you have been tasked with designing a communications system that can meet these demands within a two-year timeline and a budget of just a few million dollars.

To begin, you will need to carefully analyze the system’s requirements. What are the specific needs of the command and control centre and the remote monitoring outposts? What type of information will be transmitted, and how frequently? Once you clearly understand the requirements, you can begin designing a system that meets those needs.

Next, you will need to consider the technical aspects of the system. What type of communication technology will you use? How will the system be secured to prevent unauthorized access? What type of backup systems will be in place in case of a failure? These are just a few technical questions you must answer as you design your communications system.

As you work on your design, don’t forget to consider the budget and timeline constraints. With a few million dollars and two years, you may need to make some strategic choices to ensure the system is completed on time and within budget. This may require you to prioritize certain features or make trade-offs in certain areas.

5.2 Business Value Creation

Below is an executive summary of the task at hand.

• An organization must implement a fast, secure, and reliable intelligence transmission system from outposts in remote areas to a central server in headquarters.
• The organisation’s clients, competitors, suppliers, owners, and employees can influence its progress and be considered stakeholders.
• A two-year timeframe to launch
• A total budget of $5M
• The communication channels between the monitoring stations and the headquarters provide near-real-time, encrypted, and reliable transfer of valuable data.
• Adding new monitoring stations does not result in system changes in other stations or headquarters.
• The system operates reliably under different weather conditions with 99.99% data accuracy.
• The operations team requires no more than basic IT engineering skills to operate the system.
• The accuracy of the information relayed to the centre should be at least 90%.
• The system satisfies the stakeholders’ needs.
• The system is high quality, low cost, safe and easy to operate and maintain.

5.3 Building an Architectural Model

Having established some key requirements of the communications system we want to design, we can now  model the system (using systems modelling language like OPM ) as follows:

The diagram contains entities, states, functions, and forms, which we describe below:

5.3.1 Entities

Entities are objects that constitute the system’s building blocks. The first entity we are concerned with is  Valuable Information  or  Intelligence . The second entity is a property of the  Valuable Information  object, which is its Availability  to the headquarters.

5.3.2 Entity States

States are specific configurations in which a property of an entity can take. Intelligence  can be in two states: 1) unknown, unavailable, or 2) available.

5.3.3 Functions

Functions applied to entities can transform them from one state to another.

• Information Availing  is a function that transfers intelligence between the two states mentioned above. We can identify three instances of this function:  transport ,  mirroring , and  forecasting .
• Transport  is the traditional method of communication where data is physically transported via a medium like radio waves.
• Mirroring  or transportation of entangled quantum bits (or qubits ) forms quantum communication networks.
• Forecast ing is another method for “transporting” information from the future rather than other locations using mathematical models and historical data.

5.3.4 Forms

Forms  are a particular type of entity, differing from the ones mentioned earlier in that these are concrete systems while the main ones (Valuable Information and Availability) are abstractions. Forms are physical systems that deliver the functionality in question.

• Traditional communication systems are based on radio links (wires, antennas, and satellite links). The most mature and well-known of the three options.
• Quantum networks involve quantum processors and qubits. However, their feasibility can be questioned at the time of writing as practical solutions that can be deployed and operated in the field.
• Mathematical models use machine learning or statistical models to predict and forecast future events. Depending on the model’s prediction power, this solution can be viable.

Entities, states, functions, and forms allow us to conceptually represent what the system should do and how it would do it. In the next paragraphs, we will use this example to explain how architecture is created.

Quantum Computing, Beyond Qubits – Part 1: Starting With the Basics

6. Principles of Building a Solution Architecture

Melvin Conway presented a five-stage approach to large system design. The following quote from his article How Do Committees Invent presents those stages:

The life cycle of a system design effort proceeds through the following general stages:

• Drawing of boundaries according to the ground rules.
• Choice of a preliminary system concept.
• Organization of the design activity and delegation of tasks according to that concept.
• Coordination among delegated tasks.
• Consolidation of subdesigns into a single design

— Melvin Conway, How Do Committees Invent

In the following paragraphs, we will focus extensively on points 1 and 2, the rest (points 3-5) being a particular work method proposed by Conway for consultancy organisations engaging in designing large systems.

6.1 The Two Stages of Architecture

Solution architecture is a critical aspect of any project, as it defines the overall structure and functionality of the solution. It is a multi-stage process that involves both concept creation and concept selection .

Concept creation is the first stage in solution architecture, focusing on determining what works and what doesn’t. This stage involves brainstorming and ideation to come up with various possible solutions. It also includes the creation of architectural models, which provide a visual representation of the proposed solutions. The outcome of the concept creation activity is an architectural model representing the most promising solution.

Concept selection is the second stage in solution architecture, where the focus is on choosing the best solution from among the various possibilities. When selecting a solution, there are several things to consider, including:

Considering these factors, the best solution can be identified and implemented. The concept selection stage is critical to the success of any project, as it ensures that the solution meets the requirements and constraints. With a robust solution architecture in place, project teams can ensure that their solutions are reliable, scalable, and capable of meeting the needs of the end users.

6.2 What Is Concept Creation in Architecture?

If we look closer at the case study above on the communications system, every function , major and specialized form is a potential distinct solution to our problem. Let’s review these options:

• Solutions 1: Classical transport, radio and satellite Links
• Solutions 2: Statistical prediction, mathematical models, and AI – driven solutions

These combinations of function, form, and specialization are called concepts .

Concept : a system vision that embodies working principles and a mapping from function to form.

— MIT OpenCourseWare, System Architecture and Concept Generation

The process that generates solutions is known as Concept Creation and involves several steps, as illustrated in the communications system case study:

Logical decomposition is a critical topic we explored in greater detail in the article on Complex Problem Solving.

Complex Problem Solving Guide: Mastering the Art of Tackling Challenges

6.3 Form-Function Mapping

Function-form mapping is an essential step in any design exercise. Here are its fundamentals ideas:

The below diagram takes us back to the communications system case study.

On the left-hand side, we can see how the main Information Availing function can be decomposed into a primary part responsible for generating forecasts while secondary supporting functions are responsible for the admin part of the system, such as user setup and maintenance, data collection, processing, and storage, and reporting functionalities.

On the right-hand side, we have the submodules of the system. At its core is the statistical model responsible for generating forecasts, while other modules, such as Active Directory, provide user access and security functions.

6.6 Concept Selection

Concept selection is the application of decision analysis to select an optimal solution from a candidate list. Below are some of its key ideas:

Any selection method you use should satisfy the following constraints to be usable:

Decision Making In a Professional Environment: Techniques and Pitfalls

7. Concept Creation and Software Solutions Architectures

NASA Systems Engineering Handbook describes an interesting process for approaching design problems. The process is very systems engineering-oriented and must be adapted to suit software design problems. The essence, however, is the same.

On a high level, the process consists of two major stages that are iteratively applied to produce an optimal solution. A high-level requirement is established in the first stage, off of which a high-level design is produced. In the next stage, specific technical choices are made, requiring gathering additional, albeit low-level, requirements. This time, a low-level design is produced on these requirements.

The low-level design is validated to ensure it satisfies both levels of requirements.

The details of each step are as follows:

• Step 1: The process starts with stakeholder requirements turning into concrete objectives . A Business Requirements Document (or BRD ) typically documents these needs.
• Step 2: A High-level Solution Design (or HLD ) is generated based on the BRD for the stakeholders to review and sign off. At this stage, the business requirements and the design are still high-level, and there is a considerable challenge in providing lower-level detailed requirements without making further design decisions.
• Logical Flow
• Functional Flow
• Behavioural
• States and modes
• Depending on the system’s complexity, there may be one or more decomposition levels.
• Step 4: Now that technical design choices have been made, the second round of requirements gathering needs to be completed. Here, the requirements are low-level and delve into the specific details of the subfunctions and specialised forms.
• Step 5: A Low-Level Solution Design (or LLD ) is produced off of the detailed requirements. The detailed design is now assessed for technical feasibility and quality assurance . If it’s deemed unfeasible, an alternative low-level design is produced.
• Step 6: A failure to produce a working design might trigger a revision of the low-level requirements. Perhaps they need to be relaxed or even fundamentally changed.
• Step 7: The design is then assessed on a functional basis. It is adopted if it satisfies all stakeholder requirements, follows industry best practices, and passes regulatory mandates. Otherwise, the high-level design is altered, and the cycle starts again.
• Step 8: A failure to produce a working design that passes functional tests might prompt a revision of the high-level requirements. A new concept might be tried.

The central theme of this approach is the iterative process that cycles through the alternative solutions to produce an optimal solution. It is also acceptable to simultaneously test out variations of the low-level design (through simulations, for example, or POCs) to identify the best combination.

Before we end this section, a few words on the decomposition process itself (Step 3 above), why it is needed, and what would be an appropriate depth and breadth of its levels.

Decomposition is a method for dealing with the limits of our cognitive abilities. In a famous article published in 1956 by George A. Miller , he stated that our minds could faithfully retain seven chunks of data on average and make correct absolute judgments on problems with around seven elements (like estimating the number of beans on a floor).

If you have a system composed of many components, you can organize them logically or functionally in a hierarchy where any level in this hierarchy contains around seven elements.

Another straightforward application that I find very useful is maintaining no more than seven lines in a single PowerPoint slide and where each sentence is around seven words.

Part 5: High-Level Solution Design Documents: What Is It and When Do You Need One

8. Architecture and Complexity

In today’s market, a product must offer rich functionality to remain competitive. To achieve this, the subfunctions and secondary forms of the product must be numerous. If not, the product will only offer the bare essentials, which is unlikely sufficient in today’s sophisticated market.

Client tastes have evolved with time, becoming increasingly sophisticated. Decision-making has also shifted from technical experts to business people. As a result, products must offer a wide range of supporting functionality to compete effectively. This, however, means that products are becoming more complex and more challenging to design.

Complex systems with numerous parts and plenty of functionality can be costly. Design optimization is crucial to keep costs down, but this exercise has its price. Design optimization results in high interconnectivity between functions and forms, increasing the overall number of parts and using existing functionality best by leveraging reusable components and processes.

However, a complicated technology stack combined with users who only know what they want once they start using the systems complexifies the process substantially. These new system properties make predicting the system’s evolution and the user’s requirements challenging. Optimization brings complexity, which, in turn, leads to fragility. The system architecture’s job is to manage that complexity.

In summary, the forces of complex system design are many. User preferences evolve with time, and the need to remain competitive and user interaction with the system are just a few. Design optimization is necessary to keep costs down, but it brings about complexity, leading to fragility. The system architecture’s job is to manage this complexity to ensure the product remains robust and reliable. Ultimately, the relationship between complexity, optimization, and a highly-connected system with many parts is critical in software systems, the global economy, and the political system.

Complexity in Natural and Human Systems — Why and When We Should Care

9. Final Words

A few decades ago, architecture was simple enough. Solutions consisted of a few applications, and these were faithfully modelled in the traditional Model-View-Control blueprint.

This architecture can now be considered severely outdated; any modern solution has to make place for single-sign-on, analytics, automated testing, and continuous delivery at a minimum. Modern architecture needs to allow for that.

Architecture also involves intensive decision-making activities and can significantly impact influential players, making it more crucial to have a decision-making framework that helps avoid emotionally-driven choices with adverse strategic consequences.

Making the right decisions early on can avoid significant redesign efforts later in the implementation. It is sometimes tempting to give in to management pressure to reduce design efforts for cost or time. Pressure can likewise be applied to force specific views by influential experts in the organization.

Therefore, sound architecture also balances what’s practical and what works. We hope the ideas in this article help you find that balance.

Principles of Operational Excellence in Software Development

System architecture is the design and organization of a complex system. An example of system architecture could be designing a computer network or organising components in a manufacturing system.

A good system architecture is designed to meet the needs of stakeholders, is reliable, scalable, and efficient, and is easy to maintain and modify as requirements change over time. A good system architecture should also be flexible and accommodate future growth and technological changes.

The four types of system architecture are monolithic, client-server, microservices, and event-driven architecture.

System architecture in programming refers to how the various components of a software system are designed and organized to work together to meet users’ needs.

Systems architects are responsible for designing and organizing complex systems. They ensure the system meets stakeholders’ requirements and is reliable, efficient, and scalable.

The three types of system architecture are enterprise architecture, solution architecture, and system of systems architecture.

11. References

• Nasa Systems Engineering Handbook
• MIT OpenCourseWare lecture on System Architecture:

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